RESEARCH CENTRE

Inria Centre
at Université Côte d’Azur

2023
ACTIVITY REPORT

IN PARTNERSHIP WITH:

INRAE, CNRS, Université Côte d’Azur

Project-Team

MACBES

Modelling And Control of Biological and
Ecological Systems

IN COLLABORATION WITH: Institut Sophia Agrobiotech, Institut de
pharmacologie moléculaire et cellulaire

DOMAIN

Digital Health, Biology and Earth

THEME

Modeling and Control for Life Sciences

Contents

Project-Team MACBES

1 Team members, visitors, external collaborators

2 Overall objectives

3 Research program

3.1 Network interactions for cell function and growth . . . . . . . . . . . . . . . . . . . . . . . . .
3.2 Dynamics and control for synthetic biology . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.3 Modeling agro-ecological interactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.4 Design and control of managed ecosystems . . . . . . . . . . . . . . . . . . . . . . . . . . . .

4 Application domains

5 Social and environmental responsibility

5.1 Impact of research results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

6 Highlights of the year

6.1 Awards . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

7 New software, platforms, open data

7.1 New software . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7.1.1 EASIDRUG . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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8 New results

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8.1 Network interactions for cell function and growth . . . . . . . . . . . . . . . . . . . . . . . . .
6
8.1.1 Cellular response and cell-to-cell variability . . . . . . . . . . . . . . . . . . . . . . . .
7
8.1.2 Intercellular communication in peripheral clocks . . . . . . . . . . . . . . . . . . . . .
7
8.1.3 Cell economy and control of cell growth . . . . . . . . . . . . . . . . . . . . . . . . . .
7
8.2 Dynamics and control for synthetic biology . . . . . . . . . . . . . . . . . . . . . . . . . . . .
8
8.2.1 Dynamics in networks of cellular oscillators . . . . . . . . . . . . . . . . . . . . . . . .
8
8.2.2 Optimization and optimal control in the cell . . . . . . . . . . . . . . . . . . . . . . . .
8
8.3 Modeling agro-ecological interactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
8
8.3.1 Ecophysiological modeling of plant-microbiota interactions . . . . . . . . . . . . . .
9
8.3.2 Epidemiological modeling of plant-enemy interactions . . . . . . . . . . . . . . . . .
8.4 Design and control of managed ecosystems . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
8.4.1 Design and control of synthetic microbial ecosystems . . . . . . . . . . . . . . . . . . 10
8.4.2 Design of biological control strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
8.4.3 Sustainable management of plant resistance . . . . . . . . . . . . . . . . . . . . . . . . 11

9 Bilateral contracts and grants with industry

11
9.1 Bilateral Grants with Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

10 Partnerships and cooperations

12
10.1 International initiatives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
10.1.1 Associate Teams in the framework of an Inria International Lab or in the framework

10.3 European initiatives

10.2 International research visitors

of an Inria International Program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
10.2.1 Visits of international scientists . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
10.2.2 Visits to international teams
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
10.3.1 Horizon Europe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
10.4 National initiatives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
10.4.1 Inria funding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
10.4.2 INRAE funding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

11 Dissemination

16
11.1 Promoting scientific activities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
11.1.1 Scientific events: organisation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
11.1.2 Journal
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
11.1.3 Invited talks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
11.1.4 Scientific expertise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
11.1.5 Research administration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
11.2 Teaching - Supervision - Juries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
11.2.1 Supervision . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
11.2.2 Master theses and internships . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
11.2.3 Juries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
11.3 Popularization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
11.3.1 Internal or external Inria responsibilities . . . . . . . . . . . . . . . . . . . . . . . . . . 20
11.3.2 Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

12 Scientific production

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12.1 Major publications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
12.2 Publications of the year
12.3 Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
12.4 Cited publications

Project MACBES

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Project-Team MACBES

Creation of the Project-Team: 2023 July 01

Keywords

Computer sciences and digital sciences

A6. – Modeling, simulation and control

A6.1.1. – Continuous Modeling (PDE, ODE)

A6.1.4. – Multiscale modeling

A6.2.6. – Optimization

A6.3.4. – Model reduction

A6.4.1. – Deterministic control

A6.4.4. – Stability and Stabilization

A6.4.6. – Optimal control

A8.7. – Graph theory

A8.11. – Game Theory

Other research topics and application domains

B1.1.2. – Molecular and cellular biology

B1.1.7. – Bioinformatics

B1.1.8. – Mathematical biology

B1.1.10. – Systems and synthetic biology

B2.4.1. – Pharmaco kinetics and dynamics

B3.1. – Sustainable development

B3.5. – Agronomy

B3.6. – Ecology

2

Inria Annual Report 2023

1 Team members, visitors, external collaborators

Research Scientists

• Frédéric Grognard [Team leader, INRIA, Researcher, HDR]

• Valentina Baldazzi [INRAE, Researcher, HDR]

• Pierre Bernhard [INRIA, Emeritus, until Aug 2023]

• Madalena Chaves [INRIA, Senior Researcher, Vice-team leader, HDR]

• Jean-Luc Gouzé [INRIA, Senior Researcher, HDR]

• Ludovic Mailleret [INRAE, Senior Researcher, HDR]

• Jérémie Roux [CNRS, Researcher, HDR]

• Suzanne Touzeau [INRAE, Researcher]

Post-Doctoral Fellows

• Clotilde Djuikem [UNIV COTE D’AZUR, until Aug 2023]

• Giada Fiandaca [INRIA, from Nov 2023]

PhD Students

• Odile Burckard [INRIA]

• Benjamin Böbel [INRIA]

• Javier Innerarity Imizcoz [UNIV COTE D’AZUR, from Nov 2023]

• Pauline Mazel [UNIV COTE D’AZUR, from Oct 2023]

• Joseph Junior Penlap Tamagoua [INRIA]

Interns and Apprentices

• Javier Innerarity Imizcoz [INRIA, Intern, from Apr 2023 until Aug 2023]

Administrative Assistant

• Maeva Jeannot [INRIA]

Visiting Scientists

• Aurelien Kambeu Youmbi [UNIV DSCHANG, CAMEROON, from Dec 2023]

• Frank Kemayou Mangwa [UNIV DOUALA, CAMEROON, from Dec 2023]

External Collaborators

• Vincent Calcagno [INRAE, from Oct 2023, HDR]

• Frédéric Hamelin [INSTITUT AGRO RENNES-ANGERS, from Oct 2023, HDR]

• Marielle Péré [Inria Start-up studio, from Jul 2023]

• Louise Van Oudenhove De Saint Gery [INRAE, from Oct 2023]

Project MACBES

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2 Overall objectives

Understanding and controlling dynamics are at the core of major challenges in biology and ecology central
to human and environmental health. With the increasing availability of experimental data time-series in
these fields and better comprehension of the fundamental biological mechanisms, building models is
required to fully grasp these dynamics. The objective of MACBES is to apply and develop methodologies of
control theory and computational biology to specific applications in biology and ecology: the ecologically
friendly protection and management of ecosystems, such as agroecosystems, and the characterization
and deciphering of mammalian cell responses to their environment, in particular the effect of network
interactions and developments in synthetic biology. MACBES has privileged access to biological data
generated by the partners within the Common Project Team which allows for the development of the
most relevant models related to its applications.

Control theory provides answers to questions related to identify parameters, reconstruct non meas-
ured quantities of interest, regulate and control the system towards a desired state and optimize the yield
of a given product. In computational biology, the tools of theoretical ecology and evolutionary biology
provide answers on what a system will become.

The development of dynamical models representing mechanisms and interactions within our systems
of interest is a first step in our approach. We develop models built in continuous ordinary differential
equations, impulsive models, discrete models, or hybrid models, to better represent the variety of
biological processes. In their diversity, these models are often built on representations of simplified
biological processes, which yield systems that have particular structures that can be exploited: their
variables are positive, some interactions can be modeled as mass transfers, they can be monotonic,. . .
Such models allow for analytical and numerical developments that help explaining the dynamics and
the functioning of biological processes. These models are the cornerstones on which we can apply the
comprehensive toolbox of control theory.

The link of our models to data depends on the context. On the one hand, we are at a turning point
where the availability of “omics” and cell level data exceeds our capacity of interpretation, while on the
other hand it may still be difficult to obtain reliable and useful data time series to understand ecosystem
dynamics, though that could soon change too with the development, reliability and increasing affordabil-
ity of remote sensing data through drones. Therefore, apprehending the complexity of these processes
and interactions through this abundance of data or despite data scarcity, requires the construction of
specific mathematical models with specific calibration approaches, that face the large uncertainties and
variability that are intrinsic to biological systems. In addition, to limit the impact of uncertainties and
callibration errors on our results, we also develop models and control theoretic approaches relying on
qualitatively described functions, through which generic answers can be sought that are valid over a wide
range of situations and parameter values.

MACBES is a common project-team between Inria, INRAE, CNRS and Université Côte d’Azur, associat-
ing researchers of Inria d’Université Côte d’Azur, Institut Sophia Agrobiotech (ISA - UMR INRAE CNRS and
Université Côte d’Azur, Models and Methods for Plant Protection team), and Institut de Pharmacologie
Moléculaire et Cellulaire (IPMC - UMR CNRS and Université Côte d’Azur). MACBES was created on July
1st, 2023 and is one of the two project-teams following the Biocore project-team.

3 Research program

The research program is organized around four axes inolving common tools from control theory and
computational biology, with models built in continuous ordinary differential equations, impulsive models,
discrete models, or hybrid models. Control theory provides answers to questions related to the need to
identify parameters, reconstruct non measured quantities of interest, regulate and control the system
towards a desired state and optimize the yield of a given product. In computational biology, we use the
tools of theoretical ecology and evolutionary biology to provide answers on what a system will become.
The fours research axes of MACBES are:

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Inria Annual Report 2023

3.1 Network interactions for cell function and growth

Cells have evolved highly sophisticated intracellular communication pathways to enable their develop-
ment and growth, under multiple environmental stresses and stimuli (growth factors, hormones, different
types of drugs, temperature or light changes, etc.). In a modular view of a biological organism, each task is
executed by a specific network, or module. These modules often interact with each other, one task trigger-
ing the next in a chain of events or cyclic phenomena: cascades of signaling networks, genetic-metabolic
interactions, oscillatory behavior. One of the greatest challenges at the interface between biology and
mathematics is to decipher and reproduce the complex behavior arising from the interconnection of
two or more modules. The ability to reproduce the complexity of cellular responses will lead to a better
capacity for regulation and balancing of factors towards healthy behaviors.

3.2 Dynamics and control for synthetic biology

Synthetic biology aims at joining elements from both biology and engineering to construct cellular
circuits that perform a desired function or induce a particular type of response. It is also a complementary
approach to (traditional) molecular biology: newly creating and assembling synthetic cellular circuits
from basic biological components (such as DNA, proteins, or metabolites) to form a “whole organism”,
serves as a proof of principle towards understanding the mechanisms of biological networks. One of
the main bottlenecks in synthetic biology is how to integrate the new circuit into the cell’s machinery,
without upsetting the cellular resource allocation balance. To tackle this problem, understanding resource
allocation in the cell and the interconnection of cellular oscillators is a crucial challenge.

3.3 Modeling agro-ecological interactions

Plants are involved in a wide range of biotic interactions. Some are beneficial to plant health, as for
pollinators or symbiotic organisms, whereas others are detrimental, as in the case of pathogens or
herbivores. The dynamics and outcome of these interactions depend on the ecological conditions,
including the phenotypes of the interacting species, their physiology and the abiotic environment in
which the interactions take place. Our aim is to develop models relevant to several biotic interactions
involving plants and other organisms, from the ecophysiological scale and the intimate interaction
between plants and their partners, to the ecological interactions between populations and communities
inhabiting crop fields.

3.4 Design and control of managed ecosystems

In several contexts, such as bioreactors in industry or cropping systems in agriculture, it might be desirable
to create an ecosystem that does not exist as is in nature. Putting together species that have mutualistic
behaviors, whose synergy allows for the production of some desired output, or that protect one another,
can enhance the functioning of the resulting ecosystem. Without going as far as designing an ecosystem
de novo, it might also be necessary to take control actions to improve the functioning of an existing
ecosystem or to restore a degraded ecosystem to a previous, desirable, state. The exploitation of natural
or synthetic microbial communities for the accomplishment of processes of interest is being pursued in a
vast range of scenarios, from established applications in the biotechnology and pharmaceutical industries,
to innovative applications in medicine and environmental sciences. Larger scale managed ecosystems
can simply be natural ecosystems into which one wants to re-introduce or maintain endangered species,
but they can also be exploited ecosystems such as forests, agricultural fields, fish farms. . . A special focus
is put in MACBES on the development of pest/pathogen control methods in agroecosystems.

4 Application domains

As highlighted in the research program, in MACBES, we tackle real-life problems and contemporary
challenges with respect to safe food, food security, human and environmental health. We develop
mathematical techniques to characterize and decipher cell responses to their environment in research

Project MACBES

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axes 3.1 and 3.2, and we deal with ecologically friendly methods for the protection and management of
ecosystems, in particular of agroecosystems, in research axes 3.3 and 3.4.

5 Social and environmental responsibility

5.1 Impact of research results

The application of MACBES research for the development of ecologically friendly methods for crop
protection aim at sustainable agroecosystems. Central to our work is the reduction of chemical pesticide
usage, whose deleterious impact on health and the environment is well-documented. The applications
concerning cell dynamics may impact the development of new anti-cancer drugs and in general aim at a
better understanding of mechanisms affecting human health.

6 Highlights of the year

• Marielle Péré was awarded the i-PhD Concours d’Innovation grand prize for her participation, based
on her thesis work, in the start-up project CellEmax which goal is to propose rational identification
of new targets for anticancer combination treatments.

• Different strains of a microorganism growing in the same environment display a wide variety of
growth rates and growth yields. We developed a coarse-grained model to test the hypothesis that
different resource allocation strategies, corresponding to different compositions of the proteome,
can account for the observed rate-yield variability [2]. Validated by a compiled database of hundreds
of published rate-yield phenotypes of Escherichia coli strains, the model highlights the complex
nature of the relationship between metabolites, growth rate, and yield. An interesting prediction of
our model is that high growth rates are not necessarily accompanied by low growth yields: high-rate,
high-yield growth of E. coli can be achieved by a higher saturation of enzymes and ribosomes, and
thus by a more efficient utilization of proteomic resources.

• A workhop on mathematical modelling in tropical agriculture was organised in Dschang, Cameroon,
1-4 November 2023. Its aims were twofold: bring together people involved in the EPITAG associate
team to present scientific achievements and discuss planned work, so as to capitalise on the
experience gained; present EPITAG and foster interest in its approaches, in particular among
young researchers. The workshop was a success: there were 18 presentations and more than 30
participants from the universities of Dschang, Douala, Yaoundé, and from France (hybrid meeting),
among which a majority of young scientists. Most participants were applied mathematicians, but
biologists also attended the workshop.
More details on the EPITAG website.

6.1 Awards

• Marielle Péré obtained a STIC Doctoral School prize for her thesis “Modeling cancer drug response

dynamics in single-cells to predict the emergence of drug-tolerant cells”.

7 New software, platforms, open data

7.1 New software

7.1.1 EASIDRUG

Name: EArly Single-cell Isolation with a Drug Response Up-Graded forecaster for live-cell microscopy

assays

Keywords: Machine learning, Live-cell microscopy, FRET (Foster resonance energy transfert), Forecast-

ing, Pharmacology, Cancer, Time-trajectories classification

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Inria Annual Report 2023

Scientific Description: This software will be used by the experimental team to select cancer cells during

live-cell microscopy expriments.

Functional Description: This software follows 4 steps: 1 - Download FRET trajectories of Hela clonal
cancer cells treated with TRAIL from the article database: Roux, Jérémie, et al. "Fractional killing
arises from cell-to-cell variability in overcoming a caspase activity threshold." Molecular systems
biology 11.5 (2015): 803 and identification of the TRAIL treatment response phenotype. 2 - Ex-
traction of more than 900 mechanical and statistical features of the FRET signal for each cell. 3 -
Selection of a group of N characteristics to identify the future response (tolerant/sensitive) to TRAIL
treatment for a maximum number of cells and creation of a response forecasting algorithm (SVM
1d) taking these fetaures as input. 4 - Cross-validation of the algorithm

Release Contributions: First version, to be improved and transformed into a platform

Publications: hal-03868577, hal-03868542, hal-03868569, hal-03868584, hal-03522480

Contact: Marielle Pere

Participants: Marielle Pere, Jeremie Roux, Asma Chalabi, Madalena Chaves

Partner: Institut de Pharmacologie moléculaire et cellulaire (IPMC)

8 New results

The MACBES project-team was created on July 1st, 2023. However, in order to present a sufficient body of
work covering all the aspects of our activity, we decided to present works covering the whole 2023 year.

8.1 Network interactions for cell function and growth

Participants: Odile Burckard, Madalena Chaves, Giada Fiandaca, Marielle Péré,

Jérémie Roux, Jean-Luc Gouzé, Valentina Baldazzi, Pauline Mazel.

8.1.1 Cellular response and cell-to-cell variability

Cell response through the apoptotic pathway To analyze the considerable amount of data from fate-
seq[58], we proposed an ODE model of the molecular pathways involved in cell death triggered by
Tumor necrosis factor (TNF)-related apoptosis-inducing ligand (TRAIL) calibrated on single-cell time-
trajectories of a Förster resonance energy transfer (FRET) reporter measuring apoptosis signaling dy-
namics in clonal HeLa cells [60]. With this model, we constructed a timeline for the different steps in the
regulation of apoptosis and located an initial cell fate decision just after TRAIL binding [62]. Furthermore,
we identified three specific parameter combinations that can distinguish between drug resistant or sens-
itive phenotypes. The next step was to combine the ODE model’s mechanistic features with predictive
values for cell decision with machine-learning classification models, to determine the drug response of
each cell before it commits to an irreversible decision. Our mechanistic-informed approach, combining
an ODE system with machine learning classifiers, outperformed classic machine learning approaches
and enabled the accurate cell response prediction of otherwise unpredictable cells [61]. This part of the
work was in collaboration with Diego Oyarzún (University of Edinburgh). This methodology is part of
Marielle Péré PhD thesis [37], who won a STIC Doctoral School prize.

In addition, based on her thesis work, Marielle participated to the start-up project CellEmax, which
goal is to propose rational identification of new targets for anticancer combination treatments, for which
she was awarded an i-PhD Concours d’Innovation grand prize.

Project MACBES

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Optimization of cancer treatment Another line of research involves the application of optimal control
to Lotka-Volterra models of competition between cancerous and healthy cells. The aim is to control
cancer progression while reducing the harmful effects of chemotherapy. This strategy aims to strike a
balance between eliminating cancer cells while preserving healthy tissues, providing a more refined
method to manage the impact of cancer treatments. This is the subject of the PhD thesis of Pauline Mazel.

8.1.2 Intercellular communication in peripheral clocks

The intercellular interactions between peripheral circadian clocks, located in tissues and organs other
than the suprachiasmatic nuclei of the hypothalamus, are still very poorly understood. To investigate
this question, we performed a theoretical and computational study of the coupling between two or
more clocks, using a reduced model of the mammalian circadian clock previously developed in [1].
Based on a piecewise linearization of the dynamics of the mutual CLOCK:BMAL1 / PER:CRY inactivation
term, we proposed a segmentation of the circadian cycle into six stages, to help analyze different types
of synchronization between two clocks, including single stage duration, total period, and maximal
amplitudes. Our model reproduces some recent experimental results on the effects of different regimes of
fasting/feeding alternance in liver circadian clocks of mice [53]. This method helps to further characterize
the synchronization steps between two clocks of distinct (but close) periods. This work was presented
by Odile Burckard at the 48th Congress of the Société Francophone de Chronobiologie [28]. In addition,
through the analytical study of the above piecewise linear model of the clock, we proposed an Algorithm
to generate biologically-consistent circadian oscillators. Our study provides a characterization of the
cycle dynamics in terms of four fundamental threshold parameters and one scaling parameter, as it
recapitulates the main observations from the literature. Moreover, our analysis shows robustness of the
circadian system and its period, and identifies critical points for correct cycle progression [46], [38]. This
work is in collaboration with F. Delaunay (ANR InSync), and is part of Odile Burckard PhD thesis.

8.1.3 Cell economy and control of cell growth

Microbial growth consists of the conversion of nutrients from the environment into biomass and small
energy cofactors (ATP, NADH, NADPH, ...) driving biomass synthesis forward. Two macroscopic criteria
for characterizing microbial growth are growth rate and growth yield. The former refers to the rate of
conversion of substrate into biomass, and the latter to the efficiency of the process, that is, the fraction of
substrate taken up by the cells that is converted into biomass.

In the framework of the ANR Maximic project (collab. H. de Jong, MICROCOSME team, and T. Gedeon,
Montana State University), we developed a coarse-grained model of coupled energy and mass fluxes
in microorganisms, based on minimal assumptions, and used it to explore the variability of rate-yield
phenotypes obtained by change in proteome allocation strategy [11]. The model predictions were
verified by means of a database of hundreds of published rate-yield and uptake-secretion phenotypes
of Escherichia coli strains grown in standard laboratory conditions. We found a very good quantitative
agreement between the range of predicted and observed growth rates, growth yields, and glucose uptake
and acetate secretion rates. These results support the hypothesis that resource allocation is a major
explanatory factor of the observed variability of growth rates and growth yields across different bacterial
strains. One of the main outcomes of our model, supported by the experimental data, is that high growth
rates are not necessarily accompanied by low growth yields. The resource allocation strategies enabling
high-rate, high-yield growth of E. coli lead to a higher saturation of enzymes and ribosomes, and thus to a
more efficient utilization of proteomic resources.

The model is currently used to investigate the set of adaptation strategies that microbial cells can use
to increase their growth rate or their growth yield in a given environment. Preliminary results suggest
that multiple allocation choices are possible, depending on the initial allocation state of the cell and its
biomass composition.

8.2 Dynamics and control for synthetic biology

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Inria Annual Report 2023

Participants: Benjamin Böbel, Madalena Chaves, Javier Innerarity Imizcoz, Jean-

Luc Gouzé.

8.2.1 Dynamics in networks of cellular oscillators

Weak synchronization and convergence in coupled genetic regulatory networks. We consider a
general model of genetic networks and examine two forms of interconnection, either homogeneous or
heterogeneous coupling, corresponding to coupling functions that are either equal or different from those
governing the individual dynamics. In the case of individual subsystems having unique but different
steady states, we prove that the homogeneous coupled system has a unique globally asymptotically stable
steady state. Moreover, in the case of large coupling strength, we show that under suitable assumptions the
network achieves weak synchronization since the individual steady states become arbitrarily close [10].
We apply the results to the synchronization of damped oscillators and to the control of multistable
systems.

Synchronization of circadian clock models. To study coupling and synchronization of two clock
oscillator models, we have used Lyapunov function techniques to bound the difference between the two
oscillators in terms of the difference between their oscillating periods. We have also analyzed the form of
the periodic solutions as a function of some of the parameters, in particular one of the major degradation
rates. This is part of Benjamin Böbel PhD thesis.

8.2.2 Optimization and optimal control in the cell

Optimal allocation of resources in a bacteria. We study by techniques of optimal control the optimal
allocation between metabolism and gene expression during growth of bacteria, in collaboration with
Inria IBIS and MCTAO project-teams. We developed different versions of the problem, and considered
problems where the aim is to optimize the production of a product in a batch or fedbatch bioreactor;
the input of substrate may also be fluctuating [21], (ANR project Maximic, PhD thesis of Agustin Yabo,
internship then ongoing PhD of Javier Innerarity Imizcoz , in collaboration with W. Djema (Biocore) and
F. Mairet (IFREMER Nantes)).

8.3 Modeling agro-ecological interactions

Participants:

Valentina Baldazzi,
Suzanne Touzeau,
Frédéric Grognard,
Ludovic Mailleret, Clotilde Djuikem, Aurelien Kambeu Youmbi,
Frank Kemayou Mangwa, Joseph Junior Penlap Tamagoua.

8.3.1 Ecophysiological modeling of plant-microbiota interactions

Root-knot nematodes (RKN) are microscopic root parasites that cause considerable yield losses in nu-
merous crops worldwide. We are particularly interested in understanding the mechanisms that underlie
plant tolerance, that is the ability of certains plants to sustain RKN infestation with limited damages.
To address this, we built an ecophysiological model of plant growth, including both the vegetative and
the reproductive phases, coupled with a model of nematode population dynamics. Briefly, the plant
is divided into shoots, which provide carbon, and roots, which provide water for plant growth. During
the reproductive phase, fruit onset marks the addition of a new carbon sink for the plant. Nematodes
are explicitly considered as feeding on plant resources, so that any change in the plant physiological
status or plant composition will in turn affect pest growth and multiplication, and vice versa. The appari-
tion of fruits, in particular, can substantially modify the ressource allocation pattern of the plant, with
important consequences on plant susceptibility to pest attack. The model was calibrated for two plant
species using experimental data collected in the framework of INRAE ArchiNem project (2020-2021).
A dedicated calibration pipeline was developed in order to combine heterogeneous data at different

Project MACBES

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time-scales. Eventually, the model will be used to explore the dynamical behaviour of the system and to
gain insight into the relative role of plant development and phenotypic traits (including physiological and
architectural features), pest development and environmental factors in the progression of the infection.
This work is part of the PhD thesis of Joseph Penlap Tamagoua (Inria-INRAE funding 2022-2025) and
was presented at several international conferences [49, 33, 34]. Two publications are currently in prepara-
tion, focusing respectively on the experimental results and on model development and calibration.

8.3.2 Epidemiological modeling of plant-enemy interactions

Semi-discrete models Semi-discrete models have shown their relevance in modeling biological phe-
nomena whose nature presents abrupt changes over time [56]. In plant epidemiology, they can represent
seasonality or external perturbations of natural systems, such as harvest. We developed and analyzed
such models in the context of biological control applied to coffee leaf rust [16] or coffee berry borers [42],
and of the sterile insect technique [32]. Semi-discrete models were central in Frédéric Grognard’s HDR
defense [36] and Clotilde Djuikem’s PhD thesis [35].

In this framework, we studied how recurrent migration events (“pulsed migration”) between different
spatial locations influence the evolution of populations through a population genetics approach [9]. We
evidenced that migration pulsedness affects allele fixation rates in interaction with their selective value,
generally reducing the level of local adaptation as compared to continuous migration. This research
was part of Flora Aubree’s PhD thesis (defended in 2022), and has been performed in collaboration with
Vincent Calcagno (ISA).

Epidemiological models in tropical agriculture We developed and analyzed dynamical systems de-
scribing plant-parasite interactions, in order to better understand, predict and control the evolution of
damages in crops, with applications in tropical agriculture, in the framework of the EPITAG associate
team with Cameroon (section 10.1.1). We considered several pathosystems.

• Coffee berry borers are insects that mostly develop and feed inside coffee berries, and hence cause
major crop damages worlwide. We developed a model describing the coffee berry borer dynamics
based on the insect life cycle and the berry availability during a single cropping season. This PDE
model includes a berry age structure to account for CBB preference for mature berries [17, 42]. This
research pertains to Yves Fotso Fotso’s PhD thesis [52].

• Coffee leaf rust (CLR) is a leaf disease caused by a fungus, Hemileia vastatrix, that has a major impact
on coffee production around the world. We studied a multi-seasonal model of CLR development
in a coffee plantation, with continuous dynamics during the rainy season and a discrete event to
represent the simpler dynamics during the dry season [16, 30]. We also performed a bifurcation
analysis of a more complex model taking the development stage of the leaves into account (paper
under revision). This work is part of Clotilde Djuikem’s PhD thesis that was defended in 2023 [35].

• Cabbage is a very important food crop for small farmers in Cameroon. We developed a model self-
financing model of the crop, which includes the interaction between cabbage and the diamondback
moth, one of its major pest. The main point of this model is the inclusion of the financial balance
of the farm, used for buying young plants and biopesticide spraying. We did a bifurcation analysis
of this bioeconomic model and identified situations with forward or backward bifurcations [31].
This work is part of Aurelien Kambeu Youmbi’s ongoing PhD thesis.

• Bananas, including plantains, are major staple foods in many tropical countries, including Cameroon.
These plants are affected by burrowing nematodes (Radopholus similis) that create root lesions
and induce great damages. We developed a model of the plant-pest interactions with the original
feature that infestation intensity may vary within the root. We did a bifurcation analysis of this
model and developed an optimal control against the pest. This work is part of Frank Kemayou
Mangwa’s ongoing PhD thesis.

Spatial population dynamics of biological control agents We have been involved for several years in a
mixed modeling-experimental approach to explore the spatio-temporal dynamics of populations, with

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Inria Annual Report 2023

special interest to micro-wasp parasitoids [59, 55]. With such an approach, we explored how positive
density-dependence in growth or dispersal interact with spatial heterogeneity to impact population
spread [19]. In this context, we showed that the expansion rate is not only determined by the current
environmental conditions at the edge of the population, but is also strongly influenced by the conditions
encountered at previous times and locations by the moving front of the population. This research has
been performed in collaboration with Elodie Vercken (ISA).

Concurrently, we are exploring the correlation between biological control agents movement char-
acteristics at different scales, from laboratory experimental characterization to semi-field dispersal on
parasitoids belonging to the genus Trichogramma. A specific mid-scale laboratory device to study insect
dispersal over several meters has been designed [15] and used to understand how insect movements
shape group dispersal in such parasitoïds [13]. This research was part of the PhD theses of Victor Burte
(defended 2018) and Melina Cointe (defended 2023, [54]) and was performed in collaboration with
Vincent Calcagno (ISA).

8.4 Design and control of managed ecosystems

Participants:

Touzeau,
Frédéric Grognard,
Jean-Luc Gouzé,
Ludovic Mailleret, Clotilde Djuikem, Aurelien Kambeu Youmbi,
Frank Kemayou Mangwa, Joseph Junior Penlap Tamagoua.

Suzanne

8.4.1 Design and control of synthetic microbial ecosystems

In the framework of ANR project Ctrl-AB, we considered a synthetic algal-bacterial consortium. The
co-culture of E. coli with Chlorella could lead to higher biomass and lipid productivity. We developed a
model, studied its dynamical behaviour and built observers to try to optimize some output [26]. Moreover,
we studied the effects of control on the system (PhD thesis of Rand Aswad, Grenoble, in collaboration
with E. Cinquemani (Microcosme )).

In the framework of IPL Cosy (led by E. Cinquemani), we studied the coexistence of two strains of
bacteria E. Coli in a bioreactor. The strains had been modified synthetically. The aim was to obtain
a better productivity in the consortium than in a single strain, by control methods [57]. We obtained
optimization results for the optimal production or yield [18].

8.4.2 Design of biological control strategies

Sterile insect technique The sterile insect technique (SIT) consists in releasing irradiated sterile indi-
viduals, usually males, that can mate but produce no offspring. SIT is used to reduce pest populations
in an agricultural context. However, a small fraction of irradiated insects may escape sterilization and
remain fertile. We showed that when residual fertility is below a threshold value, wild populations can
be driven to extinction by flooding the landscape with sterile males. Nevertheless, even if the residual
fertility exceeds the aforementioned threshold value, substantial decreases in outbreak levels can be
achieved [48, 29, 47]. In the framework of Taha Belkayate’s internship, we extended these results to take
remating into account. This work pertains to Marine Courtois’s ongoing PhD thesis.

Predator releases for coffee leaf rust Biological control was added to the multi-seasonal impulsive
model describing coffee leaf rust spread in a plantation (section 8.3.2), using predators through one or
more discrete introduction events over the year. Analytical and semi-numerical studies were performed
to identify how much and how frequently predators needed to be introduced. We showed that the best
strategy to efficiently control the disease depends on the predator mortality: low mortality parasites can
be released only once a year, while high mortality parasites should be released more frequently to ensure
their persistence in the plantation [16]. This work pertains to Clotilde Djuikem’s PhD thesis that was
defended in 2023 [35].

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Optimal control for coffee berry borers Controling coffee berry borers is particularly challenging,
as the insects spend most of their life cycle inside berries. Pest control was introduced in the model
describing the interactions between borers and coffee berries (section 8.3.2), based on the combination
of a biopesticide (entomopathogenic fungus such as Beauveria bassiana), that is sprayed and persist on
the berries, and traps. Using optimal control theory, we showed a synergy between the two controls for
profit optimization [17]. We also investigated how to optimize biopesticide spraying considering it as an
impulsive control [42] (accepted in ARIMA). This research pertains to Yves Fotso Fotso’s PhD thesis [52].

8.4.3 Sustainable management of plant resistance

We studied other plant protection methods dedicated to fight plant pathogens. One such method is the
introduction of plant cultivars that are resistant to one pathogen. This often leads to the appearance of
virulent pathogen strains that are capable of infecting the resistant plants.

We built a generic spatio-temporal epidemiological model representing (fungal) disease spread on
annual field crops in a multi-pathogen context. This work benefits from data collected in INRAE projects
COCODIV and DYNAMO on wheat diseases. It will pe pursued in the ENDURANCE and PAPEETE projects
(section 10.4).

An epidemiological model of gene-for-gene interaction has been designed, considering increased
defense to pathogen infections following previous exposure to a pathogen or an elicitor, namely priming.
Priming provides a sort of immunity to virulent pathogens for resistant plants having undergone an infec-
tion attempt by an avirulent pathogen. We developed an epidemiological model to explore how mixing
two distinct resistant varieties can reduce disease prevalence. We considered a pathogen population
composed of three genotypes infecting either one or both varieties. We found that host mixtures should
not contain an equal proportion of resistant plants, but a biased ratio to minimize disease prevalence,
and that it should contain a lower proportion of the costliest resistance for the pathogen to break [14].
This was done in collaboration with Frédéric Hamelin (Institut Agro) in the framework of Pauline Clin’s
thesis.

We also participated in an opinion paper advocating that the theoretical framework of population
genetics could bridge the gap existing between evolution/epidemiology approaches and molecular
approaches to the durability of resistance problem [20]. The ENDURANCE ANR project is built upon the
findings presented in this paper (section 10.4).

9 Bilateral contracts and grants with industry

Participants:

Jérémie Roux, Marielle Péré, Madalena Chaves, Jean-Luc Gouzé.

CellEmax: is an ongoing project of start-up creation. The startup biotech will be a spin-off of our
team and the experimental biology group led by Jérémie Roux at IPMC, to exploit our previous research
results [58] and an invention disclosure (Jérémie Roux, Marielle Péré et al.). The future biotech will be an
innovation-driven company, partnering with pharmaceuticals labs to provide its proprietary technology
on Target Discovery for combination treatment in oncology. In addition to experimental workflows,
the biotech will develop software and algorithmic frameworks of cells dynamics analyses, integrating
machine learning and signal processing.

9.1 Bilateral Grants with Industry

Exactcure: in the collaboration with the start-up Exactcure (Nice), the goal of the project is to study
personalized pharmacokinetic models. We have regular contacts with Exactcure, which hired our PhD
student Lucie Chambon.

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Inria Annual Report 2023

10 Partnerships and cooperations

10.1 International initiatives

10.1.1 Associate Teams in the framework of an Inria International Lab or in the framework of an

Inria International Program

EPITAG

Title: Epidemiological Modelling and Control for Tropical Agriculture

Duration: 2022-2024

Coordinator: Samuel Bowong (sbowong@gmail.com)

Partners:

• University of Douala (Cameroon)

Inria contact: Suzanne Touzeau

Summary: EPITAG gathers French and Cameroonian researchers, with a background in dynamical
systems and control and with an interest in crop diseases. Crop pests and pathogens are responsible
for considerable yield losses and represent a threat to food security. Their control is hence a major
issue, especially in Cameroon, where agriculture is an important sector in terms of revenues and
employment. To help design efficient strategies for integrated pest management, mathematical
models are particularly relevant. Our main objective is to study the epidemiology and management
of tropical crop diseases, with a focus on Cameroon and Sub-Saharan Africa. Our approach consists
in developing and analyzing dynamical models describing plant-parasite interactions, in order to
better understand, predict and control the evolution of damages in crops. To ensure the relevance
of our models, field experts and stakeholders need to be closely associated. We will focus on pest
and pathogens that affect major staple food and cash crops, such as cocoa plant mirids, plantain
and banana plant-parasitic nematodes, coffee berry borers, coffee leaf rust, maize stalk borers,
cabbage diamondback moths, papaya mealybugs, etc. To tackle these issues, we jointly supervise
master and PhD students.

10.2 International research visitors

10.2.1 Visits of international scientists

Other international visits to the team

Julien Arino

Status: professor

Institution of origin: University of Manitoba

Country: Canada

Dates: 3-6 January 2023

Context of the visit: Clotilde Djuikem’s PhD defense

Mobility program/type of mobility: seminar

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Project MACBES

Samuel Bowong

Status: professor

Institution of origin: University of Douala

Country: Cameroon

Dates: 3-8 January 2023

Context of the visit: EPITAG associate team

Mobility program/type of mobility: Clotilde Djuikem’s PhD defense

Aurelien Kambeu Youmbi

Status: PhD student

Institution of origin: University of Dschang

Country: Cameroon

Dates: 6 February – 1 May 2023 & 15 November 2023 – 15 April 2024

Context of the visit: EPITAG associate team

Mobility program/type of mobility: research stay

Frank Kemayou Mangwa

Status: PhD student

Institution of origin: University of Douala

Country: Cameroon

Dates: 6 February – 1 May 2023 & 15 November 2023 – 15 April 2024

Context of the visit: EPITAG associate team

Mobility program/type of mobility: research stay

10.2.2 Visits to international teams

Research stays abroad

Madalena Chaves

Visited institution: Instituto Superior Técnico (Lisbon)

Country: Portugal

Dates: 8-31 July 2023

Context of the visit: collaboration with Rui Dilão on models of cell growth

Mobility program/type of mobility: research stay

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Inria Annual Report 2023

Suzanne Touzeau

Visited institution: University of Dschang

Country: Cameroon

Dates: 29 October – 6 November 2023

Context of the visit: EPITAG associate team

Mobility program/type of mobility: workshop

10.3 European initiatives

10.3.1 Horizon Europe

• NEM-EMERGE: "An integrated set of novel approaches to counter the emergence and proliferation
of invasive and virulent soil-borne nematodes" (2023-2027). This project aims at providing sustain-
able, science-based solutions for both conventional and organic farming sectors based on the prin-
ciples of IPM (integrated pest management), including optimized crop rotations schemes, tailored
host plant resistances, and optimal use of the native antagonistic potential of soils. Moreover,
monitoring and risk assessment tools will be generated to support plant health authorities in
decision and policy making.

10.4 National initiatives

• ANR Ctrl-AB: The objectives of the Ctrl-AB project (2021-2024) are (i) to develop new control
methods for the optimization of the productivity of a microbial community, and (ii) to demonstrate
the effectiveness of these methods on a synthetic algal-bacterial consortium. This project is
coordinated by Jean-Luc Gouzé.

• ANR - Maximic: The goal of the project (2017-2023) is to design and implement control strategies
in a bacterium for producing at maximal rate a high value product. It is coordinated by H. de Jong
(IBIS Grenoble), and involves members of Biocore and McTao.

• ANR - InSync: “Circadian clock synchronization in hepatocytes” (2022-2027). This project aims to
decipher intercellular synchronization mechanisms responsible for robust rhythms in peripheral
clocks. Focusing on hepatocytes, and using both 2D cultures and 3D spheroids, we will study cell
communication patterns and cell clock synchronization. Project coordinated by Madalena Chaves.

• ANR - SuzuKIISS:ME “Gérer Drosophila SuzuKII grâce aux Insectes Super Stériles : Maturation et
Efficacité” (2022-2025). This project covers the ground from the development of the operational
capacity and release strategies to deploy Sterile Insect Techniques (SIT), to the socio-economic
impact of SIT on the control of the fruit fly Drosophila Suzukii.

• ANR - BEEP: “Behavioural Epidemiology and Evolution of Plant Pathogens” (2024-2028). This
project is the first to couple behavioural dynamics and pathogen evolution in plant health, aiming
at identifying where the interplay between growers’ behaviour and pathogen epidemiological and
evolutionary dynamics leads. This project is coordinated by Frédéric Hamelin.

• ANR - ENDURANCE: “ENhanced DURability AgaiNst Crop Enemies” (2024-2027). This projects
aims at giving elements of answers on how to use and deploy pathogen resistances in crops in
order to prevent rapid pathogen adaptation. It will study the genetic determinism(s) of resistance
breakdown (the so-called virulence in the phytopathology literature), the evolution over time
of the virulence allele(s) in pathogen populations and integrate this information into relevant
epidemiological models.

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15

• EcoPhyto - PAPEETE: “Promouvoir l’Agroécologie par la prédiction intégrative du risque sanitaire
à partir de données Participatives d’Épidémiosurveillance à l’Échelle du TErritoire” (2024-2027).
This project aims at using epidemiosurveillance data to reduce the intensive use of agrochemicals.
It will assess health, production and economic risks to help farmers in their decision-making. By
focusing on wheat diseases in an intensive agricultural zone and by involving players from the
farming world, the tool developed in the project will constitute a proof of concept that can be
generalized to other crops and regions.

• EcoPhyto - CACOLAC: “Conceptual framework for analyzing combinations of agroecological levers”
(2024-2027). The models developed in this project will provide a better understanding of the
impact of management measures on the local and landscape dynamics of pests and diseases. These
results will complement previous scientific work by better representing the effects of levers, taking
into account the landscape dimension of practices and/or the multitude of direct and indirect
interactions in communities.

• EcoPhyto CeraTIS Corse: “Territorial management of the Mediterranean fruit fly in Corsica by the
Sterile Insect Technique” (2020-2023). This project is based on a pilot field experiment of sterile
male releases and it integrates population dynamics and socio-economic approaches.

• PEPR Agroécologie et Numérique - MISTIC “Microbiomes de plantes cultivées et TIC” (2023-2028).
The objective of MACBES within this flagship project of the PEPR is to model and analyze plant
microbial communities and their functioning, as well as to design minimal microbial communities
guaranteeing maintained functions.

• ITMO Cancer Aviesan - Cellema: The objective of this project (2022-2025) is to determine the
molecular factors that regulate tumor cell response dynamics to immune cell cytotoxicity and
contribute to the development of diagnosis tools for the rational design of cancer combination
therapies. We will use single-cell response data to develop mathematical models and combine
them with machine learning algorithms to enhance prediction of same-cell responses. Project
coordinated by Madalena Chaves, in collaboration with Jérémie Roux and D. Oyarzun (Univ. Edin-
burgh).

• SIGNALIFE: our team is part of this Labex (scientific cluster of excellence, 2nd period 2020-2024)
whose objective is to build a network for innovation on Signal Transduction Pathways in life Sci-
ences, and is hosted by the University Côte d’Azur. The Labex SIGNALIFE is funding the Innovation
Program Young Entrepreneur Program (YEP) coordinated by Jérémie Roux, entitled “Combination
Target Discovery in Oncology Drug Development: Accelerating Precision Treatment for immuno-
therapies, using Predictive Single-cell Pharmacodynamics” (2022-2025).

• UMT FIORIMED: FioriMed is a Mixed Technology Unit created in January 2015 to strengthen the
production and dissemination of innovation to the benefit of ornamental horticulture. Horticultural
greenhouses are seen as a "laboratory" for the actual implementation of agroecology concepts
with the possibility of generic outcomes being transfered to other production systems. The main
partners of UMT FioriMed are ASTREDHOR (National Institute of Horticulture) and the ISA Joint
Research Unit of INRA-CNRS-Univ. Côte d’Azur.

• EcoPhyto - INTERLUDE: “Territorial innovations to reduce phytoparmaceutical products for the
sustainable production of vegetable crops” (2020-2024). MACBES members participate in a case
study that focuses on the agroecological management of soil pests and pathogens in Provence.

• IHU RespirERA This project for a new Institut Hospitalo-Universitaire (running over 10 years,
2023-2033), is dedicated to Respiratory Health, Environment and Aging, to improve treatment
and reduce incidence of pulmonary diseases linked to pollution and aging. Partners include
University Côte d’Azur, the Centre Hospitalier Universitaire de Nice, and Inserm for a 20 million
Euros funding. Macbes will participate on modeling signaling pathways related to tumor cell
death and identification of drug targets, with the expected supervision of a PhD student and a
Post-doctoral fellow. Project coordinated by Paul Hofman, Charles-Hugo Marquette and Marius
Ilie.

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Inria Annual Report 2023

10.4.1 Inria funding

• Inria Startup Studio: The CellEmax startup project is supported by the Inria Startup Studio for 12
months (2023-2024), granted to Marielle Péré (see Section 9). The Start-up Studio is helping with
the entrepreneurial development of the project.

10.4.2 INRAE funding

• COCODIV: “Crop disease co-occurrence in cereal systems: determinants, role and management
of cultivated and wild diversity from plot scale to landscape level integration”, INRAE SuMCrop
Metaprogramme (2022–2023), in which MACBES is a partner with INRAE Sophia Antipolis.

• DYNAMO: “Drivers of the epidemic dynamics of wheat rusts at the landscape scale of the Zone
Atelier Plaine & Val de Sèvre”, INRAE SPE Division (2022-2024), in which MACBES is a partner with
INRAE Sophia Antipolis.

11 Dissemination

11.1 Promoting scientific activities

11.1.1 Scientific events: organisation

Member of the organizing committees

• We organise a monthly scientific seminar together with the BIOCORE project-team in which
external guests and collaborators are regularly invited. We also organise a yearly four day-retreat
where we share our work of the year; this year, it took place 16-19 october 2023 in Porquerolles.

• Marielle Péré was one of the organizers of the Inria PhD Student Seminars, taking place every two

weeks.

• Valentina Baldazzi participated in the organisation of the ICTP Advanced school on "Quantitative
Principles in Microbial Physiology: from Single Cells to Cell Communities", that took place in
Trieste, Italy in October 2023. link

• Suzanne Touzeau participated in the organisation of the EPITAG workshop at the University of

Dschang, Cameroon, 1–4 November 2023. Cf. 6.

• Suzanne Touzeau was a member of the organizing committee of the International Congress of
Plant Pathology - ICPP 2023 satellite event “How to combine remote sensing with epidemiological
modelling to improve plant disease management?”, Lyon, France, 19–20 August 2023.

• Suzanne Touzeau was a member of the scientific and organizing committees of the Mathematical
Population Dynamics, Ecology and Evolution - MPDEE 2023 conference, CIRM Marseille, France,
24-28 April 2023.

11.1.2 Journal

Member of the editorial boards

• Madalena Chaves is an Associated Editor of SIAM Journal on Applied Dynamical Systems (SIADS),
since January 2015. She is an Associated Editor of the Conference Editorial Board (CEB) of the IEEE
Control Systems Society, since August 2020. She is also an Associated Editor for the new IEEE Open
Access Journal on Control Systems.

• Jean-Luc Gouzé is an Associated Editor of the journal Frontiers in Applied Mathematics and

Statistics (Mathematical Biology).

• Suzanne Touzeau is an Academic Editor of PLOS ONE, since August 2018.

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Reviewer - reviewing activities

• All MACBES members have been reviewers for the major journals in their field: Automatica, IEEE
Transactions on Automatic Control, Journal of Mathematical Biology, Mathematical Biosciences,
New Phytologist...

11.1.3 Invited talks

• Jean-Luc Gouzé and Madalena Chaves gave talks at the "Computing combinatorial dynamics in

high dimensional biological networks", October 2023, Lorenz Center, Leiden, Netherlands.

• Madalena Chaves gave a talk at a Focus session on Network Biology at the Network Science Confer-
ence, July 2023, Vienna, Austria [23]. She also gave talks at the Canceropole PACA Webinar (30 May
2023) and at the Journées Nationales de l’Informatique Mathématique, Paris (April 2023).

• Ludovic Mailleret gave a talk at the conference "Le MOnde des Mathématiques Industrielles",

MOMI2023, Sophia Antipolis, April 2023.

11.1.4 Scientific expertise

• Suzanne Touzeau participated in selection panels for INRAE junior research scientists.

• Madalena Chaves, Frédéric Grognard, and Ludovic Mailleret are members of the INRAE Commis-
sion Scientifique Spécialisée (CSS) for Mathématique, Informatique, Sciences et Technologies du
numérique, Intelligence artificielle et Robotique (MISTI).

11.1.5 Research administration

• Madalena Chaves is member of the local Inria committee for doctoral studies (CSD) and head of
the committee NICE for welcoming external researchers (post-docs, “delegations”). She is also a
representative of Inria at the Canceropole PCA. She is the coordinator of the UE Biologie Systémique
1 of the new Master option on Bioinformatics and Computational Biology of the EUR Sciences du
Vivant et de la Santé. Madalena Chaves is a member of the scientific committee of Labex Signalife
(since 2020).

• Frédéric Grognard is a member of the steering committee of Academy 3, Space, Environment, Risk
and Resilience of UCA-JEDI. He is co-head of the MSc Risk of UCA-JEDI and is a member of the
Scientific Committee of the Agroecosysems department of INRAE.

• Ludovic Mailleret is the head of the M2P2 team (Models and Methods for Plant Protection) of ISA.
He is in the Unit and scientific council of Institut Sophia Agrobiotech, and in the council of the
INRAE PACA centre.

• Ludovic Mailleret is an elected member (since 2020) of the Scientific and Pedagogic Council (CoSP)

of the EUR LIFE (Graduate school in Life and Health Sciences ) of Université Côte d’Azur.

• Suzanne Touzeau is a member of the steering committee of the INRAE Metaprogramme SuM-

Crop“Sustainable Management of Crop Health” (since 2016).

• Valentina Baldazzi and Suzanne Touzeau are elected members of the Institut Sophia Agrobiotech

council.

• Jean-Luc Gouzé is in the Inria committee supervising the doctoral theses (until June), a member
of the steering committee of Labex SIGNALIFE of Université Côte d’Azur, and of the scientific
committee of Académie 4 (Life Sciences) of UCA. He is a member of the board of the SFBT (French
Speaking Society for Theoretical Biology).

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Inria Annual Report 2023

11.2 Teaching - Supervision - Juries

• BUT: Odile Burckard (12h ETD) "Fondamentaux de la programmation" 1st year, IUT de Nice Côte

d’Azur (Département Réseaux et Télécommunications).

• Licence: Clotilde Djuikem (40h ETD) "Analyse et modélisation", PO1, Sciences de la vie, Université

Côte d’Azur, France

• Licence: Clotilde Djuikem (16h ETD) "Fondements 2", PO1 Sciences, ingénierie, technologie,

environnement, Université Côte d’Azur, France

• Licence : Clotilde Djuikem (24h ETD) "Intro. à la modélisation mathématique et numérique", L3,
1st year Engineering in "Genie de l’eau", Polytech Nice Sophia, Université Côte d’Azur, France

• Licence: Clotilde Djuikem (28h ETD)"Statistiques et R", L3, 1st year Engineering in Modeling and

Applied Mathematics, Polytech Nice Sophia, Université Côte d’Azur, France

• Licence: Pauline Mazel (16h TD) and Joseph Junior Penlap Tamagoua (32h TD), “Fondements
mathématiques 1 - partie algèbre linéaire”, L1, Portail Sciences et Technologies, Université Côte
d’Azur, France

• Licence: Frédéric Grognard (42h ETD) and Ludovic Mailleret (24h ETD), “Equations différentielles
ordinaires et systèmes dynamiques”, L3, 1st year Engineering in Modeling and Applied Mathematics,
Polytech Nice Sophia, Université Côte d’Azur, France

• Licence: Joseph Junior Penlap Tamagoua (28h TD), "Approximation de fonctions, intégrales et

EDO", L3 Mathématiques, Université Côte d’Azur, France

• Master : Jean-Luc Gouzé (20h ETD), Madalena Chaves (13.5h ETD), “Modeling biological networks
by ordinary differential equations”, M1, 2nd year Engineering in Génie biologique, Polytech Nice
Sophia, Université Côte d’Azur, France.

• Master: Frédéric Grognard (21h ETD) and Ludovic Mailleret (21h ETD), “Bio-Mathématiques”, M1,
2nd year Engineering in Modeling and Applied Mathematics, Polytech Nice Sophia, Université Côte
d’Azur, France.

• Master: Frédéric Grognard (30h ETD) "Elements of mathematical modelling", M1, MSc in Environ-

mental Hazards and Risks Management, Université Côte d’Azur, France.

• Research School: Suzanne Touzeau gave a lecture at the CIMPA school “Mathematical and statistical

modeling of complex systems", N’Djamena, Chad, 2–13 January 2023.

11.2.1 Supervision

• HDR: Frédéric Grognard. "Modelling and control of managed ecosystems, from bioreactors to

agroecosystems", Université Côte d’Azur, defended February 20th.

• PhD: Marielle Péré. “Modeling cancer drug response dynamics in single-cells to predict the
emergence of drug-tolerant cells", Université Côte d’Azur, defended March 27th. Supervisors:
Madalena Chaves and Jérémie Roux.

• PhD: Clotilde Djuikem. “Modelling and control of perennial plant phytopathogens”, Université
Côte d’Azur, defended January 5th. Supervisors: Frédéric Grognard, Suzanne Touzeau and Samuel
Bowong (Univ. Douala, Cameroon).

• PhD: Melina Cointe. “Mieux prédire la propagation spatiale de groupes de trichogrammes pour
améliorer le biocontrôle : de l’écologie du mouvement à la dispersion dans les cultures”, Université
Côte d’Azur, defended Octobre 13th. Supervisors: Vincent Calcagno, Ludovic Mailleret.

• PhD in progress: Aurelien Kambeu Youmbi. "Self-Financing Model for Cabbage Crops with Pest
Management", University of Dschang,Cameroon, since 2020. Supervisors: Berge Tsanou, Suz-
anne Touzeau and Frédéric Grognard.

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• PhD in progress: Odile Burckard. "Coupling, synchronization, and control of cellular oscillators
through mathematical modeling and analysis", Université Côte d’Azur, since 2021. Supervisor:
Madalena Chaves.

• PhD in progress: Marine Courtois. "Modélisation de la technique de l’insecte stérile dans un
contexte agricole : comment intégrer les réalités biologiques et techniques pour optimiser son
déploiement ?", Université Côte d’Azur, since 2022. Supervisors: Ludovic Mailleret, Suzanne Touzeau
and Louise Van Oudenhove De Saint Gery.

• PhD in progress: Rand Asswad. “Développement de stratégies de contrôle pour les consortiums
microbiens synthétiques”, since 2022, Université Grenoble-Alpes. Supervisors: Jean-Luc Gouzé and
Eugenio Cinquemani (Microcosme, Inria Grenoble).

• PhD in progress: Joseph Junior Penlap Tamagoua. "Ecophysiological modeling of plant-nematode
interactions: Understanding the origins and consequences of differential plant susceptibility",
Université Côte d’Azur, since 2022. Supervisors: Valentina Baldazzi, Frédéric Grognard and Suz-
anne Touzeau.

• PhD in progress: Frank Kemayou Mangwa. "Mathematical modeling and analysis of the impact of
Radopholus similis on the banana-plantain production", University of Douala, Cameroon, since
2022. Supervisors: Samuel Bowong, Suzanne Touzeau and Frédéric Grognard.

• PhD in progress: Benjamin Böbel. "Mathematical models for robustness and control of intercellular
coupling and synchronization between peripheral circadian clocks", Université Côte d’Azur, since
April 2023. Supervisors: Madalena Chaves and Jean-Luc Gouzé.

• PhD in progress: Pauline Mazel. "Modeling, analysis and control of cancer cell population dynam-

ics", Université Côte d’Azur, since 2023. Supervisors: Walid Djema and Frédéric Grognard.

• PhD in progress: Javier Innerarity Imizcoz "Allocation optimale de ressources pour des modèles
mathématiques de micro-organismes dans des conditions environnementales dynamiques", since
October 2023, Université Côte d’Azur, Supervisors: Jean-Luc Gouzé, Walid Djema (team Biocore)
and Francis Mairet (Ifremer Nantes).

11.2.2 Master theses and internships

• L2: Jules Baldous. "Inflation écologique, interactions proies-prédateurs et modélisation des aug-

mentoriums." Supervisor: Ludovic Mailleret.

• M2: Taha Belkhayate. "Modélisation de la technique de l’insecte stérile avec sexage imparfait",
Université de Pau et des Pays de l’Adour. Supervisors: Marine Courtois, Louise Van Oudenhove De
Saint Gery and Ludovic Mailleret.

• M2: Javier Innerarity Imizcoz "Optimisation de la croissance microbienne sous conditions périod-

iques", Sorbonne Université. Supervisors: Jean-Luc Gouzé and Walid Djema (Biocore team).

• M1: Dylan Cormet. "Développement d’un package Julia pour l’épidémiologie saisonnière des

maladies des plantes", Polytech Nice. Supervisors: Ludovic Mailleret and Frédéric Grognard

11.2.3 Juries

• Jean-Luc Gouzé was a member of the jury for the PhD thesis of Clotilde Djuikem (UniCA), for
the HDR of Frédéric Grognard (UniCA), and was a rapporteur for the HDR of D. Bichara (Univ.
Bordeaux). Jean-Luc Gouzé was in the PhD committee of P. Jacquet (Univ. Grenoble) and A. Pavlou
(Univ. Grenoble).

• Madalena Chaves was a rapporteur for the PhD thesis of Ana Bulovic (Institut für Biologie, Humboldt-
Universität zu Berlin, April 17th 2023) and for the PhD thesis of Gian-Karlo Aguirre-Samboní (Uni-
versité Paris-Saclay, December 14th 2023). She was a member of the jury for the PhD thesis of

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Inria Annual Report 2023

Maaike Sansgter (Université Grenoble Alpes, May 11th 2023). Madalena Chaves is in the Comité de
Suivi Doctoral of: Romain Michelucci (UniCA), Adel Anabi (UniCA), Joseph Penlap (UniCA), and
Clémence Métayer (Institut Curie).

• Suzanne Touzeau was a member of the PhD examination committee of Andrea Radici (Avignon

Université, December 11th 2023).

11.3 Popularization

11.3.1 Internal or external Inria responsibilities

• Madalena Chaves is in the local committee for selection of speakers for the monthly Inria Col-

loquium Morgenstern.

11.3.2 Education

• Madalena Chaves was selected to be part of a group of 101 Portuguese Women in Science, high-
lighted to showcase several branches of science and research, and motivate young generations to
follow a scientific education. Photos of each scientist with a short phrase are on exhibition at the
Pavilhão do Conhecimento - Ciência Viva museum in Lisbon and in a booklet.

12 Scientific production

12.1 Major publications

[1] S. Almeida, M. Chaves and F. Delaunay. ‘Control of synchronization ratios in clock/cell cycle
coupling by growth factors and glucocorticoids’. In: Royal Society Open Science 7.2 (2020), p. 192054.
DOI: 10.1098/rsos.192054. URL: https://hal.sorbonne-universite.fr/hal-02505080.

[2] V. Baldazzi, D. Ropers, J.-L. Gouzé, T. Gedeon and H. de Jong. ‘Resource allocation accounts for
the large variability of rate-yield phenotypes across bacterial strains’. In: eLife 12 (31st May 2023),
pp. 1–29. DOI: 10.7554/eLife.79815. URL: https://hal.inrae.fr/hal-04145943.

[3] M. Chaves, L. Gomes-Pereira and J. Roux. ‘Two-level modeling approach to identify the regulatory
dynamics capturing drug response heterogeneity in single-cells’. In: Scientific Reports 11.1 (Dec.
2021). DOI: 10.1038/s41598-021-99943-0. URL: https://inria.hal.science/hal-034392
55.

[4] P. Clin, F. Grognard, D. Andrivon, L. Mailleret and F. M. Hamelin. ‘Host mixtures for plant disease
control: Benefits from pathogen selection and immune priming’. In: Evolutionary Applications
15.6 (23rd May 2022), pp. 967–975. DOI: 10.1111/eva.13386. URL: https://inria.hal.scienc
e/hal-03676499.

[5] S. Nilusmas, M. Mercat, T. Perrot, C. Djian-caporalino, P. Castagnone-Sereno, S. Touzeau, V. Cal-
cagno and L. Mailleret. ‘Multi-seasonal modelling of plant-nematode interactions reveals efficient
plant resistance deployment strategies’. In: Evolutionary Applications 13.9 (2020), pp. 2206–2221.
DOI: 10.1111/eva.12989. URL: https://hal.inrae.fr/hal-02775269.

[6] C. Poignard, M. Chaves and J.-L. Gouzé. ‘A Stability Result for Periodic Solutions of Nonmonotonic
Smooth Negative Feedback Systems’. In: SIAM Journal on Applied Dynamical Systems 17.2 (3rd Apr.
2018), pp. 1091–1116. DOI: 10.1137/17M1141205. URL: https://inria.hal.science/hal-01
872255.

[7] E. Rousseau, M. Bonneault, F. Fabre, B. Moury, L. Mailleret and F. Grognard. ‘Virus epidemics,
plant-controlled population bottlenecks and the durability of plant resistance’. In: Philosophical
Transactions of the Royal Society B: Biological Sciences 374.1775 (24th June 2019), p. 20180263. DOI:
10.1098/rstb.2018.0263. URL: https://inria.hal.science/hal-02149025.

[8]

I. Tankam Chedjou, S. Touzeau, L. Mailleret, J. J. Tewa and F. Grognard. ‘Modelling and control of a
banana soilborne pest in a multi-seasonal framework’. In: Mathematical Biosciences 322 (Apr. 2020),
p. 108324. DOI: 10.1016/j.mbs.2020.108324. URL: https://hal.inrae.fr/hal-02775460.

Project MACBES

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12.2 Publications of the year

International journals

[9] F. Aubree, B. Lac, L. Mailleret and V. Calcagno. ‘Migration pulsedness alters patterns of allele
fixation and local adaptation in a mainland-island model’. In: Evolution - International Journal
of Organic Evolution 77.3 (1st Mar. 2023), pp. 718–730. DOI: 10.1093/evolut/qpac067. URL:
https://hal.inrae.fr/hal-04047090.

[10] N. Augier, M. Chaves and J.-L. Gouzé. ‘Weak synchronization and convergence in coupled genetic
regulatory networks: Applications to damped oscillators and multistable circuits’. In: International
Journal of Robust and Nonlinear Control 33.9 (June 2023), pp. 4867–4892. DOI: 10.1002/rnc.6061.
URL: https://inria.hal.science/hal-03270268.

[11] V. Baldazzi, D. Ropers, J.-L. Gouzé, T. Gedeon and H. de Jong. ‘Resource allocation accounts for
the large variability of rate-yield phenotypes across bacterial strains’. In: eLife 12 (31st May 2023),
pp. 1–29. DOI: 10.7554/eLife.79815. URL: https://hal.inrae.fr/hal-04145943.

[12] P. Bernhard, M. Deschamps and G. Zaccour. ‘Large satellite constellations and space debris: explor-
atory analysis of strategic management of the space commons’. In: European Journal of Operational
Research 304.3 (1st Feb. 2023), pp. 1140–1157. DOI: 10.1016/j.ejor.2022.04.030. URL: https:
//inria.hal.science/hal-03909662.

[13] V. Burte, M. Cointe, G. Perez, L. Mailleret and V. Calcagno. ‘When complex movement yields simple
dispersal: behavioural heterogeneity, spatial spread and parasitism in groups of micro-wasps’. In:
Movement Ecology 11.1 (Dec. 2023), p. 13. DOI: 10.1186/s40462-023-00371-8. URL: https://h
al.inrae.fr/hal-04047110.

[14] P. Clin, F. Grognard, D. Andrivon, L. Mailleret and F. M. Hamelin. ‘The proportion of resistant
hosts in mixtures should be biased towards the resistance with the lowest breaking cost’. In: PLoS
Computational Biology 19.5 (25th May 2023), e1011146. DOI: 10.1371/journal.pcbi.1011146.
URL: https://hal.inrae.fr/hal-04143995.

[15] M. Cointe, V. Burte, G. Perez, L. Mailleret and V. Calcagno. ‘A double-spiral maze and hi-resolution
tracking pipeline to study dispersal by groups of minute insects’. In: Scientific Reports 13.1 (Dec.
2023), p. 5200. DOI: 10.1038/s41598-023-31630-8. URL: https://hal.inrae.fr/hal-04144
010.

[16] C. Djuikem, F. Grognard and S. Touzeau. ‘Impulsive modelling of rust dynamics and predator
releases for biocontrol’. In: Mathematical Biosciences 356 (23rd Jan. 2023), p. 108968. DOI: 10.1016
/j.mbs.2023.108968. URL: https://inria.hal.science/hal-03952381.

[17] Y. Fotso Fotso, S. Touzeau, F. Grognard, B. Tsanou and S. Bowong. ‘Optimal Control of Coffee
Berry Borers: Synergy Between Bio-insecticide and Traps’. In: Journal of Optimization Theory and
Applications 196.3 (2023), pp. 882–899. DOI: 10.1007/s10957-022-02151-7. URL: https://hal
.inrae.fr/hal-03954863.

[18] C. Martinez, E. Cinquemani, H. de Jong and J.-L. Gouzé. ‘Optimal protein production by a synthetic
microbial consortium: Coexistence, distribution of labor, and syntrophy’. In: Journal of Mathemat-
ical Biology 87 (2023), pp. 1–37. DOI: 10.1007/s00285-023-01935-3. URL: https://inria.hal
.science/hal-03525249.

[19] T. Morel-Journel, M. Haond, L. Dunan, L. Mailleret and E. Vercken. ‘Colonisation debt: when
invasion history impacts current range expansion’. In: Peer Community Journal 3 (28th June 2023),
e59. DOI: 10.24072/pcjournal.293. URL: https://hal.science/hal-04236191.

[20] M. Saubin, C. Louet, L. Bousset, F. Fabre, P. Frey, I. Fudal, F. Grognard, F. M. Hamelin, L. Mailleret,
S. Stoeckel, S. Touzeau, B. Petre and F. Halkett. ‘Improving sustainable crop protection using
population genetics concepts’. In: Molecular Ecology 32.10 (May 2023), pp. 2461–2471. DOI: 10.11
11/mec.16634. URL: https://hal.science/hal-03394837.

[21] A. G. Yabo, M. Safey El Din, J.-B. Caillau and J.-L. Gouzé. ‘Stability analysis of a bacterial growth
model through computer algebra’. In: MathematicS In Action 12.1 (26th Sept. 2023), pp. 175–189.
DOI: 10.5802/msia.37. URL: https://hal.science/hal-03671432.

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Inria Annual Report 2023

Invited conferences

[22] V. Baldazzi, D. Ropers, J.-L. Gouzé, T. Gedeon and H. de Jong. ‘Resource allocation strategies behind
rate-yield phenotypes in E.coli’. In: 2023 - Workshop on Advanced School on Quantitative Principles
in Microbial Physiology: from Single Cells to Cell Communities. Trieste, Italy, 31st July 2023, p. 1.
URL: https://hal.inrae.fr/hal-04216644.

[23] M. Chaves. ‘Cycle dynamics and synchronization analysis for biological oscillators’. In: Interna-
tional School and Conference on Network Science. Vienna, Austria, 10th July 2023. URL: https:
//inria.hal.science/hal-04380044.

[24] L. Mailleret. ‘Hands on Pluto : dynamical systems with reactive Julia notebooks’. In: Julia day.

Sophia Antipolis, France, 12th Jan. 2023. URL: https://hal.inrae.fr/hal-04144081.

[25] L. Mailleret. ‘Pulsed perturbations in population dynamics’. In: MOMI2023 - Le MOnde des Math-
ématiques Industrielles. Sophia Antipolis (06), France, 3rd Apr. 2023. URL: https://hal.inrae.f
r/hal-04144067.

International peer-reviewed conferences

[26]

J. C. Arceo, O. Bernard and J.-L. Gouzé. ‘Observer Design via Non-Monotone Lyapunov Functions
for Monitoring Heterotrophic Microalgae’. In: IfacOnLine. 22nd IFAC World Congress. Yokohama,
Japan, 2023. URL: https://inria.hal.science/hal-04229860.

[27] C. Bresch, L. van Oudenhove, J. Nardini, L. Browet, L. Ottenwaelder and L. Mailleret. ‘Ringed
micro-habitats as supplementations for predatory mites’. In: IOBC-WPRS WGs 2023 - Integrated
control in protected crops, temperate and mediterranean climate. Brest, France, 27th Aug. 2023.
URL: https://hal.inrae.fr/hal-04166972.

[28] O. Burckard, M. Chaves, F. Delaunay and M. Teboul. ‘Couplage et synchronisation d’horloges
circadiennes périphériques’. In: Médecine du Sommeil. 48ème congrès de la Société Francophone
de Chronobiologie. Vol. 20. 4. Paris, France, Dec. 2023, p. 249. DOI: 10.1016/j.msom.2023.10.02
1. URL: https://hal.science/hal-04391603.

Conferences without proceedings

[29] M. Courtois, K. Rastello, F. Grognard, L. Mailleret, S. Touzeau and L. van Oudenhove. ‘How does
residual fertility impact the effectiveness of the sterile insect technique in controlling Ceratitis
capitata?’ In: MPDEE 2023 - Mathematical Population Dynamics, Ecology and Evolution. Marseille,
France, Apr. 2023. URL: https://hal.inrae.fr/hal-04144121.

[30] C. Djuikem, F. Grognard and S. Touzeau. ‘Impulsive modelling of rust dynamics and predator
releases’. In: CMPD6 - Computational and Mathematical Population Dynamics. Winnipeg, Canada,
23rd May 2023. URL: https://hal.inrae.fr/hal-04140599.

[31] A. Kambeu Youmbi, S. Touzeau, F. Grognard and B. Tsanou. ‘Self-financing model for cabbage crops’.
In: MPDEE 2023 - Conference on Mathematical Population Dynamics, Ecology and Evolution.
Marseille, France, 24th Apr. 2023. URL: https://hal.inrae.fr/hal-04140598.

[32] C. Kounoudji, S. Touzeau, F. Grognard, L. van Oudenhove and L. Mailleret. ‘A sex- and stage-
structured population dynamics model for pest control using the sterile insect technique’. In:
MPDEE 2023 - Mathematical Population Dynamics, Ecology and Evolution. Marseille, France,
24th Apr. 2023. URL: https://hal.inrae.fr/hal-04144139.

[33]

[34]

J. J. Penlap Tamagoua, S. Touzeau, F. Grognard and V. Baldazzi. ‘Modelling plant - nematode inter-
actions to understand plant tolerance’. In: MPDEE 2023 - Conference on Mathematical Population
Dynamics, Ecology and Evolution. Marseille, France, 24th Apr. 2023. URL: https://hal.inrae.f
r/hal-04223383.

J. J. Penlap Tamagoua, S. Touzeau, F. Grognard and V. Baldazzi. ‘Modelling plant-nematodes inter-
actions to understand plant tolerance’. In: IMACS 2023 - 21st World Congress of the International
Association for Mathematics and Computers in Simulation. Rome, Italy, 11th Sept. 2023. URL:
https://hal.inrae.fr/hal-04216608.

Project MACBES

23

Doctoral dissertations and habilitation theses

[35] C. Djuikem. ‘Mathematical modelling and control of perennial plant phytopathogens’. Université

Côte d’Azur, 5th Jan. 2023. URL: https://theses.hal.science/tel-04026720.

[36] F. Grognard. ‘Modelling and control of managed ecosystems, from bioreactors to agroecosystems’.

Université Côte D’Azur, 20th Feb. 2023. URL: https://inria.hal.science/tel-04176866.

[37] M. Péré. ‘Modeling cancer drug response dynamics in single-cells to predict the emergence of
drug-tolerant cells’. Université Côte d’Azur, 27th Mar. 2023. URL: https://inria.hal.science
/tel-04350085.

Reports & preprints

[38] O. Burckard and M. Chaves. Analytic solutions for the circadian oscillator characterize cycle dynamics
and its robustness. 21st Dec. 2023. DOI: 10.21203/rs.3.rs-3772537/v1. URL: https://hal.sc
ience/hal-04391710.

[39] M. Cointe, V. Burte, G. Perez, L. Mailleret and V. Calcagno. A double-spiral maze and hi-resolution
tracking pipeline to study dispersal by groups of minute insects. 2023. DOI: 10.1101/2022.09.06
.506709. URL: https://hal.science/hal-04050823.

[40]

J. Cresson, M. Péré and A. Szafranska. Numerical approach to the identification of fractional differ-
ential equations and applications in epidemics. 11th Apr. 2023. URL: https://hal.science/hal-
04065555.

[41] M. Deschamps and P. Bernhard. Cournot oligopoly: a discrete time sticky-prices paradox. 5th Jan.

2024. URL: https://univ-fcomte.hal.science/hal-04390731.

[42] Y. Fotso Fotso, S. Touzeau, B. Tsanou, F. Grognard and S. Bowong. Optimal impulsive control of
coffee berry borers in a berry age-structured epidemiological model. 2023. URL: https://hal.scie
nce/hal-04100767.

[43] H. Kanso, M.-M. Memah, V. Baldazzi, B. Quilot-Turion and C. Baey. Assessing Inter-Individual
Genetic Variability in Peach Sugar Metabolism through Reliable Parameter Estimation of a Kinetic
Model. 13th Aug. 2023. DOI: 10.1101/2023.08.10.552764. URL: https://hal.science/hal-0
4215456.

[44] T. Morel-Journel, M. Haond, L. Dunan, L. Mailleret and E. Vercken. Colonisation debt: when invasion
history impacts current range expansion. 15th Nov. 2022. DOI: 10.1101/2022.11.13.516255. URL:
https://hal.inrae.fr/hal-04144037.

[45] A. G. Yabo, J.-B. Caillau and J.-L. Gouzé. Optimal bacterial resource allocation strategies in batch

processing. 25th Sept. 2023. URL: https://inria.hal.science/hal-03710681.

Other scientific publications

[46] O. Burckard and M. Chaves. ‘Benchmark for quantitative characterization of circadian clock models’.
In: 21st International Conference on Computational Methods in Systems Biology. Vol. LNCS.LNBI-
14137. Computational Methods in Systems Biology 21st International Conference, CMSB 2023,
Luxembourg City, Luxembourg, September 13–15, 2023, Proceedings. Luxembourg City, Luxem-
bourg, 13th Sept. 2023. URL: https://inria.hal.science/hal-04379973.

[47] M. Courtois, K. Rastello, F. Grognard, L. Mailleret, S. Touzeau and L. van Oudenhove. ‘Sterile Insect
Technique for crop protection: accounting for residual fertility’. In: Le MOnde des Mathématiques
Industrielles, MOMI2023. Sophia Antipolis, France, 3rd Apr. 2023. URL: https://hal.inrae.fr
/hal-04144059.

[48] M. Courtois, K. Rastello, F. Grognard, L. Mailleret, S. Touzeau and L. van Oudenhove. ‘Sterile insect
technique for crop protection: accounting for residual fertility’. In: DSABNS 2023 - 14th Conference
on Dynamical Systems Applied to Biology and Natural Sciences. Bilbao, Spain, Spain, 5th Feb. 2023.
URL: https://hal.inrae.fr/hal-04049975.

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Inria Annual Report 2023

J. J. Penlap Tamagoua, S. Touzeau, F. Grognard and V. Baldazzi. ‘Ecophysiological modelling of
plant-nematode interactions to understand plant tolerance’. In: DSABNS 2023 Conference - 14th
International Conference on Dynamical Systems Applied to Biology and Natural Sciences. Bilbao,
Spain, 2023. URL: https://hal.inrae.fr/hal-04146030.

12.3 Other

Scientific popularization

[50] F. Aubree, B. Lac, L. Mailleret and V. Calcagno. ‘Life is not a long quiet river: consequences of
migration pulsedness for adaptation and divergence’. In: Complex Days. Complex Days 2023.
Complex Days 3. Nice, France, 7th Feb. 2023. URL: https://hal.science/hal-04043134.

[51] M. Cointe, V. Burte, G. Perez, L. Mailleret and V. Calcagno. ‘Bridging behavior and spatial propaga-
tion: a new double spiral maze and image analysis pipeline to study dispersal in groups of minute
insects’. In: Complex Days. UCA Complex Days 2023. Complex Days 3. Nice, France, 7th Feb. 2023.
URL: https://hal.science/hal-04030917.

12.4 Cited publications

[52] Y. Fotso Fotso. ‘Modelling, analysis and control of coffee berry borer’. Université de Dschang
(Cameroun), 17th Jan. 2022. URL: https://hal.archives-ouvertes.fr/tel-03608463.

[53] O. Burckard, M. Teboul, F. Delaunay and M. Chaves. ‘Cycle dynamics and synchronization in a
coupled network of peripheral circadian clocks’. In: Interface Focus 12.3 (June 2022), p. 20210087.
DOI: 10.1098/rsfs.2021.0087. URL: https://inria.hal.science/hal-03685352.

[54] M. Cointe. ‘Du laboratoire au terrain, du mouvement à la dispersion : étude de la propagation
des parasitoïdes du genre Trichogramma à différentes échelles spatiales et temporelles’. Theses.
Université Côte d’Azur, Oct. 2023. URL: https://theses.hal.science/tel-04390275.

[55] M. Haond. ‘Impact de la capacité de charge de l’environnementsur les dynamiques d’expansions
de métapopulations. Théories et applications à un système expérimental hôte-parasitoïde’. PhD
thesis. Université Côte d’Azur, 2019.

[56] L. Mailleret and V. Lemesle. ‘A note on semi-discrete modelling in the life sciences’. In: Philosophical
Transactions of the Royal Society A: Mathematical,Physical and Engineering Sciences 367.1908 (2009),
pp. 4779–4799. DOI: 10.1098/rsta.2009.0153. eprint: http://rsta.royalsocietypublishi
ng.org/content/367/1908/4779.full.pdf+html. URL: http://rsta.royalsocietypubli
shing.org/content/367/1908/4779.abstract.

[57] M. Mauri, J.-L. Gouzé, H. De Jong and E. Cinquemani. ‘Enhanced production of heterologous
proteins by a synthetic microbial community: Conditions and trade-offs’. In: PLoS Computational
Biology 16.4 (2020), e1007795. DOI: 10.1371/journal.pcbi.1007795. URL: https://hal.sorb
onne-universite.fr/hal-02640446.

[58] M. Meyer, A. Paquet, M.-J. Arguel, L. Peyre, L. Gomes-Pereira, K. Lebrigand, B. Mograbi, P. Brest,
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<scratchpad>
- Main topic: Research Centre MACBES (Inria Centre at Université Côte d’Azur)
- Key points:
  - Focus on modeling and control of biological and ecological systems
  - Four research axes: Network interactions for cell function and growth, Dynamics and control for synthetic biology, Modeling agro-ecological interactions, Design and control of managed ecosystems
  - Application domains: Digital Health, Biology and Earth, with a focus on sustainable agroecosystems and crop protection
  - Social and environmental responsibility: Reduction of chemical pesticide usage, impact on human and environmental health
- Structure: Document is organized into sections, including Activity Report, Project-Team, Research Program, Application Domains, Social and Environmental Responsibility, Highlights of the Year, New Software, New Results, Bilateral Contracts and Grants, Partnerships and Cooperations, Dissemination, Scientific Production, and more
- Potential artifacts to ignore: Links, HTML tags, unnecessary web-related elements
</scratchpad>

<final_summary>
The MACBES research centre, located at Université Côte d’Azur, focuses on modeling and control of biological and ecological systems. The centre has four research axes: Network interactions for cell function and growth, Dynamics and control for synthetic biology, Modeling agro-ecological interactions, and Design and control of managed ecosystems. These axes aim to improve our understanding of complex biological systems and develop sustainable solutions for agroecosystems and crop protection. The centre's work has significant social and environmental implications, with a focus on reducing chemical pesticide usage and promoting sustainable agriculture practices.
The MACBES research centre, located at Université Côte d’Azur, focuses on modeling and control of biological and ecological systems. The centre has four research axes: Network interactions for cell function and growth, Dynamics and control for synthetic biology, Modeling agro-ecological interactions, and Design and control of managed ecosystems. These axes aim to improve our understanding of complex biological systems and develop sustainable solutions for agroecosystems and crop protection. The centre's work has significant social and environmental implications, with a focus on reducing chemical pesticide usage and promoting sustainable agriculture practices.