Ingénieur de recherche
Tel: 04 72 44 83 08
Chargé de recherche
Tel: 04 72 44 85 98
Maître de conférences
Tel: 33 04 72 43 15 52
Maître de conférences
Tel: 04 72 43 15 52
Professeur des universités
Tel: 04 26 23 44 60
Directrice de recherche
Tel: 33 04 72 44 82 38
Baobab is a French research team of the Laboratoire de Biométrie et Biologie Évolutive, and at the same time represents the core of a European research team of Inria called Erable. Besides the members of Baobab, Erable has thus members in three institutions in Italy (Sapienza University of Rome, Luiss University, and University of Pisa) and two institutions in the Netherlands (CWI and Free University of Amsterdam).
Baobab has two main sets of research goals that currently cover four axes:
The first is related to the original areas of expertise of the team, namely combinatorial and statistical modelling and algorithms, although more recently the team has also been joined by members that come from biology including experimental.
The second set of goals concern its main Life Science interest which is to better understand interactions between living systems and their environment. This includes close and often persistent interactions between two living systems (symbiosis), interactions between living systems and viruses, and interactions between living systems and chemical compounds.
(pan)genomics and transcriptomics in general,
metabolism and (post)transcriptional regulation,
health in general, of living systems and environmental.
A longer objective of the team is to become able in some cases to suggest the means of controlling for or of re-establishing equilibrium in an interacting community by acting on its environment or on its players, how they play and who plays.
Two major steps are constantly involved in the research done by the team: a first one of modelling (i.e. translating) a Life Science problem into a mathematical one, and a second of algorithm analysis and design. The algorithms developed are then applied to the questions of interest in Life Science using data from the literature or from collaborators. More recently, thanks to the recruitment of young researchers (PhD students and postdocs) in biology, the team has become able to start doing experiments and producing data or validating some of the results obtained on its own.
From a methodological point of view, the main characteristic of the team is to consider that, once a model is selected, the algorithms to explore such model should, whenever possible, be exact in the answer provided as well as exhaustive when more than one exists for a more accurate interpretation of the results. More recently, the team has become interested in exploring the interface between exact algorithms on one hand, and probabilistic or statistical ones on the other such as used in machine learning approaches. More in particular, the team is interested in investigating an area of research called “interpretable machine learning” that has been developing more recently and its potential relations with exact, combinatorial approaches.
Besides being at the core of a European team, Baobab has a number of other collaborations at the international level.
Baobab is also strongly involved in teaching at the University of Lyon and Insa-Lyon, well as in other research institutions in Europe, directly or through the members of Erable that are not in France.
For more information, you may also visit the site of the Inria team Erable here: http://team.inria.fr/erable/en/.
Display of 1 to 30 publications on 320 in total
Hybrid modelling to Solve Optimal Concentrations of Metabolites and Enzymes in Constraint-based modelling
BIOSTEC 2023 .
Mutations in the non-coding RNU4ATAC gene affect the homeostasis and function of the Integrator complex
Nucleic Acids Research .
Geometric programming to Solve Optimal Concentrations of Metabolites and Enzymes in Constraint-based modelling
International Conference on System Biology .
Special Issue on “Frontiers in Connecting Steady-State and Dynamic Approaches for Modelling Cell Metabolic Behavior”
Processes . 10 ( 8 ) : 1612
Hybrid metabolic modeling to identify new control strategies of living organisms
Hybrid models and methods in systems medicine .
Mod ́elisation m ́etabolique pour identifier de nouvelles strat ́egies de contrˆole des organismes vivants
Neural Networks beyond explainability: Selective inference for sequence motifs
Mycobacterium tuberculosis genetic features associated with pulmonary tuberculosis severity
International Journal of Infectious Diseases . 125 : 74-83
BrumiR: A toolkit for de novo discovery of microRNAs from sRNA-seq data
GigaScience . 11
Phyloformer: towards fast and accurate phylogeny estimation with self-attention networks
Efficiently sparse listing of classes of optimal cophylogeny reconciliations
Algorithms for Molecular Biology . 17 ( 1 ) : 1-16
Totoro: Identifying Active Reactions During the Transient State for Metabolic Perturbations
Frontiers in Genetics . 13 : 1-12
CALDERA: Finding all significant de Bruijn subgraphs for bacterial GWAS
Answer set programming to compute constraint elementary flux modes
Computational Methods in System Biology .
Answer set programming to compute constraint elementary flux modes.
Metabolic Pathway Analysis .
Fine-tuning mitochondrial activity in Yarrowia lipolytica for citrate overproduction
Scientific Reports . 11 ( 1 )
Combining Kinetic and Constraint-Based Modelling to Better Understand Metabolism Dynamics
Processes . 9 ( 10 ) : 1701
Within-host genetic micro-diversity of Mycobacterium tuberculosis and the link with tuberculosis disease features
A General Framework for Enumerating Equivalence Classes of Solutions
ESA 2021 - 29th Annual European Symposium on Algorithms . : 1-14
Dichloroacetate and Pyruvate Metabolism: Pyruvate Dehydrogenase Kinases as Targets Worth Investigating for Effective Therapy of Toxoplasmosis
MSphere . 6 ( 1 )
A family of tree-based generators for bubbles in directed graphs
Journal of Graph Algorithms and Applications . 25 ( 1 ) : 549-562
A comprehensive evaluation of binning methods to recover human gut microbial species from a non-redundant reference gene catalog
NAR Genomics and Bioinformatics . 3 ( 1 )
Making Sense of a Cophylogeny Output: Efficient Listing of Representative Reconciliations
WABI 2021 - 21st International Workshop on Algorithms in Bioinformatics . : 1-18
Cancer and Alzheimer’s disease: intracellular pH scales the metabolic disorders
Biogerontology . 21 ( 6 ) : 683-694
Thermodynamic Approaches in Flux Analysis
Metabolic Flux Analysis in Eukaryotic Cells . : 359-367
Book chaptersee the publication
Controlling technical variation amongst 6693 patient microarrays of the randomized MINDACT trial
Communications Biology . 3
Efficient hybrid de novo assembly of human genomes with WENGAN
Nature Biotechnology . 39 : 422–430
MOMO - multi-objective metabolic mixed integer optimization: application to yeast strain engineering
BMC Bioinformatics . 21 ( 1 ) : 1-13
A Family of Tree-Based Generators for Bubbles in Directed Graphs
IWOCA 2020 - 31st International Workshop on Combinatorial Algorithms . 12126 : 17-29
MOOMIN – Mathematical explOration of ’Omics data on a MetabolIc Network
Bioinformatics . 36 ( 2 ) : 514-523