Contact: aurelien.naldi [AT] ens.fr
I work on deciphering the mechanisms underlying complex biological systems through formal analysis of qualitative dynamical models. These models are based on mechanistic details identified experimentaly. By confronting model predictions with known phenotypes, we aim to highlight missing or inconsistent knowledge, as well as to guide experimental design. as summarized below, this work combines methodological developments, software implementation, and applications to biological systems.
My main methodological contributions rely on the use of Multivalued Decision Diagrams (MDDs) to represent logical functions. By using MDDs, we could design an efficient method to find all possible stable states of a model, as well as to extract some information on the most important feedback circuits in a model. Later on, we proposed a reduction method, allowing to remove some components while preserving important dynamical properties. I was also involved in the definition of Hierarchical Transition Graphs, a novel compact representation of the dynamics, inspired by the graph of Strongly Connected Components.
Decision Diagrams for the Representation and Analysis of Logical Models of Genetic Networks
Computational Methods in Systems Biology :233--247
Dynamically consistent reduction of logical regulatory graphs
Theoretical Computer Science 412:2207--2218
Dynamical modeling and analysis of large cellular regulatory networks
Since 2006, I am the main developer of the GINsim software for the definition and analysis of logical models. This tool provides a graphical interface for model design and a number of analytical tools, including my formal works on logical models. It also provides import/export bridges to other software tools. GINsim has been used to study dozens of models, either through collaborations or by independent researchers.
Logical modelling and analysis of cellular regulatory networks with GINsim 3.0
Frontiers in Physiology 9:646
SBML qualitative models: a model representation format and infrastructure to foster interactions between qualitative modelling formalisms and tools
BMC Systems Biology 7:135
BioLQM: a java toolkit for the manipulation and conversion of Logical Qualitative Models of biological networks
Frontiers in Physiology 9:1605
The CoLoMoTo Interactive Notebook: Accessible and Reproducible Computational Analyses for Qualitative Biological Networks
Frontiers in Physiology 9:680
Logical models of biological systems
Qualitative models have been applied to a wide range of biological networks, I have been personnaly involved mainly in the study of cell cycle, and differentiation of T helper cells.
Dynamical analysis of a generic Boolean model for the control of the mammalian cell cycle
Diversity and Plasticity of Th Cell Types Predicted from Regulatory Network Modelling
PLoS Computational Biology 6:e1000912
Genomics and metabolism
During my postdoctoral work in Lausanne (Switzerland), I was involved in the study of genomics data (microarray and ChIP-seq) in the context of metabolic processes.
Genome-Wide Analysis of SREBP1 Activity around the Clock Reveals Its Combined Dependency on Nutrient and Circadian Signals
PLoS Genetics 10:e1004155
System analysis of cross-talk between nuclear receptors reveals an opposite regulation of the cell cycle by LXR and FXR in human HepaRG liver cells
PLOS ONE 14:e0220894