Aurélien Naldi

Aurelien's homepage

profile picture I am a postdoctoral researcher in bioinformatics in the Computational Systems Biology group of the biology department at ENS (Paris, France).

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.

Methodological work

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
A. Naldi, D. Thieffry, C. Chaouiya (2007).
Computational Methods in Systems Biology :233--247 [ doi:10.1007/978-3-540-75140-3_16 ]

Dynamically consistent reduction of logical regulatory graphs
A. Naldi, E. Remy, D. Thieffry, C. Chaouiya (2011).
Theoretical Computer Science 412:2207--2218 [ doi:10.1016/j.tcs.2010.10.021 ]

Dynamical modeling and analysis of large cellular regulatory networks
D. Bérenguier, C. Chaouiya, P. Monteiro, A. Naldi, E. Remy, D. Thieffry, L. Tichit (2013).
Chaos 23:025114 [ doi:10.1063/1.4809783 ]

Software tools

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.

I am also involved in the CoLoMoTo effort to improve the exchange of discrete models. This effort led to the qual extension for SBML and the bioLQM toolbox.

Logical modelling and analysis of cellular regulatory networks with GINsim 3.0
A. Naldi, C. Hernandez, W. Abou-Jaoudé, P. Monteiro, C. Chaouiya, D. Thieffry (2018).
Frontiers in Physiology 9:646 [ doi:10.3389/fphys.2018.00646 ]

SBML qualitative models: a model representation format and infrastructure to foster interactions between qualitative modelling formalisms and tools
C. Chaouiya, D. Bérenguier, S. Keating, A. Naldi, M. van Iersel, N. Rodriguez, A. Dräger, F. Büchel, T. Cokelaer, B. Kowal, B. Wicks, E. Gonçalves, J. Dorier, M. Page, P. Monteiro, A. Kamp, I. Xenarios, H. de Jong, M. Hucka, S. Klamt, D. Thieffry, N. Novère, J. Saez-Rodriguez, T. Helikar (2013).
BMC Systems Biology 7:135 [ doi:10.1186/1752-0509-7-135 ]

BioLQM: a java toolkit for the manipulation and conversion of Logical Qualitative Models of biological networks
A. Naldi (2018).
Frontiers in Physiology 9:1605 [ doi:10.3389/fphys.2018.01605 ]

The CoLoMoTo Interactive Notebook: Accessible and Reproducible Computational Analyses for Qualitative Biological Networks
A. Naldi, C. Hernandez, N. Levy, G. Stoll, P. Monteiro, C. Chaouiya, T. Helikar, A. Zinovyev, L. Calzone, S. Cohen-Boulakia, D. Thieffry, L. Paulevé (2018).
Frontiers in Physiology 9:680 [ doi:10.3389/fphys.2018.00680 ]

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
A. Faure, A. Naldi, C. Chaouiya, D. Thieffry (2006).
Bioinformatics 22:e124--e131 [ doi:10.1093/bioinformatics/btl210 ]

Diversity and Plasticity of Th Cell Types Predicted from Regulatory Network Modelling
A. Naldi, J. Carneiro, C. Chaouiya, D. Thieffry (2010).
PLoS Computational Biology 6:e1000912 [ doi:10.1371/journal.pcbi.1000912 ]

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
F. Gilardi, E. Migliavacca, A. Naldi, M. Baruchet, D. Canella, G. Martelot, N. Guex, B. Desvergne (2014).
PLoS Genetics 10:e1004155 [ doi:10.1371/journal.pgen.1004155 ]

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
L. Wigger, C. Casals-Casas, M. Baruchet, K. Trang, S. Pradervand, A. Naldi, B. Desvergne (2019).
PLOS ONE 14:e0220894 [ doi:10.1371/journal.pone.0220894 pmid ]