Life Sciences Research for Lifelong Health

Nicolas Le Novère

Research Summary

Our group uses bioinformatic methods and mathematical modelling to study the basic processes of life. Biological research now relies on the generation and analyses of large amounts of quantitative data, coming for example from nucleic acid sequencing and mass spectrometry.

Such data need to be processed, quantified and put in context. This is done using software tools and statistics. Based on the information acquired from experiments and existing literature one can build mathematical models that can then be simulated under various conditions.

The success or failure of reproducing observed behaviours tell us if we adequately understand the mechanisms of life. This activity is an important part of what is now called "systems biology". The systems biology paradigm recognises that the behaviour of any living system emerges from the interactions between many of its components and cannot be fully understood by studying those components in isolation.

The main biological focus of the group is to understand how cellular and molecular systems interpret signals from their environment and adapt their behaviour as a consequence. This entails understanding how the various cells receive and transduce the signal, the interplay of different signalling pathways, and the final outcome for cell physiology, including gene expression and cell fate.

​Our main biological models are the synaptic signalling between neurons of the central nervous system, and the maintenance and differentiation of stem cells.

Latest Publications

The health care and life sciences community profile for dataset descriptions.

Dumontier M, Gray AJ, Marshall MS

PeerJ
4 2167-8359:e2331 (2016)

PMID: 27602295

The systems biology format converter.

Rodriguez N, Pettit JB, Dalle Pezze P

BMC bioinformatics
17 1471-2105:154 (2016)

PMID: 27044654

Mathematical Models of Pluripotent Stem Cells: At the Dawn of Predictive Regenerative Medicine.

Pir P, Le Novère N

Methods in molecular biology (Clifton, N.J.)
1386 1940-6029:331-50 (2016)

PMID: 26677190

Enabling surface dependent diffusion in spatial simulations using Smoldyn.

Seeliger C, Le Novère N

BMC research notes
8 1756-0500:752 (2015)

PMID: 26647064

SBOL Visual: A Graphical Language for Genetic Designs.

Quinn JY, Cox RS, Adler A

PLoS biology
13 1545-7885:e1002310 (2015)

PMID: 26633141

Do genome-scale models need exact solvers or clearer standards?

Ebrahim A, Almaas E, Bauer E

Molecular systems biology
11 1744-4292:831 (2015)

PMID: 26467284

JSBML 1.0: providing a smorgasbord of options to encode systems biology models.

Rodriguez N, Thomas A, Watanabe L

Bioinformatics (Oxford, England)
1367-4811: (2015)

PMID: 26079347

Promoting Coordinated Development of Community-Based Information Standards for Modeling in Biology: The COMBINE Initiative.

Hucka M, Nickerson DP, Bader GD

Frontiers in bioengineering and biotechnology
3 2296-4185:19 (2015)

PMID: 25759811

Quantitative and logic modelling of molecular and gene networks.

Le Novère N

Nature reviews. Genetics
16 1471-0064:146-58 (2015)

PMID: 25645874

SPARQL-enabled identifier conversion with Identifiers.org.

Wimalaratne SM, Bolleman J, Juty N

Bioinformatics (Oxford, England)
1367-4811: (2015)

PMID: 25638809

Ligand-dependent opening of the multiple AMPA receptor conductance States: a concerted model.

Dutta-Roy R, Rosenmund C, Edelstein SJ

PloS one
10 1932-6203:e0116616 (2015)

PMID: 25629405

Modulation of calmodulin lobes by different targets: an allosteric model with hemiconcerted conformational transitions.

Lai M, Brun D, Edelstein SJ

PLoS computational biology
11 1553-7358:e1004063 (2015)

PMID: 25611683