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

SBpipe: a collection of pipelines for automating repetitive simulation and analysis tasks.
Dalle Pezze P, Le Novère N

The rapid growth of the number of mathematical models in Systems Biology fostered the development of many tools to simulate and analyse them. The reliability and precision of these tasks often depend on multiple repetitions and they can be optimised if executed as pipelines. In addition, new formal analyses can be performed on these repeat sequences, revealing important insights about the accuracy of model predictions.

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BMC systems biology, 11, 1752-0509, 46, 2017

PMID: 28395655

Specifications of Standards in Systems and Synthetic Biology: Status and Developments in 2016.
Schreiber F, Bader GD, Gleeson P, Golebiewski M, Hucka M, Le Novère N, Myers C, Nickerson D, Sommer B, Walthemath D

Standards are essential to the advancement of science and technology. In systems and synthetic biology, numerous standards and associated tools have been developed over the last 16 years. This special issue of the Journal of Integrative Bioinformatics aims to support the exchange, distribution and archiving of these standards, as well as to provide centralised and easily citable access to them.

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Journal of integrative bioinformatics, 13, 1613-4516, 289, 2016

PMID: 28187405

The health care and life sciences community profile for dataset descriptions.
Dumontier M, Gray AJ, Marshall MS, Alexiev V, Ansell P, Bader G, Baran J, Bolleman JT, Callahan A, Cruz-Toledo J, Gaudet P, Gombocz EA, Gonzalez-Beltran AN, Groth P, Haendel M, Ito M, Jupp S, Juty N, Katayama T, Kobayashi N, Krishnaswami K, Laibe C, Le Novère N, Lin S, Malone J, Miller M, Mungall CJ, Rietveld L, Wimalaratne SM, Yamaguchi A

Access to consistent, high-quality metadata is critical to finding, understanding, and reusing scientific data. However, while there are many relevant vocabularies for the annotation of a dataset, none sufficiently captures all the necessary metadata. This prevents uniform indexing and querying of dataset repositories. Towards providing a practical guide for producing a high quality description of biomedical datasets, the W3C Semantic Web for Health Care and the Life Sciences Interest Group (HCLSIG) identified Resource Description Framework (RDF) vocabularies that could be used to specify common metadata elements and their value sets. The resulting guideline covers elements of description, identification, attribution, versioning, provenance, and content summarization. This guideline reuses existing vocabularies, and is intended to meet key functional requirements including indexing, discovery, exchange, query, and retrieval of datasets, thereby enabling the publication of FAIR data. The resulting metadata profile is generic and could be used by other domains with an interest in providing machine readable descriptions of versioned datasets.

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PeerJ, 4, 2167-8359, e2331, 2016

PMID: 27602295

01223 496433

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Keywords

computational biology
mathematical modelling
neurobiology
systems biology

Latest Publications

SBpipe: a collection of pipelines for automating repetitive simulation and analysis tasks.

Dalle Pezze P, Le Novère N

BMC systems biology
11 1752-0509:46 (2017)

PMID: 28395655

Specifications of Standards in Systems and Synthetic Biology: Status and Developments in 2016.

Schreiber F, Bader GD, Gleeson P

Journal of integrative bioinformatics
13 1613-4516:289 (2016)

PMID: 28187405

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