The availability of large amounts of quantitative data, coupled to the rise of computational biology methods, now makes possible the study of biological processes at a system level.
Our group tries to understand how cellular and molecular systems interpret signals from their environment and adapt their behaviour as a consequence. By building detailed and quantitative computational models, we try to understand how receptor movements, clustering and activity influence signalling. Downstream from the transduction machinery, we build integrated signalling pathways known to mediate the effects of neurotransmitters, neuromodulators and drugs of abuse. We have been in the past particularly focused on signal transduction in neurons, ranging from the molecular structure of proteins involved in neurotransmission to signalling pathways and electrophysiology. We are now extending our activity to other systems such as stemcells.
The group also participates to the development of community services that facilitate research in computational systems biology. This includes efforts towards encoding, annotating and sharing mathematical models in molecular and cellular biology, such as creation of standard representations (SBML,SED-ML, SBGN), controlled vocabularies (SBO, KiSAO, TEDDY, MAMO, Identifiers.org) production of databases (BioModels Database, MIRIAM Registry) and development of software to support the use of standards.
Website: http://lenoverelab.orgMembers involved in CoLoMoTo activities:
- Nicolas Le Novère
- Nicolas Rodriguez