Life Sciences Research for Lifelong Health

Research

Our group uses bioinformatic methods and mathematical modelling to study the basic processes of life. The methods we use range from analysis of transcriptomes and epigenomes to temporal and spatial models.

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 on cell physiology, including gene expression and cell fate.

​Our activity currently unfolds along four parallel though cross-fertilizing themes.

Molecular basis of neuronal signalling

The group is a partner in several collaborations aiming at understanding synaptic transmission at a systems level. We develop models of transduction pathways at different levels of granularities to understand synaptic plasticity in normal and pathological conditions (in particular Alzheimer's Disease).

Cross-talk between MAPK, calcium and phosphoinositide signalling.

We believe intracellular signalling is largely made of "vertical" kinase cascades cross-linked by horizontal phosphatase modulations. Accordingly, we are trying to understand how the connections between these different pathways affect cell behaviour.

Large scale model development.

The availability of vast curated pathway databases and omics datasets make it possible to generate mathematical models of large cellular systems. The group collaborates in efforts enabling data and model integration and reconstructing cell-wide models. We also integrate models of signalling pathways, metabolism, gene regulatory networks and the epigenetic machinery to understand cell physiology.

Ageing and stem cells

By using mathematical models, we try to understand the regulation of stem cell pluripotency, reprogramming and differentiation. Quantitative modelling the fine control of these processes will be an important tool for future bioengineering and regenerative medicine.
In addition to hypothesis driven research, we participate in the development of community services that facilitate research in computational systems biology. This includes efforts in encoding and annotating kinetic models in chemistry and cellular biology, such as creation of standard representations (e.g. SBML, SED-ML, SBGN), production of databases (e.g. BioModels Database) and software development (e.g. JSBML).

​More information can be found on the lenoverelab.org laboratory website