omics data integration

Mitochondrial computational biology is a major focus of our lab. We are interested in understanding mitochondrial heterogeneity and the dynamic changes of mitochondria in different tissues or in different disease states. We have compiled so far the most complete mitochondrial interactomes for 4 major model organisms. We develop tools such as the mitoXplorer web-server for deep mining and visual data mining of mitochondria-associated gene expression dynamics, using in-house and public RNA-seq or proteomics data ... more

mitoXplorer (v2) is available at: http://mitoxplorer2.ibdm.univ-mrs.fr/

Biological networks are a popular means to interpret omics data coming from RNA-seq or proteomic experiments. Other than pure gene lists or enrichments, they can tell us something about pathways or connected gene groups (subnetworks) acting together during a cellular response. We are interested in including time as a component in these networks ... more

With NGS, sequencing also became functional. We can now describe also the non-coding part of a genome, for instance by looking at histone marks, transcription factor binding events, or chromatin states. These new techniques also require new tools for annotating and integrating data from such epigenetic studies. With the web-tool AnnoMiner, we introduce an annotation and integration tools for epigenetic data that offers the user flexibility and choice in determining the association of a genomic peak and a genomic feature ... more

AnnoMiner is available at http://chimborazo.ibdm.univ-mrs.fr/AnnoMiner