September 27, 2018

BRANE power: Gene network inference with graph optimization

Aurélie Pirayre's bioinformatics PhD manuscript and slides for her thesis:
are finally online. The work was ruled by BRANE power; a methodology for gene regulatory networks inference and clustering based on graph optimization and biological priors. BRANE stands for Biologically Related Apriori Network Enhancement. It rhymes with cell membrane (and brain, for who it's worth).

Gene regulatory network inference with BRANE Cut

State-of-the-art results are obtained on synthetic and real transcriptomic data (DREAM-4, DREAM-5 challenges, Escherichia coli dataset). Derived methods are BRANE Cut (with graph cuts), BRANE Relax (with proximal optimization) and BRANE Clust (with graph Laplacian). 

Gene network joint inference and clustering with BRANE Clust

Used concepts include:
  • data science, optimization on graphs: maximal flow, minimum cut, random walker algorithm, variational and Bayes variational formalism, convex relaxation, alternating optimization, combinatorial Dirichlet problem, hard-clustering and soft-clustering
  • biology, biotechnology, bioinformatics: transcription factors (TFs) as regulators and non-transcription factors (TFs) as targets, modular networks, biological priors, in-silico data, second generation bio-fuel production, DREAM4 challenge, DREAM5 challenge
Supervising team:
PhD Thesis Reporters

PhD Thesis Examiners

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