In a word, optimization methodologies with biologically-related a-priori for genomic/transcriptomic data. Globally, we call that BRANE power:) 

We are developing a series of bioinformatics tools based on graphs and optimization, dedicated to -omics gene expression data (from RNA-seq or microarrays). They are meant for Gene Regulatory Network (GRN) inference. Genomic data is complicated. Especially, gene-condition and transcription factor-target gene ratios are not favorable. Data counts are even biased, noisy and variable.

There exists therefore a large number of solutions. One needs to introduce a priori (co-regulation,  co-expression, clustering, modularity, sparsity) to improve the graph structure, for instance around modules, or using gene clustering. We use biologically-plausible assumptions, and propose a couple of Biologically-Related A priori Network Enhancement (BRANE) techniques. They can be used in post-processing of other network inferences techniques like CLR (Context Likelihood of Relatedness) or GENIE3 (GEne Network Inference with Ensemble of trees). They have been successfully tested on DREAM4 and DREAM5 challenges, Escherichia coli, Trichoderma reesei. Graph inference in the inferred Escherichia coli network is evaluated using the STRING database. Clustering is compared to SIMONE, WGCNA, X-means and RegulonDB.

The BRANE approach notably uses image processing and computer vision algorithms (dual thresholding, proximal methods, graph cuts, maximization-majorization), as noted in Enhancing gene regulatory network inference through data integration with markov random fields, Banf & Rhee, Nature Scientific Reports, 2017.
Borrowing concepts from the field of Computer Vision to infer gene regulatory networks in prokaryotes has recently gained some attention
Publications on the BRANE methodology:
  • BRANE HK (aka BRANE Cone): upcoming
BRANE: Biologically-related A priori Network Enhancement for gene regulation network
BRANE application papers:
A note in passing: on Gilles Azzoni, wine producer (Le Raisin et l'Ange), who inspired our BRANE tools with his biodynamic Bran wines.