Combinatorial and graph theoretical approach to systems biology and mol. evo.

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My group continued to work on computational methods to study the dynamics of biological networks (1), impact of genetic variations and structural variation on gene expression, organismal phenotype and diseases. We are particularly interested in understanding genetic interactions underlying complex traits. We have developed two new methods for computational detection of epistatic interaction (manuscript in preparation and manuscript in submission). Our studies of epistasis are performed in the context of yeast and Plasmodium. In a related study, we developed a new method that allows to identify pathways dys-regulated in diseases and genotypic variation that are putative causes of such dys-regulation. In this method we model interaction network as an electric circuit and the flow of information from genotype to gene expression as current flow. Using this approach we traced the propagation of expression changes caused by copy number variations in human network and how related perturbation dys-regulate specific disease-related subnetworks and genes. We have published the method results of its application to Glioma in PloS Computational Biology (5), and mathematical results underlying the methods in Physical Biology (4). The impact of copy number variation on gene expression is also the main subject of our collaborative work with Brian Olivers lab. We study the effect of gene dose on gene expression and the propagation of these effects in the fly interaction network (manuscript in preparation). Finally, zooming an the DNA and RNA structures, we continue to study the relation of DNA structure and gene expression (collaboration with David Levens and Rafael Casellas; manuscript in preparation; poster FARE award for Damian Wojtowicz) and the impact of mutations on RNA structure and their relation to disease (collaboration with Michael Gottesman; manuscript in preparation; best poster award of RECOMB 2011 for Raheleh Salari). We have developed a new powerful method to measure the impact of a SNP/mutation on RNA structure.