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

我继续研究遗传变异对基因表达和疾病的影响。我们已经取得了进展，将我们最近的eQTL分析方法扩展到上位相互作用（手稿正在准备中）。我们还开发了一种新方法，可以识别疾病中失调的途径和基因型变异，这些途径被认为是这种失调的原因。在这种方法中，我们将相互作用网络建模为电路，将从基因型到基因表达的信息流建模为电流。描述这项工作的初步结果的手稿已被邀请在最近的分子计算生物学研究会议（RECOMB 2010）上作口头报告。

I continued to study the impact of genetic variations on gene expression and diseases. We have made progress towards extending our recent method of eQTL analysis to epistatic interaction (manuscript in preparation). We also developed a new method that allows to idnetyfy 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. A manuscript describing preliminary results of this work has been invited for an oral presentation on the recent Conference on Research in Molecular Computational Biology (RECOMB 2010). My group also continued to work on computational methods for simulation of signal propagation in signaling network. We developed a fuzzy logic based approach and used it to study the combined Epidermal Growth Factor Receptor (EGFR), Insulin-like Growth Factor-1 Receptor (IGF-1R), and Insulin Receptor (IR) signaling network and to elucidate the crosstalk between the component pathways (7). We made the simulation software is freely available (6). Continuing our work on codon usage, we have been able to demonstrate that codon usage is optimized towards avoiding frameshifting errors in translation (1). We used the frame shifting model developed in this paper to further study the robustness to frameshifting errors(5).