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

系统生物学和分子生物学的组合和图论方法。

• 批准号: 8149615
• 负责人: Teresa Przytycka
• 金额: $ 115.56万
• 依托单位: NATIONAL LIBRARY OF MEDICINE
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/8149615
• 关键词: Binding; Computational Molecular Biology; DNA; Dependency; Disease; Elements; Graph; Insulin-Like-Growth Factor I Receptor; Systems Biology; combinatorial

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).

我继续研究遗传变异对基因表达和疾病的影响。我们已经取得了进步，将我们最近的EQTL分析方法扩展到上皮相互作用（制备中的手稿）。我们还开发了一种新方法，该方法允许在疾病和基因型变异中iDnetyfy途径进行DYS调节，这些途径是这种Dys-调节的推定原因。在这种方法中，我们将相互作用网络建模为电路，以及从基因型到基因表达的信息流作为电流流动。 邀请了一项描述这项工作初步结果的手稿，以在最近的分子计算生物学研究会议上进行口头介绍（Recomb 2010）。 我的小组还继续研究信号网络中信号传播的计算方法。我们开发了一种基于模糊的逻辑方法，并将其用于研究表皮生长因子受体（EGFR），胰岛素样生长因子-1受体（IGF-1R）和胰岛素受体（IR）信号网络，并阐明组件途径之间的串扰（7）。我们使模拟软件免费提供（6）。 继续我们在密码子使用方面的工作，我们能够证明密码子的使用已优化，以避免翻译中的帧误差（1）。我们使用了本文开发的框架变化模型来进一步研究帧误差的鲁棒性（5）。