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: 8344970
• 负责人: Teresa Przytycka
• 金额: $ 122.92万
• 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/8344970
• 关键词: Award; Binding; Biological; Biology; Cells; Collaborations; Complex; Computational Biology; Computing Methodologies; Copy Number Polymorphism; DNA; DNA Structure; Data; Dependency; Detection; Disease; Dose; Elements; Evolution; Gene Dosage; Gene Expression; Gene Expression Regulation; Genes; Genetic; Genetic Epistasis; Genetic Variation; Genotype; Glioma; Graph; Growth Factor Gene; Human; Language; Malignant Neoplasms; Manuscripts; Measures; Methods; Modeling; Molecular; Mutation; Noise; Pathway interactions; Phenotype; Plasmodium; Play; Preparation; Property; Proteins; Publishing; RNA; Regulation; Regulatory Element; Role; Signal Transduction; Structure; System; Systems Biology; Technology; Tertiary Protein Structure; Variant; Work; Yeasts; base; biological systems; combinatorial; disease phenotype; fly; insight; interest; mathematical model; posters; response; theories; tool; trait

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.

我的小组继续研究计算方法，研究生物网络的动力学（1），遗传变异的影响以及结构变异对基因表达，生物体表型和疾病的影响。我们对理解复杂性状的基础遗传相互作用特别感兴趣。我们已经开发了两种新方法来检测上任互动（在提交中制备和手稿中的手稿）。 我们对上毒的研究是在酵母和疟原虫的背景下进行的。 在一项相关研究中，我们开发了一种新方法，该方法允许识别在疾病和基因型变异中受调节的途径，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。 使用这种方法，我们追溯了由人网络中拷贝数变化以及相关扰动调节特定特定疾病相关的子网和基因引起的表达变化的传播。 我们已经发布了其在PLOS计算生物学中应用于神经胶质瘤的方法（5），以及物理生物学方法的数学结果（4）。 拷贝数变化对基因表达的影响也是我们与Brian Olivers Lab的合作工作的主要主题。我们研究基因剂量对基因表达的影响以及在苍蝇相互作用网络中这些影响的传播（制备中的手稿）。 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）。我们开发了一种新的强大方法来衡量SNP/突变对RNA结构的影响。