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，以研究生物网络的动态（1），遗传变异和结构变异对基因表达，生物表型和疾病的影响。我们特别感兴趣的是了解复杂性状背后的遗传相互作用。我们已经开发了两种新的方法，上位相互作用的计算检测（手稿在准备和手稿提交）。 我们的上位性研究是在酵母和疟原虫的背景下进行的。 在一项相关的研究中，我们开发了一种新的方法，可以识别疾病中失调的途径和基因型变异，这是这种失调的假定原因。 在该方法中，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。 使用这种方法，我们追踪了人类网络中拷贝数变化引起的表达变化的传播，以及相关扰动如何失调特定疾病相关的子网络和基因。 我们已经在PloS Computational Biology（5）中发表了将其应用于胶质瘤的方法结果，并在Physical Biology（4）中发表了该方法的数学结果。 拷贝数变异对基因表达的影响也是我们与Brian Olivers实验室合作的主要课题。我们研究了基因剂量对基因表达的影响，以及这些影响在果蝇相互作用网络中的传播（手稿正在编写中）。 最后，放大DNA和RNA结构，我们继续研究DNA结构和基因表达的关系（与大卫莱文斯和拉斐尔Casellas合作;手稿在准备中; Damian Wojtowicz获得海报FARE奖）以及突变对RNA结构的影响及其与疾病的关系（与Michael Gottesman合作;手稿在准备中; Raheleh Salari获得2011年RECOMB最佳海报奖）。我们开发了一种新的强大的方法来测量SNP/突变对RNA结构的影响。