Algorithmic approaches to systems biology, data integration, and evolution

系统生物学、数据集成和进化的算法方法

• 批准号: 9555743
• 负责人: Teresa Przytycka
• 金额: $ 141.35万
• 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/9555743
• 关键词: Adult; Algorithmic Software; Algorithms; Area; Award; B-Lymphocytes; Binding; Biological; Cell physiology; Cells; Chromatin; Collaborations; Complex; Computational Biology; Computer Analysis; Computer Simulation; Computer software; Computing Methodologies; Cytotoxic agent; DNA; DNA Maintenance; DNA Sequence; DNA Structure; Data; Data Set; Dependency; Development; Disease; Drosophila genus; Elements; Evolution; Fluorouracil; Focus Groups; Gene Dosage; Gene Expression; Gene Expression Regulation; Gene Targeting; Genes; Genetic; Genotype; Graph; Growth Factor Gene; Hand; Heterogeneity; In Vitro; Language; Left; Location; Machine Learning; Malignant Neoplasms; Malignant neoplasm of pancreas; Maps; Methodology; Methods; Molecular; Molecular Conformation; Mus; Mutate; Mutation; Network-based; Noise; Normal Cell; Nucleosomes; Oral; Paper; Pharmaceutical Preparations; Phenotype; Physiological Processes; Play; Positioning Attribute; Potassium Permanganate; Prevalence; Property; Publishing; RNA; RNA Polymerase II; Regulator Genes; Regulatory Element; Reporting; Research; Resolution; Role; Sampling; Sequence Analysis; Signal Transduction; Site; Structure; System; Systems Biology; Techniques; Technology; Therapeutic Index; Tissues; Variant; Work; aptamer; base; biological systems; cancer cell; cancer subtypes; chemotherapeutic agent; data integration; design; fly; gemcitabine; gene function; genome-wide; graph theory; improved; in vivo; insight; method development; novel; nuclease; programs; quadruplex DNA; response; sex; success; symposium; theories; tool; transcription factor

My group continued to work on computational methods to study the dynamics of biological networks, impact of genetic and structural My group continued to develop and apply computational methods to study the dynamics of biological networks, impact of genetic and structural variation on gene expression and phenotype with emphasis on studies related to cancer and its heterogeneity. We also continued our research on the role of DNA conformational dynamics for gene regulation, and methods for analysis of HT-SELEX data. In particular, we worked on new computational methods to delineate genetic underpinnings of cancer and interactions between them. We focused on delineating properties on mutational landscape of cancer. In particular, we utilized our recently developed Weighted Sampling Mutual Exclusivity (WeSME) method to estimate statistical significance of Mutual Exclusivity (ME) relation (1) and our novel optimization technique, BeWith, to investigate various aspects of the cancer mutational landscape, leading to uncovering relationships between mutated gene modules, cancer subtypes, and mutational signatures. A paper describing preliminary results of this work has been invited for an oral presentation at RECOMB 2017 a premier conference in Computational Biology. We also continued developing our comprehensive software package, AptaTools, for analysis of HT-SELEX derived Aptamers - synthetic. We are preparing the next release of the software for late 2017. In addition, our expertise in this area has led to the collaborative studies with experimental groups as for example the work reported in (2). We also developed a method to construct RNA-drug conjugates. Aptamer-drug conjugates (ApDCs) have the potential to improve the therapeutic index of traditional chemotherapeutic agents due to their ability to deliver cytotoxic drugs specifically to cancer cells while sparing normal cells. One of the conjugated designed by us has been to obtain the conjugation of cytotoxic drugs to an aptamer previously described by our group, the pancreatic cancer RNA aptamer P19. To this end, P19 was incorporated with gemcitabine and 5-fluorouracil (5-FU), or conjugated to monomethyl auristatin E (MMAE) and derivative of maytansine 1 (3). We are also continuing our long-standing collaboration with Brian Oliver's group on gene regulation in Drosophila. In particular we used the data generated in (4) for constructing sex specific gene regulatory networks (GRN) for adult drosophila. GRN describe regulatory relationship between transcription factors and their target genes. Methods to infer GRNs are typically context-agnostic based on evidence collected in many different conditions, disregarding the fact that regulatory programs are conditioned on tissue type, developmental stage, sex, and other factors. We focused our studies on developing a novel network inference method NetREX, that given a context-agnostic network as a prior and context-specific expression data (e.g. expression in an adult fly), constructs a context-specific GRN by rewiring the prior network. We reported the preliminary results related to the method development on RECOMB 2017, one of the most prestigious conferences in Computational Biology, where this work has been awarded the best paper award. Several new methodological advancements introduced in this contributed to the success of NetREX. In particular, one of the key contributions is the development of a convergent algorithm that can estimate unknown TFAs while rewiring the prior network based the recently proposed PALM framework. Finally, we are also continuing our long standing collaboration with David Levens group focusing on the role of DNA conformational dynamics in gene. DNA in cells is predominantly B-form double helix. Though certain DNA sequences in vitro may fold into other structures, such as triplex, left-handed Z form, or quadruplex DNA, the stability and prevalence of these structures in vivo were not known. Using computational analysis of sequence motifs, RNA polymerase II binding data, and genome-wide potassium permanganate-dependent nuclease footprinting data, we mapped thousands of putative non-B DNA sites at high resolution in mouse B cells. Computational analysis associated these non-B DNAs with particular structures and indicates that they form at locations compatible with an involvement in gene regulation. Further analyses supported the notion that non-B DNA structure formation influences the occupancy and positioning of nucleosomes in chromatin. These results, published in Cell Systems (5) suggested that non-B DNAs contribute to the control of a variety of critical cellular and organismal processes.

我的团队继续研究计算方法，以研究生物网络的动态，遗传和结构的影响。我的团队继续开发和应用计算方法来研究生物网络的动态，遗传和结构变化对基因表达和表型的影响，重点是与癌症及其异质性有关的研究。我们还继续研究DNA构象动力学在基因调控中的作用，以及分析HT-SELEX数据的方法。 特别是，我们致力于新的计算方法来描绘癌症的遗传基础以及它们之间的相互作用。我们专注于描绘癌症突变图景的特性。特别是，我们利用我们最近开发的加权抽样互斥(WeSME)方法来估计互斥(ME)关系(1)的统计意义，并利用我们的新优化技术BeWith来研究癌症突变格局的各个方面，从而揭示突变基因模块、癌症亚型和突变特征之间的关系。描述这项工作的初步结果的一篇论文已被邀请在计算生物学的首要会议RECOMB 2017上作口头陈述。 我们还继续开发我们的综合软件包AptaTools，用于分析HT-SELEX衍生的适体合成。我们正在准备2017年底发布的下一版软件。此外，我们在这一领域的专门知识促成了与实验小组的合作研究，例如(2)中报告的工作。我们还开发了一种构建RNA-药物偶联物的方法。适体-药物结合物(ApDCs)由于能够将细胞毒药物特异性地输送到癌细胞，而不影响正常细胞，因此有可能提高传统化疗药物的治疗指数。我们设计的其中一种偶联物是将细胞毒药物与我们小组之前描述的适体P19偶联。为此，P19与吉西他滨和5-氟尿嘧啶(5-FU)结合，或与单甲基金雀异黄素E(MMAE)和美坦辛1(3)的衍生物偶联。 我们还在继续与布莱恩·奥利弗的团队在果蝇基因调控方面的长期合作。特别是，我们使用(4)中产生的数据来构建成年果蝇的性别特异性基因调控网络(GRN)。GRN描述转录因子与其靶基因之间的调控关系。推断GRN的方法通常是基于在许多不同条件下收集的证据，而忽略了调控程序受组织类型、发育阶段、性别和其他因素影响的事实。我们的研究集中在开发一种新的网络推理方法NetREX，该方法将上下文不可知的网络作为先验的和上下文特定的表达数据(如成虫的表达)，通过重新连接先前的网络来构建上下文特定的GRN。我们报告了与RECOMB 2017方法开发相关的初步结果，RECOMB 2017是计算生物学中最负盛名的会议之一，这项工作已被授予最佳论文奖。其中引入的几个新的方法进步促成了NetREX的成功。特别是，其中一个关键贡献是开发了一种收敛算法，该算法可以估计未知的TFA，同时基于最近提出的Palm框架重新布线先前的网络。 最后，我们还在继续我们与David Levens小组的长期合作，重点关注DNA构象动力学在基因中的作用。细胞中的DNA主要是B型双螺旋结构。虽然某些DNA序列在体外可能折叠成其他结构，如三链、左手Z型或四链DNA，但这些结构在体内的稳定性和普遍性尚不清楚。利用对序列基序、RNA聚合酶II结合数据和全基因组高锰酸钾依赖的核酸酶足迹数据的计算分析，我们在小鼠B细胞中以高分辨率绘制了数千个假定的非B DNA位点。计算分析将这些非B-DNA与特定的结构相关联，并表明它们形成于与基因调控相关的位置。进一步的分析支持非B DNA结构的形成影响核小体在染色质中的占位和定位的观点。发表在《细胞系统》(5)上的这些结果表明，非B-DNA有助于控制各种关键的细胞和生物过程。