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.

我的小组继续研究计算方法，以研究生物网络的动态，遗传和结构的影响，我的小组继续开发并应用计算方法来研究生物网络的动力学，遗传和结构变化对基因表达和表型的影响，重点是研究与癌症及其异质性有关的研究。我们还继续研究DNA构象动力学对基因调节的作用以及用于分析HT-SELEX数据的方法。 特别是，我们研究了新的计算方法来描述癌症的遗传基础及其之间的相互作用。我们专注于描述癌症突变景观的特性。特别是，我们利用了我们最近开发的加权采样相互排他性（WESME）方法来估计相互排他性（ME）关系（1）和我们的新颖优化技术的统计意义，以研究癌症突变环境的各个方面，从而导致突变基因模块化，癌症子型和cocyational Signational Signations Signations cassections oferce of clusation。邀请了一篇描述这项工作初步结果的论文，邀请了在2017年Recomb举行的一项计算生物学的主要会议上进行口头介绍。 我们还继续开发我们的综合软件包Aptatools，以分析HT -SELEX衍生的适体 - 合成。我们正在准备2017年末软件的下一个版本。此外，我们在该领域的专业知识导致与实验组进行了协作研究，例如（2）中报告的工作。我们还开发了一种构建RNA-grug共轭物的方法。适体毒物缀合物（APDC）具有改善传统化学治疗剂的治疗指数，因为它们能够在保留正常细胞的同时将细胞毒性药物专门递送给癌细胞。我们设计的共轭之一是为了获得先前由我们组胰腺癌RNA Aptamer P19所描述的适体的结合。为此，将P19与吉西他滨和5-氟尿嘧啶（5-FU）合并，或与Maytansine 1（3）的单甲基甲氨酸E（MMAE）和衍生物结合。 我们还继续与布莱恩·奥利弗（Brian Oliver）的果蝇基因调节小组的长期合作。特别是，我们使用（4）中生成的数据用于为成年果蝇构建性别特异性基因调节网络（GRN）。 GRN描述了转录因子及其靶基因之间的调节关系。推断GRN的方法通常是基于在许多不同条件下收集的证据的上下文不可知的，而无视监管计划以组织类型，发育阶段，性别和其他因素为条件的事实。我们将研究重点放在开发一种新型网络推理方法NetRex上，该方法将上下文不合时宜的网络作为先前和上下文特定的表达数据（例如，在成年蝇中的表达），通过重新布线来构建上下文特定的GRN。我们报道了与《 2017年Rebomb》的方法开发有关的初步结果，这是计算生物学上最负盛名的会议之一，该会议已获得最佳纸张奖。 在这一过程中引入的一些新方法学进步促进了Netrex的成功。特别是，关键贡献之一是开发收敛算法，该算法可以在基于最近提出的棕榈框架基于先前的网络时估算未知的TFA。 最后，我们还继续与David Levens集团长期合作，重点关注DNA构象动态在Gene中的作用。细胞中的DNA主要是B形式的双螺旋。尽管体外某些DNA序列可能会折叠成其他结构，例如三型，左手z形式或四链体DNA，但这些结构在体内的稳定性和流行率尚不清楚。使用序列基序的计算分析，RNA聚合酶II结合数据和全基因组钾依赖的核酸酶足迹数据，我们在小鼠B细胞中以高分辨率绘制了数千个推定的非B DNA位点。计算分析将这些非B DNA与特定结构相关联，并表明它们在兼容基因调控的位置形成。进一步的分析支持了以下观点：非B DNA结构形成会影响染色质中核小体的占用和定位。这些结果发表在细胞系统（5）上表明，非B DNA有助于控制各种关键细胞和生物体过程。