MacMillan: Project 3; Technology Development and Research Project #3: Bioinformatics (White)

麦克米伦：项目 3；

• 批准号: 8881715
• 负责人: MICHAEL A. WHITE
• 金额: $ 6.29万
• 依托单位: UT SOUTHWESTERN MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2020-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8881715
• 关键词: Acute; Affinity; Algorithms; Area; Bioinformatics; Biological; Biological Assay; Biological Factors; Biology; Botanicals; Cancer cell line; Cell Line; Chemicals; Cluster Analysis; Communities; DNA; Data; Data Analyses; Data Correlations; Data Set; Databases; Development; Diet; Disease; Dose; Euclidean Space; Experimental Designs; Gene Expression; Generations; Genes; Genetic; Goals; Grant; Guilt; Imagery; Individual; Informatics; Lead; Libraries; Link; Malignant Neoplasms; Malignant neoplasm of lung; Maps; Measures; Messenger RNA; Metadata; Methods; Microscopy; Modeling; Molecular; Molecular Profiling; Non-Small-Cell Lung Carcinoma; Ontology; Output; Pathway interactions; Patient Rights; Phenotype; Phylogenetic Analysis; Process; Reading; Reporter; Reporter Genes; Research Project Grants; Safety; Series; Signal Pathway; Source; Technology; The Cancer Genome Atlas; Therapeutic; Time; Trees; Validation; Variant; abstracting; base; chemical genetics; computerized data processing; cytotoxicity; data visualization; disorder subtype; evidence base; file format; high throughput technology; innovation; insight; interest; metabolomics; molecular scale; research and development; research study; screening; technology development; tool; tool development; transcriptomics; tumor

Abstract: Technology and Research Development Project #3: Bioinformatics is responsible for the development of tools and methods for the analysis of data from the other technology projects that are part of this proposal. This takes advantage of the data analytics and informatics strengths of UTSW and UCSC to help produce a broad-scale molecular and chemical annotation of large libraries of natural products and botanicals. Our deliverable will be a data and data analytics pipeline that will help define a cytological signature to chemical entities, map chemical entities to signaling pathways they interrupt, help identify principal nodes in normal and diseased biological networks that natural products and botanicals target, and help indicate potential therapeutic/dietary applications for these compounds. This will be accomplished by using a series of data analysis methods including 1) Clustering analysis of natural products fractions and botanical activity by the affinity propagation clustering (APC) algorithm. This algorithm can be applied to data features generated by cytological profiling, unbiased metabolomics and FUSION. 2) Use of Euclidean distance distribution to generate a similarity matrix for all of the chemical and genetic perturbagens in FUSION to obtain “guilt by association correlations. 1) Develop tools for intuitive data visualization based on phylogenetic tree algorithms. These tools will be developed for visualization of not only the data generated by TRD#1 and TRD#2, but by other large scale methods looking at natural product mechanisms of action. The ultimate goal of the bioinformatics component of this grant is to drive the generation of hypotheses on the biological activity of the chemical being evaluated and provide this information to the scientific community.

摘要：技术和研究开发项目#3：生物信息学负责 开发用于分析来自其他技术项目的数据的工具和方法 该提案利用了 UTSW 和 UCSC 的数据分析和信息学优势来提供帮助。 对大型天然产物和植物药库进行广泛的分子和化学注释。 我们的交付成果将是一个数据和数据分析管道，它将帮助定义细胞学特征 化学实体，将化学实体映射到它们中断的信号通路，帮助识别主要节点 天然产品和植物药针对的正常和患病的生物网络，并帮助表明 这些化合物的潜在治疗/饮食应用这将通过使用一系列来实现。 数据分析方法包括 1) 天然产物组分和植物活性的聚类分析 亲和传播聚类（APC）算法该算法可以应用于由 生成的数据特征。 细胞学分析、无偏代谢组学和 FUSION 2) 使用欧几里得距离分布。 为 FUSION 中的所有化学和遗传扰动因素生成一个相似矩阵，以获得“罪恶感” 1) 开发基于系统发育树算法的直观数据可视化工具。 这些工具的开发不仅用于可视化 TRD#1 和 TRD#2 生成的数据，还用于可视化 其他大规模方法研究天然产物的作用机制。 这笔赠款的生物信息学部分是推动关于生物活性的假设的产生 正在评估的化学品并向科学界提供此信息。