Bioinformatics and Pathways Core

生物信息学和通路核心

• 批准号: 10629617
• 负责人: Jonathan Daniel Wren
• 金额: $ 48.5万
• 依托单位: OKLAHOMA MEDICAL RESEARCH FOUNDATION
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-01 至 2028-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10629617
• 关键词: Acceleration; Applications Grants; Bioinformatics; Biological; Centers of Research Excellence; ChIP-seq; Chemicals; Computer software; Data; Data Analyses; Databases; Dedications; Development; Developmental Biology; Disease; Doctor of Philosophy; Ensure; FAIR principles; Fee-for-Service Plans; Feedback; Future; Gene Expression; Genes; Genomic Segment; Genomics; Human Resources; Image Analysis; Institution; Literature; Meta-Analysis; Methods; Modeling; Nature; Network-based; Oklahoma; Participant; Pathway interactions; Peer Review; Phase; Phenotype; Property; Publications; Publishing; Research; Research Design; Research Personnel; Resources; Sample Size; Scientist; Services; Technology; Troglodytinae; cohesion; cost effective; data integration; design; differential expression; experience; experimental analysis; experimental study; high throughput analysis; improved; interest; machine learning method; novel; novel strategies; power analysis; public database; skills; task analysis; tool; transcriptome sequencing

ABSTRACT BIOINFORMATICS & PATHWAYS CORE The Bioinformatics and Pathways Core (BPC) will support users with bioinformatics analysis of high- throughput experiments such as RNA-seq, ChIP-seq, and genomic analyses, and provide statistical support in both the design and interpretation of experiments. During Phases I and II of this COBRE, BPC support has helped substantially to increase the competitiveness of Project Lead grant applications, based upon reviewer feedback. The BPC is led by Dr. Jonathan Wren, a bioinformatician with 19 years of experience and includes a dedicated Ph.D.-level Statistician and a Bioinformatics Scientist. Our Specific Aims are: Aim 1: Create a cost-effective resource for high-quality, advanced data analysis services, employing both fee-for-service and collaborative models. BPC personnel have extensive experience using state-of- the-art bioinformatics methods, as well as a track record of developing novel analysis methods. We will provide support for pre-experimental study design, including power analyses and utilize novel bioinformatics and statistical tools to solve specific biological questions posed by COBRE participants. The Core Director has developed a number of novel tools, such as software to: 1) Automate the identification and analysis of related entities of interest (e.g., genes, diseases, phenotypes, etc.) within the published literature; 2) Identify features, properties and experiments that overlap with genomic regions of interest; 3) Identify and analyze experiments in public microarray databases like NCBI’s Gene Expression Omnibus (GEO) through meta-analysis and 4) Interpret differentially expressed genes in terms of the correlations between them within public databases. Aim 2: Provide a set of experienced analysts with a diversity of skills and expertise to accommodate a variety of future analysis projects. This COBRE has enabled the BPC to develop novel software and to hire personnel with a set of skills broadly useful to helping biomedical researchers. And, as evidenced by our collaborative publications during COBRE Phases I and II, we have been successful at using our capabilities to help others advance their research. Phase III will enable us to establish a self-sustaining institutional Core. Aim 3: Continue to develop, evaluate, and refine new methods of data analysis and data integration. The BPC will develop increasingly sophisticated and powerful technologies that evolve with the demands of scientific investigators. We will improve tracking of resource utilization, advance technologies that improve online interactivity between the data provided and our analysis of it, help investigators make their data compliant with FAIR principles, develop methods for evaluating network-based data cohesion, and advance machine-learning methods for common image analysis tasks.

抽象生物信息学&路径核心 生物信息学和路径核心(BPC)将支持用户进行高质量的生物信息学分析。 吞吐量实验，如RNA-SEQ、CHIP-SEQ和基因组分析，并提供统计支持 包括实验的设计和解释。在此Cobre的第一阶段和第二阶段，BPC支持 根据审核者的意见，大大提高了项目牵头拨款申请的竞争力 反馈。BPC由乔纳森·雷恩博士领导，他是一名拥有19年经验的生物信息学家，包括 敬业的博士级别的统计学家和生物信息学科学家。我们的具体目标是： 目标1：为高质量、高级数据分析服务创建具有成本效益的资源，使用 收费服务模式和协作模式。BPC人员拥有丰富的使用状态 先进的生物信息学方法，以及开发新的分析方法的记录。我们将提供 支持实验前研究设计，包括电力分析和利用新的生物信息学和 解决Cobre参与者提出的特定生物学问题的统计工具。核心总监已经 开发了许多新的工具，如用于：1)自动识别和分析相关的 感兴趣的实体(例如，基因、疾病、表型等)在出版的文献中；2)识别特征， 与基因组感兴趣区域重叠的特性和实验；3)识别和分析实验 在公共微阵列数据库中，如NCBI的基因表达总览(GEO)通过荟萃分析和4) 根据公共数据库中差异表达基因之间的相关性解释差异表达的基因。 目标2：提供一批具有各种技能和专业知识的经验丰富的分析师，以适应 各种未来分析项目。这个Cobre使BPC能够开发新的软件并聘请 具有对帮助生物医学研究人员广泛有用的一套技能的人员。而且，正如我们的 协作出版在Cobre第一阶段和第二阶段期间，我们成功地利用我们的能力 帮助其他人推进他们的研究。第三阶段将使我们能够建立一个自给自足的机构核心。 目标3：继续开发、评估和改进数据分析和数据集成的新方法。 BPC将开发日益复杂和强大的技术，这些技术将随着 科学调查人员。我们将改进对资源利用的跟踪，推动技术进步 提供的数据和我们对数据的分析之间的在线互动，帮助调查人员制作数据 遵循公平原则，制定评估基于网络的数据凝聚力的方法，并推动 常见图像分析任务的机器学习方法。