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COBRE: Center for Computational Biology of Human Disease

COBRE：人类疾病计算生物学中心

基本信息

批准号：
10681232
负责人：
DAVID M RAND
金额：
$ 225.31万
依托单位：
BROWN UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2016
资助国家：
美国
起止时间：
2016-06-01 至 2026-07-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10681232
关键词：
Acceleration Address Award Biochemical Bioinformatics Biological Biological Models Biology Biomedical Research CRISPR/Cas technology Cell physiology Centers of Research Excellence Clinical Collaborations Communities Computational Biology Creativeness Data Data Analyses Data Scientist Disease Drug resistance Ensure Environment Faculty Faculty Recruitment Funding Gene Expression Gene Expression Profile Genital Genitalia Goals Grant Growth Hospitals Human Biology Infrastructure Joints Laboratory Scientists Language Maps Mentors Mission Modeling Mucous Membrane Multiomic Data Neoplasm Circulating Cells Pathway interactions Phase Philosophy Pilot Projects Program Research Project Grants Proteins Regulator Genes Research Research Infrastructure Research Personnel Research Project Grants Research Support Rhode Island Science Scientist Services Sexually Transmitted Diseases Software Engineering Specificity T cell differentiation T cell regulation T-Cell Development Technology Therapeutic Training Training and Infrastructure Tumor Cell Invasion United States Department of Agriculture United States National Institutes of Health Universities Vaccines bioinformatics tool biological research cell type computer infrastructure computerized tools data acquisition deep learning graph neural network human disease innovation medical schools member operation programs reproductive senior faculty single cell sequencing skills three dimensional cell culture tissue resident memory T cell translational medicine

项目摘要

PROJECT SUMMARY We propose to strengthen and extend the research capacity of the COBRE Center for the Computational Biology of Human Disease (CBHD) at Brown University and affiliated hospitals. High throughput data from multiple ‘omics-level’ technologies are fundamental factors in the identification and treatment of human disease. The acquisition of these data is now straightforward, but the efficient and creative interpretation of these data remain a serious impediment to progress for junior faculty in both the basic and translational aspects of biomedical science. The underlying principle of this Center is that close collaboration between laboratory scientists working with model systems and data scientists working with computational and bioinformatics tools can accelerate the implementation of human disease research. In Phase 1, we established the CBHD COBRE around a Computational Biology Core (CBC) and support for junior faculty Project Leaders (9) and Pilots Project leaders (8). These Project Leaders have been awarded six NIH R01s, an R35 MIRA, an NIH T32 Training Grant, an NIH R21, a USDA grant, a Sloan Award, and a Searle Award, totaling ~$17.9M. In Phase 2 we will strengthen this research environment with support for four new Project Leaders and a plan for growth and sustainability of the CBC that serves as the analysis and training hub of this COBRE. Our innovative joint mentoring strategy where each Project Leader is advised by both computational and biological or clinical senior faculty members has proven successful, and this will be extended. Moreover, we will build sustainable support for the CBC through expanded collaboration with COBRE graduates and other faculty on external grant support plus internally funded staff data scientists. The long-term goal of the Center is to grow a nexus of computational biology infrastructure for the greater Brown and hospital environments that will benefit all of Rhode Island. The objective of this proposal is to strengthen the infrastructure of the CBHD COBRE to ensure the transition of junior faculty Project Leaders to R01-funded scientists, and raise the computational proficiency and diversity of the broader biomedical research community. The three Aims are: Aim 1. Support the research of junior faculty Project Leaders pursuing biological and computational approaches to human disease. Aim 2. Broaden the CBHD research environment through enhanced Pilot and Mentoring programs that increase faculty recruitment and promote funding independence for Project Leaders. Aim 3. Strengthen the Computational Biology Core through enhanced staffing and broader access across the Brown biomedical community to build sustainability. The four new Research Projects are: 1. Local Regulation of T-cell Differentiation and Function in the Reproductive Mucosa; 2: Profiling Gene Expression and Mechanophenotype in Circulating Tumor Cells Ex Vivo; 3: Mapping Long-range Allosteric Pathways in CRISPR-Cas9; 4: Modeling Long-range Regulatory Interactions to Predict Gene Expression Using Graph Convolutional Networks.

项目摘要我们建议加强和扩大COBRE计算中心的研究能力，人类疾病生物学（CBHD）在布朗大学和附属医院。高通量数据来自多种“组学水平”技术是人类疾病识别和治疗的基本因素。这些数据的获取现在很简单，但对这些数据的高效和创造性解释仍然是初级教师在基础和翻译方面取得进展的严重障碍，生物医学科学该中心的基本原则是实验室之间的密切合作使用模型系统的科学家和使用计算和生物信息学工具的数据科学家可以加速人类疾病研究的实施。在第一阶段，我们建立了CBHD COBRE 围绕计算生物学核心（CBC）和支持初级教师项目领导人（9）和试点项目领导者（8）。这些项目负责人已被授予六个NIH R 01，R35 MIRA，NIH T32培训补助金， NIH R21、美国农业部赠款、斯隆奖和塞尔奖，共计约1790万美元。在第二阶段，我们将加强这一研究环境与支持四个新的项目领导人和增长和可持续发展的计划， CBC是COBRE的分析和训练中心。我们创新的联合指导战略每个项目负责人都由计算和生物或临床高级教员提供建议已经被证明是成功的，而且会被推广。此外，我们将通过以下方式为CBC建立可持续的支持扩大与COBRE毕业生和其他教师在外部赠款支持和内部资助方面的合作数据科学家该中心的长期目标是建立一个计算生物学基础设施的网络，为大布朗和医院环境，将有利于所有的罗得岛。的目的建议加强CBHD COBRE的基础设施，以确保初级教师项目的过渡领导人R 01资助的科学家，并提高更广泛的生物医学领域的计算能力和多样性研究社区。这三个目标是：目标1。支持初级教师的研究项目负责人追求人类疾病的生物学和计算方法。目标2.浏览CBHD研究环境通过加强试点和指导计划，增加教师招聘和促进资金项目负责人的独立性。目标3.通过增加人员配置加强计算生物学核心和更广泛的访问整个布朗生物医学社区，以建立可持续性。四项新研究项目有：1。生殖粘膜中T细胞分化和功能的局部调节; 2：分析体外循环肿瘤细胞中的基因表达和机械表型; 3：远程变构作图 CRISPR-Cas9; 4中的途径：使用建模远程调控相互作用来预测基因表达图卷积网络。

项目成果

期刊论文数量（34）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Revising transcriptome assemblies with phylogenetic information.

DOI：
10.1371/journal.pone.0244202
发表时间：
2021
期刊：
PloS one
影响因子：
3.7
作者：
Guang A;Howison M;Zapata F;Lawrence C;Dunn CW
通讯作者：
Dunn CW

Graphene oxide nanosheets augment silk fibroin aerogels for enhanced water stability and oil adsorption.

DOI：
10.1039/d3na00350g
发表时间：
2023-11-07
期刊：
Nanoscale advances
影响因子：
4.7
作者：
通讯作者：

Proteinarium: Multi-sample protein-protein interaction analysis and visualization tool.

DOI：
10.1016/j.ygeno.2020.07.028
发表时间：
2020-11
期刊：
Genomics
影响因子：
4.4
作者：
Armanious D;Schuster J;Tollefson GA;Agudelo A;DeWan AT;Istrail S;Padbury J;Uzun A
通讯作者：
Uzun A

TIMEOR: a web-based tool to uncover temporal regulatory mechanisms from multi-omics data.