Administrative Supplement for Equipment in Support of NRNB Aims

支持 NRNB 目标的设备行政补充

基本信息

批准号：
10799346
负责人：
Trey Ideker
金额：
$ 14.92万
依托单位：
UNIVERSITY OF CALIFORNIA, SAN DIEGO
依托单位国家：
美国
项目类别：
财政年份：
2010
资助国家：
美国
起止时间：
2010-09-13 至 2025-04-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10799346
关键词：
Administrative Supplement Adopted Algorithms Applications Grants Automobile Driving Binding Bioinformatics Biological Biological Markers Biological Process Biological Sciences Biology Biomedical Research Biomedical Technology Cataloging Cell Communication Cell physiology Cells Cellular Structures Clinical Trials Cloud Computing Collaborations Communities Complex DNA Data Databases Detection Developmental Cell Biology Diabetes Mellitus Disease Disease stratification Drug Modelings Ecosystem Equipment Expert Systems Funding Generations Genes Genotype Health Individual International Knowledge Lead Life Malignant Neoplasms Maps Methods Mission Molecular Biology National Institute of General Medical Sciences Network-based Ontology Organ Pathway Analysis Pathway interactions Patients Pharmaceutical Preparations Policies Procedures Process Proteins Protocols documentation Research Research Personnel Resource Development Resources Sampling Science Scientist Social Network Software Tools Structure System Technology algorithm development biological systems cBioPortal cancer genome clinical phenotype computerized tools deep learning model gene function innovation machine learning model meetings network models neuropsychiatric disorder novel operation pleiotropism predictive tools research study response scaffold software infrastructure symposium technology development technology research and development tool training opportunity transcriptomics

项目摘要

OVERALL - PROJECT SUMMARY The mission of the National Resource for Network Biology (nrnb.org) is to advance the science of biological networks by creating leading-edge bioinformatic methods, software tools and infrastructure, and by engaging the scientific community in a portfolio of collaboration and training opportunities. Much of biomedical research is dependent on knowledge of biological networks of multiple types and scales, including molecular interactions among genes, proteins, metabolites and drugs; cell communication systems; sample similarity networks; relationships among genotypes and biological and clinical phenotypes; and patient and social networks. NRNB technologies, like Cytoscape, are among the most widely used software tools in biology, with tens of thousands of active users, and enable researchers to analyze these networks and use them to better understand biological systems and how they are reprogrammed in disease. Since 2010, the NRNB has been supported as a Biomedical Technology Research Resource of the National Institute of General Medical Sciences. NRNB’s three technology research and development efforts seek to introduce innovative concepts with the potential to transform network biology, transitioning it from a static to a dynamic science (TR&D Project 1); from flat network diagrams to multi-scale hierarchies of biological structure and function (Project 2); and from descriptive interaction maps to interpretable and predictive network models (Project 3). In previous funding periods our technology projects have produced novel and highly cited approaches, including network-based biomarkers for stratification of disease, data-driven gene ontologies assembled completely from network data, and deep learning models of cell structure and function built using biological networks as a scaffold. NRNB has also produced widely adopted software infrastructure, including the Cytoscape ecosystem; the cBioPortal for cancer genomes and pathways; the GeneMANIA network query and gene function prediction tool; the NDEx biological networks cloud; and WikiPathways for biological pathway curation. During the next period of support, we introduce dynamic regulatory networks formulated from single-cell transcriptomics data (TR&D1); efficient algorithms for detection of hierarchical structure and pleiotropy in biological networks (TR&D2); and procedures for using networks to seed machine learning models of drug response that are both mechanistically interpretable and transferable across biomedical contexts (TR&D3). These efforts are developed and applied in close collaboration with outside investigators from 19 Driving Biomedical Projects (DBPs) who specialize in experimental generation of network data, disease biology (cancer, neuropsychiatric disorders, diabetes), single-cell developmental biology, and clinical trials. TR&Ds are also bolstered by 7 Technology Partnerships (TPs), in which NRNB scientists coordinate technology development with leading resource-development groups in biomedical databases, cloud computing, and algorithm development. Beyond these driving collaborations, we will support and expand a portfolio of (currently 50) active research collaborations, organize and lead international meetings including the popular Network Biology track of the Intelligent Systems for Molecular Biology (ISMB) conference; and deliver a rich set of training opportunities and network analysis protocols. Finally, this grant application is the last competitive renewal of this center, which in accordance with NIGMS policy we plan to sunset after 15 years of operation. We thus present plans to transition key technologies and resources to separate support, a process which has already been successful for several tools now supported elsewhere (e.g. cBioPortal, NDEx).

总体 - 项目摘要国家网络生物学资源（NRNB.org）的使命是提高生物学科学通过创建领先的生物信息学方法，软件工具和基础架构以及参与网络合作和培训机会组合中的科学界。生物医学研究的大部分是取决于多种类型和量表的生物网络的知识，包括分子相互作用在基因，蛋白质，代谢产物和药物中；细胞通信系统；样本相似性网络；基因型以及生物学和临床表型之间的关系；以及患者和社交网络。 NRNB 像Cytoscape这样的技术是生物学中使用最广泛的软件工具之一，成千上万活跃的用户，并使研究人员能够分析这些网络并使用它们来更好地了解生物学系统及其在疾病中的重新编程。自2010年以来，NRNB被支持国家一般医学科学研究所的生物医学技术研究资源。 NRNB的三项技术研发工作旨在与改变网络生物学的潜力，将其从静态科学转变为动态科学（TR＆D项目1）；从平坦的网络图到生物结构和功能的多尺度层次结构（项目2）；并来自描述性互动图映射到可解释和预测网络模型（项目3）。在以前的资金中我们的技术项目已经产生了新颖和高度引用的方法，包括基于网络的方法疾病分层的生物标志物，数据驱动的基因本体论完全由网络数据组装而来，以及使用生物网络作为支架的细胞结构和功能的深度学习模型。 NRNB有还生产了广泛采用的软件基础架构，包括Cytoscape生态系统； cbioportal 癌症基因组和途径； GeneMania网络查询和基因功能预测工具； NDEX 生物网络云；和Wikipathways生物通路策划。在下一个支持期间，我们引入了由单细胞制定的动态调节网络转录组学数据（TR＆D1）;用于检测分层结构和多效性的有效算法生物网络（TR＆D2）;和使用网络来播种机器学习模型的程序既可以在生物医学环境（TR＆D3）上进行机械解释和转移。这些努力是与19个驾驶的外部调查人员密切合作的开发和应用专门研究网络数据，疾病生物学（癌症，癌症）的生物医学项目（DBP）神经精神疾病，糖尿病），单细胞发育生物学和临床试验。 TR＆D也是由7个技术伙伴关系（TPS）加强，NRNB科学家协调技术开发在生物医学数据库中领先的资源发展组，云计算和算法发展。除了这些驾驶合作之外，我们还将支持和扩展一个活跃（目前为50）的投资组合研究合作，组织和主持国际会议，包括流行的网络生物学轨道分子生物学智能系统（ISMB）会议；并提供丰富的培训机会和网络分析协议。最后，该赠款申请是该中心的最后一次竞争续约，根据NIGMS政策，我们计划在运营15年后日落。因此，我们提出了计划过渡关键技术和资源以分开支持，这一过程已经成功现在在其他地方支持几种工具（例如CBIOPORTAL，NDEX）。

项目成果

期刊论文数量（200）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Genotype to phenotype via network analysis.

DOI：
10.1016/j.gde.2013.10.003
发表时间：
2013-12
期刊：
CURRENT OPINION IN GENETICS & DEVELOPMENT
影响因子：
4
作者：
Carter, Hannah;Hofree, Matan;Ideker, Trey
通讯作者：
Ideker, Trey

Combined deletion of Pten and p53 in mammary epithelium accelerates triple-negative breast cancer with dependency on eEF2K.

DOI：
10.15252/emmm.201404402
发表时间：
2014-12
期刊：
EMBO molecular medicine
影响因子：
11.1
作者：
Liu JC;Voisin V;Wang S;Wang DY;Jones RA;Datti A;Uehling D;Al-awar R;Egan SE;Bader GD;Tsao M;Mak TW;Zacksenhaus E
通讯作者：
Zacksenhaus E

BraInMap Elucidates the Macromolecular Connectivity Landscape of Mammalian Brain.

DOI：
10.1016/j.cels.2020.03.003
发表时间：
2020-04-22
期刊：
Cell systems
影响因子：
9.3
作者：
Pourhaghighi R;Ash PEA;Phanse S;Goebels F;Hu LZM;Chen S;Zhang Y;Wierbowski SD;Boudeau S;Moutaoufik MT;Malty RH;Malolepsza E;Tsafou K;Nathan A;Cromar G;Guo H;Abdullatif AA;Apicco DJ;Becker LA;Gitler AD;Pulst SM;Youssef A;Hekman R;Havugimana PC;White CA;Blum BC;Ratti A;Bryant CD;Parkinson J;Lage K;Babu M;Yu H;Bader GD;Wolozin B;Emili A
通讯作者：
Emili A

Multi-scale systems genomics analysis predicts pathways, cell types, and drug targets involved in normative variation in peri-adolescent human cognition.