Cancer Informatics Shared Resource

癌症信息学共享资源

• 批准号: 10456692
• 负责人: Colin Noel Dewey
• 金额: $ 44.84万
• 依托单位: UNIVERSITY OF WISCONSIN-MADISON
• 依托单位国家: 美国
• 财政年份: 1997
• 资助国家: 美国
• 起止时间: 1997-04-25 至 2023-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10456692
• 关键词: Address; Adoption; Advisory Committees; Algorithms; Applications Grants; Area; Award; Bioinformatics; Biological; Biometry; Cancer Center; Cancer Center Support Grant; Clinical; Clinical Data; Clinical Informatics; Clinical Research; Computational Science; Data; Data Analyses; Data Set; Databases; Development; Doctor of Philosophy; Electronic Health Record; Ensure; Faculty; Funding; Funding Agency; Gene Expression; Grant; Growth; Image; Image Analysis; Informatics; Leadership; Machine Learning; Malignant Neoplasms; Medical Informatics; Mentors; Mission; National Cancer Institute; Natural Language Processing; Patient-Focused Outcomes; Patients; Pattern; Positioning Attribute; Postdoctoral Fellow; Predictive Analytics; Program Development; Publications; Research; Research Design; Research Personnel; Resources; Role; Scientist; Services; System; Technology; Time; Universities; University of Wisconsin Comprehensive Cancer Center; Visualization; Wisconsin; Work; algorithm development; algorithmic methodologies; anticancer research; artificial neural network; cancer genomics; cost effective; deep learning; design; experience; experimental study; graduate student; improved outcome; informatics shared resource; innovation; knowledge base; machine learning algorithm; machine learning method; member; neoplasm resource; novel; programs; recruit; response; skills; task analysis; tool development; transcriptome sequencing

PROJECT SUMMARY / ABSTRACT The Cancer Informatics Shared Resource (CISR) operates out of the University of Wisconsin (UW) Department of Biostatistics and Medical Informatics (BMI) to serve University of Wisconsin Carbone Cancer Center (UWCCC) members. Our mission is to promote high quality, innovative cancer research by providing members of the UWCCC with bioinformatics and computational expertise and services, including the design of experiments, analysis of research and clinical data, development of tools for analysis and visualization, and interpretation of results. This is achieved through CISR's well-qualified staff: three PhD staff scientists with expertise in state-of-the-art bioinformatics, clinical informatics, and machine learning methodologies; and four highly skilled faculty, who mentor the CISR scientists and collaborate with UWCCC members in cases where new algorithm development is required. CISR continues to advance in its essential role to meet the evolving needs of all UWCCC programs by providing a technical and intellectual resource that addresses the specific bioinformatics and clinical research informatics needs of UWCCC members across all six programs in a reliable and cost-effective manner. CISR accomplishes this through two specific aims, the first of which is a new enhancement made during the most recent CCSG funding cycle in direct response to requests from the UWCCC membership and advice from our advisory committee. Our specific aims are to: 1) provide state-of- the-art Informatics services: image analysis, bioinformatics, cancer genomics, predictive analytics, clinical informatics to facilitate study design and grant applications, and to employ programs to correlate, stratify, and discover patterns from research and clinical data sets using state-of-the-art informatics and machine learning algorithms; and 2) provide world-class Informatics Algorithm/Methodology Development by each of four faculty members with expertise in the development of novel algorithms in areas such as machine learning, electronic health record analysis, causal discovery from observational data, natural language processing, deep learning and knowledge-based artificial neural networks, and RNA-Seq gene expression data analysis. Together, CISR scientists and faculty are agile and have the availability and expertise required to enable UWCCC members to quickly investigate new hypotheses for grant submissions, analyze research or clinical data for publication, as well as tackle more challenging, unsolved research questions which require longer-term research. Funding provided by CCSG will ensure that our team of CISR scientists and faculty will continue to be well positioned to meet the bioinformatics and computational research needs of UWCCC investigators to enable discoveries that can improve outcomes for our patients.

项目总结/摘要 癌症信息学共享资源（CISR）在威斯康星州大学（UW）外运作。 生物统计学和医学信息学系（BMI）为威斯康星州大学Carbone Cancer提供服务 中心（UWCCC）成员。我们的使命是促进高质量，创新的癌症研究，提供 具有生物信息学和计算专业知识和服务的UWCCC成员，包括设计 实验，研究和临床数据的分析，分析和可视化工具的开发，以及 结果的解释。这是通过CISR的高素质的工作人员实现的：三名博士科学家， 在最先进的生物信息学，临床信息学和机器学习方法学方面的专业知识;以及四 高技能的教师，指导CISR科学家，并与UWCCC成员合作， 需要开发新的算法。CISR继续发挥其重要作用，以满足不断变化的 所有UWCCC计划的需求，通过提供技术和知识资源，解决具体的 UWCCC成员在所有六个项目中的生物信息学和临床研究信息学需求 可靠和具有成本效益的方式。CISR通过两个具体目标来实现这一目标，第一个目标是 在最近的CCSG供资周期中，直接应 UWCCC会员资格和我们咨询委员会的建议。我们的具体目标是：1）提供国家- 最先进的信息学服务：图像分析、生物信息学、癌症基因组学、预测分析、临床 信息学，以促进研究设计和赠款申请，并采用程序，以相互关联，分层， 使用最先进的信息学和机器学习从研究和临床数据集中发现模式 算法; 2）由四个学院的每一个提供世界一流的信息学算法/方法论开发 成员具有在机器学习、电子和计算机等领域开发新算法的专业知识， 健康记录分析，从观察数据中发现因果关系，自然语言处理，深度学习 和基于知识的人工神经网络，以及RNA-Seq基因表达数据分析。CISR一起 科学家和教师是敏捷的，并有可用性和专业知识，使UWCCC成员， 快速调查新的假设，以获得资助，分析研究或临床数据以供发表， 以及解决更具挑战性的、需要长期研究的未解决的研究问题。资金 CCSG提供的技术将确保我们的CISR科学家和教师团队将继续处于有利地位， 满足UWCCC研究人员的生物信息学和计算研究需求，以实现以下发现： 可以改善患者的预后。