Cancer Informatics Shared Resource

University Of Wisconsin-Madison, Madison WI

Investigators

Linked publications, trials & patents

Abstract

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.