Center for Computational Biotechnology and Genomic Medicine (CCBGM)
The application of genomics across the life sciences industries is currently challenged by an inadequate ability to generate, interpret, and apply genomic data quickly and accurately for a wide variety of applications. Major Innovations in the applicability, timeliness, efficiency, and accuracy of computational genomic methods are needed, and these innovations will develop best when an interdisciplinary team of scientists, engineers, and physicians from academia and industry, spanning computer systems, health care/pharmaceuticals, and life sciences, work together. The University of Illinois at Urbana-Champaign (UIUC) and the Mayo Clinic are building on their longstanding collaboration to form the Center for Computational Biotechnology and Genomic Medicine (CCBGM), which will bring together their excellence in computing, genomic biology, and patient-specific individualized medicine. Working closely with industry, the CCBGM’s multidisciplinary teams will use the power of computational genomics to advance pressing societal issues, such as enabling patient-specific cancer treatment, understanding and modifying microbial communities in diverse environments related to human health and agriculture, and supporting humanity’s rapidly expanding need for food by improving the efficiency of plant and animal agriculture. The CCBGM will leverage UIUC’s long-standing prowess in large-scale parallel systems, big data analytics, and hardware and software system design, to develop new technologies that enable future genomic breakthroughs. A key element of the Center’s vision is to advance breakthroughs at the interface of biology and computing to transform health-care delivery while enhancing efforts that focus on the health science needs of underrepresented minorities.
The CCBGM will bring together an interdisciplinary team to address the colossal genomic data challenge. Academia/industry partnerships will enhance research, education, and entrepreneurship while performing important technology transfer. The Center will achieve transformational computing innovations on three fronts. (1) It will innovate computing and data management to deal with issues of scaling to the ever-growing volume, velocity, and variety of genomic data. It will concentrate initially on scaling the computation of epistatic interactions (interactions between two or more genes or DNA variants) in genome-wide association study data, generating lists of genomic features that are maximally predictive of phenotypes, and information-compression algorithms for genomic data storage and transfer. (2) It will revolutionize the generation of actionable intelligence from multimodal structured and unstructured data, to generate knowledge from big data. The emphasis will be on the processing and integration of genomic and multi-omic data, and on the merging of unstructured phenotypic data with information from curated data sources (e.g., electronic medical records, annotation databases). The integration of these diverse data types will improve discovery research, predictive genomics, diagnostics, prognostics, and theranostics. Application areas include targeted cancer therapy, pharmacogenomics, crop improvement, and predictive microbiome analysis. (3) It will achieve systems innovation by designing computer systems specially suited for computational genomics, providing unprecedented speed and energy efficiency while preserving the accuracy of the analytics. The systems will be used to quantify and improve the accuracy of detecting genomic variation and, more generally, to optimize computing architectures for the execution of genome analysis workflows.