Strategic Planning for the New "Center for Integrative Bioinformatics and Experimental Mathematics (CIBEM)"
Recent advances in the development and application of cutting-edge biomedical technologies have significantly accelerated the generation of complex high-throughput data that potentially enable us to gain new insights into life sciences. However, to analyze and extract meaningful information from such complex data, novel and sophisticated quantitative techniques and approaches must be developed and integrated systematically. The quantitative and computational methods for high-throughput data have become a major component in biomedical research and an indispensable tool in interrogating biological systems in the modern era. Based on the Division of Biomedical Modeling and Informatics, the Center for Integrative Bioinformatics and Experimental Mathematics (CIBEM) is created and established within the Department of Biostatistics and Computational Biology (DBCB) in order to integrate and consolidate available resources and expertise on University of Rochester (UR) campus to meet the challenges. The new Center's missions are
Although most of the Center's faculty members will
have primary appointments in DBCB, the Center's membership may also include
adjunct faculty from other departments across
The current members of the CIBEM include 5 tenured or tenure-track faculty, 2 research-track faculty, 11 research associate/assistant or staff (statisticians, programmers, data managers, software developers), 6 postdoctoral fellows, 4 PhD students, 1 adjunct professor, and several visiting scholars. We are also recruiting several tenure-track faculty, research associates, and postdoctoral fellows in bioinformatics for the new Center. The expertise and research interests of current center members include bioinformatics data analysis and modeling, biostatistics, biomathematical modeling and computational biology, complex high-dimensional data analysis, network modeling, bio-imaging data processing and analysis, numerical computing and optimization, bioinformatics computing and analysis software development, and translational data management and data management system development. Strong collaboration/consulting services and education program will be established. A seed-funding pilot award program will be developed to promote collaborations between computational bioinformaticians and experimental bioinformaticians.