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.