About the CCIB |
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OverviewWhat is computational and integrative biology? At a general level, computational biology is the study of biological systems using tools from traditional biomedical disciplines such as biology, chemistry and physics integrated with methods for analysis of interacting complex systems frommathematics and computer science. In particular, computational analysis is a prominent aspect of integrative biology, which analyzes a large number of interacting biological variables to obtain a fuller overall understanding of complex biological systems. The goal of integrative biology is to extract broad quantitative organizational principles that can relate interactions of component parts to macroscopic behaviors of the complex system. Examples of areas of investigation particularly amenable to an integrative approach include ecological and physiological systems. The Rutgers' Center for Computational and Integrative Biology (CCIB) emphasizes the development of mathematical models for these biological systems, application of the models to data from laboratory and field investigations, the adjustment of the model based on its fit to and predictive value for experimental results and the subsequent modification of the experimental design based on the predictions of the model. Research DirectionsThe CCIB is comprise of over 40 nationally and internationally recognized scholars and researchers, many of whom have received prestigious awards and honors. The CCIB regularly receives research funding from the National Science Foundation (NSF) and the National Institutes of Health (NIH). Most recently, the CCIB has received a Major Research Instrumention (MRI) award from the NSF to construct a high-level computational cluster to support modeling projects. Some of the CCIB's current research directions include:
The CCIB is always interested in exploring new research directions and is happy to lend its computational expertise to external collaborators. Please contact us if you are interested in discussing current or potential projects. Scientific Working GroupsThe CCIB faculty have been actively developing internal collaborative efforts, which have further expanded with the advent of the new Graduate Program. A number of focal points of these efforts have served as a basis for the formation of interdisciplinary Scientific Working Groups (SWGs). The SWGs provide further formal structure for the CCIB and its research directions. The CCIB Scientific Working Groups include: Group 1 - Physiological The boundaries between the groups are not rigid; they define broad themes with possible overlaps. The SWGs represent the mechanism by which graduate students receive both peer and faculty mentorship and are exposed to multi-disciplinary research in biological signaling in different contextual/application areas. By combining faculty members from at least two different departments into thematic groups, the CCIB aims to foster research topics that will create linkages between diverse disciplines. This effort is reinforced through the graduate curriculum that serves to educate all CCIB graduate students with a basic understanding of the various topics related to biological signaling. Collaborative RelationshipsIn addition to our core and contributing faculty, the CCIB has a number of external collabortive relationships locally, nationally, and internationally. Collaboration with the CCIB takes many forms. Many of our partners provide summer placements for our Graduate Program. Other partners collaborate with our faculty through research, both academic and within industry. Finally, the CCIB offers instructional collaboration in the form of the CCIB seminar series, professional development workshops for practising researchers, and visiting scholar positions. Some of our current collaborative partners include:
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Recent PublicationsThe table below includes a selection of some of our faculty's recent publications.
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The Center for Computational and Integrative Biology (CCIB)
Rutgers,
The State University of New Jersey
Camden, NJ 08102 • (856) 225-1766
Copyright information page updated
05-Apr-2012
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