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The increasing power and sophistication of laboratory computers over the past 15-20 years has placed many scientific disciplines in a position to incorporate formal mathematical analyses and computer modeling techniques into their methodologies. At the same time, there has been a growing interest among mathematicians, physicists, computer scientists, and engineers in the complex systems and databases of the life sciences. The resulting natural alliance of biologists with mathematicians, physicists, computer scientists, and engineers has led to the emergence of the rapidly growing and highly interdisciplinary field of Quantitative Biology (see Selected References, below). The importance of this new field is underscored by several new initiatives from federal funding agencies that support interdisciplinary, quantitative research in areas such as neurobiology, bioinformatics/functional genomics, animal behavior, ecology, and evolutionary physiology.

In recognition of these developments, Ohio University has established the Quantitative Biology Institute (QBI) in December, 2000.

Mission and Goals


The mission of the Quantitative Biology Institute is to stimulate and focus interdisciplinary research and training efforts in Quantitative Biology at Ohio University.  Our goals are to: 1) catalyze basic and applied research collaborations between life scientists and researchers in the more quantitative fields of Mathematics, Physics, Computer Science and Engineering, 2) enhance undergraduate education and research opportunities in Quantitative Biology, 3) provide graduate education and career preparation in Quantitative Biology and 4) increase awareness and understanding of Quantitative Biology in the larger community.




The Quantitative Biology Institute provides a rich environment for interdisciplinary research collaborations. An important component of the research mission of the Institute is to catalyze research collaborations between biologists and researchers in the traditionally more quantitative fields of Mathematics, Physics, Computer Science, and Engineering. Each of these individual disciplines has its own distinct intellectual history, culture, and methods of identifying and solving problems of interest. Successful collaboration between these disciplines will require individuals to learn not only new methods, but also new ways of thinking about traditional subjects. These changes can only come about through extensive interactions designed to foster an interdisciplinary perspective. The Institute provides a venue for these interdisciplinary interactions at Ohio University through a variety of formal and informal interactions.

A key component of the research mission is the extension of our interdisciplinary collaborations into the areas of graduate and undergraduate education. This integration of research and education not only provides unique training opportunities for students, but also fits the agendas of a number of funding agencies that view training of graduate and undergraduate students as an extension of their research mission.

Graduate Training

The Quantitative Biology Institute provides unique opportunities for interdisciplinary graduate undergraduate education. Students with undergraduate degrees in physics, mathematics or engineering who want to pursue graduate studies in biology often lack the biological background to be considered for admission by ordinary Biology departments. Students with traditional Biology degrees who want to formally pursue more quantitative interests in mathematics, physics, computer science, or engineering face similar problems.

The Quantitative Biology Institute provides such students an academic program that allows them to develop the necessary interdisciplinary expertise. Students have the option of entering the Graduate programs of individual participating departments, or entering the Individual Interdisciplinary Program (IIP) at either the master's or doctoral level. Students admitted into the IIP are able to tailor their course of study to suit their individual interests.

Undergraduate Education

The Institute oversees undergraduate preparation in Quantitative Biology. Students at this level have the option of pursuing double majors, for example in Biology and Physics or Computer Science, or developing an individualized 4-year program through one of two mechanisms.

The Honors Tutorial College offers a highly flexible alternative to the standard curriculum by replacing lectures with one-on-one tutorials in the students major. This program is available for students majoring in Biological Sciences, Computer Science, Engineering Physics, Mathematics, or Physics.

In addition, University College offers a Bachelor of Specialized Studies program that allows students to combine elements of available curricula to create a unique and individualized program of study.

All students being trained in Quantitative Biology at Ohio University will receive significant amounts of hands-on research experience as part of their education.


Institute faculty hold academic appointments in participating departments: Biological Sciences, Mathematics, and Physics and Astronomy.

Selected References

“Math & Bio 2010 Linking Undergraduate Disciplines,”  LA Steen (ed), The Mathematical Association of America, 2005.

Cohen JE (2004) Mathematics is biology’s next microscope, only better; biology is mathematics’ next physics, only better. PLoS Biol 2(12): e439.

“Introductory Science and Mathematics Education for 21st-century Biologists,” W. Bialek and D. Botstein. Science 303:788-790, 2004.

“Educating Future Scientists,” NS Sung et al., Science 301:1485, 2003.

Hastings A, Arzberger P, Bolker B, Ives T, Johnson N et al. (2003) Quantitative biology for the 21st century.  Available:


Hastings A, Palmer MA (2003) A bright future for biologists and mathematicians? Science 299:2003-2004.


Palmer MA, Arzberger P, Cohen JE, Hastings A, Holt RD et al. (2003) Accelerating mathematical-biological linkages.  Report available at

 “Tackling the challenges of interdisciplinary bioscience,” J. McCarthy, Nature Reviews in Molecular Cell Biology, 5:933-937, 2004.

“Uses and abuses of mathematics in biology,” RM May, Science 303:790-793, 2004.

“Understanding biological complexity:  lessons from the past,” JN Weiss et al., FASEB Journal, 17:1-6, 2003.

“Making sense of complex phenomena in biology,” PK Maini, Novartis Foundation symposium 247:53-59; discussion 60-65, 84-90, 244-252, 2002.

"The Bioinformatics Gold Rush," Scientific American July, 2000, p. 58-64

"Bioinformatics in the information age," Science 287:1221 February 20, 2000.

"The Human Genome Business Today," Scientific American July, 2000 p. 50-55

"US universities create bridges between physics and biology," Nature 397:3 January 7, 1999.

"Bioinformatics boom," The Scientist 12(24):17 December 7, 1998.

"NIH urged to fund centers to merge computing and biology," Science 284:1742 June 11, 1999.

"Interdisciplinary research 'being stifled'," Nature 396:202 November 19, 1998.

"Profile: Smashing through Science's Glass Ceiling" (A profile of the new NSF head Rita Colwell and views on biocomplexity), Scientific American December 1998 p. 36.

"Mathematical and computational challenges in population biology and ecosystems science", Science 275:334 January 17, 1997.

"Biologists put on mathematical glasses," Science 274:2039 December 20, 1996.

"Hot property: biologists who compute," Science 272:1730 June 21, 1996.



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