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News Release

Last modified: Monday, May 12, 2003

James Glazier

BLOOMINGTON, Ind. -- As a result of the Human Genome Project, vast amounts of raw information are becoming available about the structure and behavior of our genes. To make sense out of this wealth of data, a new kind of scientist is needed.

The mission of the Indiana University Biocomplexity Institute is to produce these scientists.

"Biocomplexity is the study of the emergence of self-organized, complex behaviors from the interaction of many simple agents. Such emergent complexity is a hallmark of life, from the organization of molecules into cellular machinery, through the organization of cells into tissues, to the organization of individuals into communities. The other key element of biocomplexity is the unavoidable presence of multiple scales. Often, agents organize into much larger structures; those structures organize into much larger structures, etc.. A classic example is the primary, secondary, tertiary, and quaternary folding of DNA into chromosomes that allows a strand of a length of several centimeters to fold, without tangling or losing function, into a chromosome about one micron long. Biocomplexity is a methodology and philosophy as well as a field of study. It focuses on networks of interactions and the general rules governing such networks."

From 'Solving Life's Equations': "When organic molecules, cells, and organisms interact, they give rise to limitless variation and ever more complex structures. "Systems level" biology—how groups of simple agents or cells or organisms come together to exhibit complex behaviors—is the basis of biocomplexity, the study of these phenomena. To understand how a biological system works, a multidisciplinary approach is necessary. Electricity, chemistry, biology, and physics all come together to make a heart beat."

"Our long-term goal is to develop comprehensive multiscale models of cell and tissue organization and their relation to development. We will address three scales of structure starting from the subcellular level, and will include genetic control networks, protein networks, molecular machines and the cytoskeleton. At the cell level, we will emphasize cell polarity, cell migration and cell-cell interactions such as adhesion. At the supercellular level, our studies will include the aggregation of cells into tissues and tissues into organs."

"One main goal is to improve communication between biological, mathematical and physical scientists."

"Our goal is to educate scientists to combine a deep knowledge of biology with the mathematical, computational and physical sophistication needed to address the increasingly complex problems of post-Human-Genome-Project biology, particularly the patterns and behaviors that arise from the interactions of many autonomous agents (Knight Report, 2002)."

"We will approach this goal initially through three focused, interrelated projects that combine quantitative experiments and computer simulation. The three projects provide a unified and logical program for research in biocomplexity; they build on the mutually complementary strengths of the researchers at the universities in the consortium; and they will receive additional support from our collaborators at other institutions. The projects motivate and exploit intersecting projects in areas of outreach, bioinformatics and education.

Project 1 - Modeling biological networks at the molecular level, including gene regulation pathways, protein networks and intra- and inter-cell signaling networks.

Project 2 - Modeling the structure and function of the cytoskeleton, including transport and mechanical interactions in the cytoskeleton and the mechanical properties of cells.

Project 3 - Modeling organogenesis, including limb development, innervation, gastrulation and cardiovascular development, topics chosen to illustrate a broad variety of fundamental developmental mechanisms."

There is a need to translate biologists' qualitative models into quantitative models from which we can make predictions -- physicists are good at that.

"Post-genomic" biology

Typical experimentalist: "I'd much rather discover a new pathway than quantify a pathway that's already known." But soon all important pathways will be known, and we need to move past that to extract information from what is known.

"I do biology experiments in my laboratory, and I do physics experiments in my laboratory. I firmly straddle the fence."

He is about half computational and half experimental in biophysics. "I do not distinguish myself from biologists."

"It's easy to come up with a model that's beautiful but not relevant." Physicists have to be careful not to lose contact with the experimental side of biophysics because of that.

"That's why this kind of institute organization is so important. You have to convince people to work together. It's not small science anymore. It's not huge science in the sense that you need a particle accelerator, but it's not something that an individual can do by himself. The technology is too sophisticated, and there are too many issues that you have to address. Intellectually it's complicated, and you need different approaches to the same problem."

The place where mathematics, computation and experiment have come together the most is bioinformatics, for example looking at the genome and trying to understand what parts of the genome are junk and what parts are significant, where regulatory pathways are

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