The new biology and computational statistical physics


DOI: 10.1016/S0010-4655(02)00437-X

While it has historically been an exploratory, descriptive, and empirical science, in the past 100 years, biology has become more discovery- and mechanism-oriented. There are a number of ways in which this new paradigm is driving much of the current biological research toward statistical physics. This is happening at a molecular level due to the very large nature of biological molecules, such as proteins and nucleic acids. It is also occurring at the cellular level where random processes play an important role in cell function. There are even examples that describe the behavior of large numbers of individual organisms within one or more species. Finally, this trend has been accelerated with the advent of high-throughput experimental techniques that are driving biology towards information science. Analysis and discovery of the information gained from such experiments will rely heavily on techniques that have traditionally been applied in statistical physics. This paper will focus on examples of how statistical physics techniques are being applied and hope to be applied to biological problems, with an emphasis on high-performance computing. We will also speculate on what we feel are the necessary computing requirements to solve many of the outstanding problems in computational biology using the techniques that will be discussed. (C) 2002 Elsevier Science B.V. All rights reserved.

Return to Publications page