Molecules, Magnets, and Mathematics

ited audience, a useful companion to other computa-biologists (and others) with only minimal mathematical training. tional biology books currently available. Parts of the The authors develop the idea that complexity arises book read quite well although, given its nature, it gets when the behavior of a system is not given simply by quite dense in places. This is an exciting time to move the sum of its parts. An essential ingredient in such into the field of computational molecular biology, moti-systems is nonlinearity, and it is often useful to talk vate others to move into this field, or simply keep an about phenomena that " emerge " at a higher level of eye on the practical developments emerging from this structure as a consequence of interactions between in-rapidly evolving field. Reading all or parts of this book dividual components. Some relatively simple physical can help meet some of these goals. systems provide a useful starting point for showing the Computational Molecular Biology is the first in a series power of mathematical tools for describing such emer-of books on computational biology published by the MIT gent phenomena. After reviewing some of these, the Press. Additional titles forthcoming within the next year book moves on to illustrate how mathematical models or two include Computational Modeling of Genetic and can provide insight into biological systems from the Biochemical Networks; Gene Regulation and Metabo-molecular level to cellular, organismic, and finally social lism: Post-Genomic Computational Approaches; Cur-and cultural level. By the end one is left with a strong rent Topics in Computational Biology; Comparative Ge-sense that there really are coherent themes that charac-nomics: The Domains of Life; and The Handbook of terize complexity across many biological systems at Computational Molecular Biology and Bioinformatics. many levels of analysis. This is a series worth watching for anyone interested in A classic example of complexity emerging from simple the growing field of computational biology. underlying components is the Ising model of the magne-tization of iron. Each iron atom acts as a miniature mag-Fran Lewitter net that can line up one way or the other, and a macro-Whitehead Institute scopic block of iron is magnetic when the majority of 9 Cambridge Center atoms are lined up in the same direction. Iron atoms Cambridge, Massachusetts 02142 exert forces on each other, tending to cause each atom to become lined up with other atoms nearby. At high temperatures, these forces are …