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Grid Computing P40

Computational biology is undergoing a revolution from a traditionally compute-intensive science conducted by individuals and small research groups to a high-throughput, datadriven science conducted by teams working in both academia and industry. It is this new biology as a data-driven science in the era of Grid Computing that is the subject of this chapter. This chapter is written from the perspective of bioinformatics specialists who seek to fully capitalize on the promise of the Grid and who are working with computer scientists and technologists developing biological applications for the Grid. To understand what has been developed and what is proposed. | 40 The new biology and the Grid Kim Baldridge and Philip E. Bourne University of California San Diego California United States 40.1 INTRODUCTION Computational biology is undergoing a revolution from a traditionally compute-intensive science conducted by individuals and small research groups to a high-throughput data-driven science conducted by teams working in both academia and industry. It is this new biology as a data-driven science in the era of Grid Computing that is the subject of this chapter. This chapter is written from the perspective of bioinformatics specialists who seek to fully capitalize on the promise of the Grid and who are working with computer scientists and technologists developing biological applications for the Grid. To understand what has been developed and what is proposed for utilizing the Grid in the new biology era it is useful to review the first wave of computational biology application models. In the next section we describe the first wave of computational models used for computational biology and computational chemistry to date. 40.1.1 The first wave compute-driven biology applications The first computational models for biology and chemistry were developed for the classical von Neumann machine model that is for sequential scalar processors. With the Grid Computing - Making the Global Infrastructure a Reality. Edited by F. Berman A. Hey and G. Fox 2003 John Wiley Sons Ltd ISBN 0-470-85319-0 908 KIM BALDRIDGE AND PHILIP E. BOURNE emergence of parallel computing biological applications were developed that could take advantage of multiple processor architectures with distributed or shared memory and locally located disk space to execute a collection of tasks. Applications that compute molecular structure or electronic interactions of a protein fragment are examples of programs developed to take advantage of emerging computational technologies. As distributed memory parallel architectures became more prevalent computational biologists .