Session Introduction

This marks the first time that the Pacific Symposium in Biocomputing has hosted a session specifically devoted to the emerging computational needs of metabolomics. Metabolomics, or metabonomics as it is sometimes called, is a relatively new field of “omics” research concerned with the high-throughput identification and quantification of the small molecule metabolites in the metabolome (i.e. the complete complement of all small molecule metabolites found in a specific cell, organ or organism). It is a close counterpart to the genome, the transcriptome and the proteome. Together these four “omes” constitute the building blocks of systems biology. Even though metabolomics is primarily concerned with tracking and identifying chemicals as opposed to genes or proteins, it still shares many of the same computational needs with genomics, proteomics and transcriptomics. For instance, just like the other “omics” fields, metabolomics needs electronically accessible and searchable databases, it needs software to handle or process data from various highthroughput instruments such as NMR spectrometers or mass spectrometers, it needs laboratory information management systems (LIMS) to manage the data, and it needs software tools to predict or find information about metabolite properties, pathways, relationships or functions. These computational needs are just beginning to be addressed by members of the metabolomics community. As a result we believed that a PSB session devoted to this topic could address a number of important issues concerning both the emerging computational needs and the nascent computational trends in metabolomics. This year we solicited papers that focused specifically on describing novel methods for the acquisition, management and analysis of metabolomic data. We were particularly interested in papers that covered one of the five following topics: 1) metabolomics databases; 2) metabolomics LIMS; 3) spectral analysis tools for metabolomics; 4) medical or applied metabolomics