tailieunhanh - Báo cáo khoa học: Metabolomics, modelling and machine learning in systems biology – towards an understanding of the languages of cells

The newly emerging field of systems biology involves a judicious interplay between high-throughput ‘wet’ experimentation, computational modelling and technology development, coupled to the world of ideas and theory. This interplay involves iterative cycles, such that systems biology is not at all confined to hypothesis-dependent studies, with intelligent, principled, hypothesis-generating studies being of high importance and consequently very far from aimless fishing expeditions. | FEBS Journal THE THEODOR BUCHER LECTURE Metabolomics modelling and machine learning in systems biology - towards an understanding of the languages of cells Delivered on 3 July 2005 at the 30th FEBS Congress and 9th IUBMB conference in Budapest Douglas B. Kell1 2 1 Schoolof Chemistry Faraday Building The University of Manchester UK 2 Manchester Centre for Integrative Systems Biology Manchester Interdisciplinary Biocentre UK Keywords hypothesis generation genetic programming evolutionary computing signal processing elements technology development systems biology Correspondence . Kell Schoolof Chemistry University of Manchester Faraday Building Sackville Street Manchester M60 1QD UK Tel 44 161 3064492 E-mail dbk@ Website http http http Received 15 November 2005 revised 7 January 2006 accepted 16 January 2006 doi The newly emerging field of systems biology involves a judicious interplay between high-throughput wet experimentation computational modelling and technology development coupled to the world of ideas and theory. This interplay involves iterative cycles such that systems biology is not at all confined to hypothesis-dependent studies with intelligent principled hypothesis-generating studies being of high importance and consequently very far from aimless fishing expeditions. I seek to illustrate each of these facets. Novel technology development in metabolomics can increase substantially the dynamic range and number of metabolites that one can detect and these can be exploited as disease markers and in the consequent and principled generation of hypotheses that are consistent with the data and achieve this in a value-free manner. Much of classical biochemistry and signalling pathway analysis has concentrated on the analyses of changes in the concentrations of intermediates with local equations -such as that of Michaelis and Menten v Vmax S S Km - that describe .