Title: Developing a Logical Model of Yeast Metabolism
Authors: Philip G.K. Reiser, Ross D. King, Douglas B. Kell, Stephen H. Muggleton, Christopher H. Bryant, and Stephen G. Oliver
Series: Linköping Electronic Articles in Computer and Information Science
ISSN 1401-9841
Issue: Vol. 6 (2001), No. 024
URL: http://www.ep.liu.se/ea/cis/2001/024/

Abstract: With the completion of the sequencing of genomes of an increasing number of organisms, the focus of biology is moving to determining the role of these genes (functional genomics). To this end it is useful to view the cell as a biochemical machine: it consumes simple molecules to manufacture more complex ones by chaining together biochemical reactions into long sequences referred to as metabolic pathways. Such metabolic pathways are not linear but often intersect to form a complex network. Genes play a fundamental role in this network by synthesising the enzymes that catalyse biochemical reactions. Although developing a complete model of metabolism is of fundamental importance to biology and medicine, the size and complexity of the network has proven beyond the capacity of human reasoning. This paper presents intermediate results in the Robot Scientist research programme that aims to discover the function of genes in the metabolism of the yeast Saccharomyces cerevisiae. Results include: (1) the first logical model of metabolism; (2) a method to predict phenotype by deductive inference; and (3) a method to infer reactions and gene function by abductive inference. We describe the in vivo experimental set-up which will allow these in silico inferences to be automatically tested by a laboratory robot.

Original publication
2001-08-30
Postscript Checksum