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Träfflista för sökning "WFRF:(Muggleton Stephen H.) "

Search: WFRF:(Muggleton Stephen H.)

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1.
  • Reiser, Philip G.K., et al. (author)
  • Developing a Logical Model of Yeast Metabolism
  • 2001
  • Reports (other academic/artistic)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.
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2.
  • Turcotte, Marcel, et al. (author)
  • Use of Inductive Logic Programming to Learn Principles of Protein Structure
  • 2000
  • Reports (other academic/artistic)abstract
    • Inductive logic programming (ILP) has been applied to learn rules which characterize protein folds. Several representations for the background set have been explored and the results have been interpreted in their biological context. In this paper, we present new results obtained with a background set containing information about protein topology. The new rules are more descriptive than the previous ones, {\em i.e.} where previous rules represented local motifs, often associated with functional regions, the new rules represent more complete descriptions, often similar to the descriptions found in SCOP. Cross-validation experiments were conducted for the 20 most populated folds. The overall cross-validated accuracy was found to be 75.1 +- 1.6 % for the more limited background knowledge, and 82.1 +- 1.4 % with additional information.
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  • Result 1-2 of 2

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