The automatic discovery of structural principles describing protein fold space.

Adrian P. Cootes*, Stephen H. Muggleton, M. J. Sternberg

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

24 Citations (Scopus)

Abstract

The study of protein structure has been driven largely by the careful inspection of experimental data by human experts. However, the rapid determination of protein structures from structural-genomics projects will make it increasingly difficult to analyse (and determine the principles responsible for) the distribution of proteins in fold space by inspection alone. Here, we demonstrate a machine-learning strategy that automatically determines the structural principles describing 45 folds. The rules learnt were shown to be both statistically significant and meaningful to protein experts. With the increasing emphasis on high-throughput experimental initiatives, machine-learning and other automated methods of analysis will become increasingly important for many biological problems.

Original languageEnglish
Pages (from-to)839-850
Number of pages12
JournalJournal of molecular biology
Volume330
Issue number4
Publication statusPublished - 18 Jul 2003

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