PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Identifying interface elements implied in protein-protein interactions using statistical tests and Frequent Item Sets
Christine Martin and Antoine Cornuéjols
In: BIBM-08 (The IEEE International Conference on Bioinformatics and Biomedicine), 3-5 Nov 2008, Philadelphia, USA.

Abstract

Understanding what are the characteristics of protein-protein interfaces is at the core of numerous applications. This paper introduces a method in which the proteins are described with surfacic geometrical elements. Starting from a database of known interfaces, the method produces the elements and combinations thereof that are characteristic of the interfaces. This is done thanks to a frequent item set technique and the use of statistical tests to ensure a marked difference with a null hypothesis. This approach allows one to easily interpret the results, as compared to techniques that operate as ``black-boxes''. Furthermore, it is naturally adapted to discover disjunctive concepts, i.e. different underlying processes. The results obtained on a set of 459 protein-protein interfaces from the PDB database confirm that the findings are consistent with current knowledge about protein-protein interfaces.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
ID Code:5311
Deposited By:Antoine Cornuéjols
Deposited On:24 March 2009