Formal Concept Analysis for the Interpretation of Relational Learning Applied on 3D Protein-binding Sites

Emmanuel Bresso, Renaud Grisoni, Marie-Dominique Devignes, Amedeo Napoli, Malika Smaïl-Tabbone

2012

Abstract

Inductive Logic Programming (ILP) is a powerful learning method which allows an expressive representation of the data and produces explicit knowledge in the form of a theory, i.e., a set of first-order logic rules. However, ILP systems suffer from a drawback as they return a single theory based on heuristic user-choices of various parameters, thus ignoring potentially relevant rules. Accordingly, we propose an original approach based on Formal Concept Analysis for effective interpretation of reached theories with the possibility of adding domain knowledge. Our approach is applied to the characterization of three-dimensional (3D) protein-binding sites which are the protein portions on which interactions with other proteins take place. In this context, we define a relational and logical representation of 3D patches and formalize the problem as a concept learning problem using ILP. We report here the results we obtained on a particular category of protein-binding sites namely phosphorylation sites using ILP followed by FCA-based interpretation.

Paper Citation

in Harvard Style

Bresso E., Grisoni R., Devignes M., Napoli A. and Smaïl-Tabbone M. (2012). Formal Concept Analysis for the Interpretation of Relational Learning Applied on 3D Protein-binding Sites . In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2012) ISBN 978-989-8565-29-7, pages 111-120. DOI: 10.5220/0004149901110120

in Bibtex Style

@conference{kdir12,
author={Emmanuel Bresso and Renaud Grisoni and Marie-Dominique Devignes and Amedeo Napoli and Malika Smaïl-Tabbone},
title={Formal Concept Analysis for the Interpretation of Relational Learning Applied on 3D Protein-binding Sites},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2012)},
year={2012},
pages={111-120},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004149901110120},
isbn={978-989-8565-29-7},
}

in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2012)
TI - Formal Concept Analysis for the Interpretation of Relational Learning Applied on 3D Protein-binding Sites
SN - 978-989-8565-29-7
AU - Bresso E.
AU - Grisoni R.
AU - Devignes M.
AU - Napoli A.
AU - Smaïl-Tabbone M.
PY - 2012
SP - 111
EP - 120
DO - 10.5220/0004149901110120