LogCHEM: interactive discriminative mining of chemical structure

• Type: Article in International Conference Proceedings Book
• Date: 2008

Authors

Vítor Santos Costa (Author) FCUP; Nuno A. Fonseca (Author) Other; Rui Camacho (Author) FEUP

Conference proceedings International

Title: 2008 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE, PROCEEDINGS

Pages: 421-426

IEEE International Conference on Bioinformatics and Biomedicine

Philadelphia, PA, NOV 03-05, 2008

Indexing

ISI Web of Knowledge - 3 Citations

Scopus - 3 Citations

INSPEC

Scientific classification

FOS: Natural sciences > Mathematics

CORDIS: Technological sciences > Engineering > Knowledge engineering ; Technological sciences > Technology > Pharmaceutical technology

Other information

Authenticus ID: P-004-5AB

DOI: 10.1109/bibm.2008.45

Abstract (EN): One of the most well known successes of Inductive Logic Programming (ILP) is on Structure-Activity Relationship (SAR) problems. In such problems, ILP has proved several times to be capable of constructing expert comprehensible models that hell) to explain the activity of chemical compounds based on their structure and properties. However, despite its successes on SAR problems, ILP has severe scalability problems that prevent its application oil larger datasets. In this paper we present LogCHEM, an ILP based tool for discriminative interactive mining of chemical fragments. LogCHEM tackles ILP's scalability issues in the context of SAR applications. We show that LogCHEM benefits from the flexibility of ILP both by its ability to quickly extend the original mining model, and by its ability, to interface with external tools. Furthermore, We demonstrate that LogCHEM can be used to mine effectively large chemoinformatics datasets, namely, several datasets from EPA's DSSTox database and on a dataset based on the DTP AIDS anti-viral screen.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 6