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Author(s): Vítor Santos Costa
Nuno A. Fonseca
Rui Camacho
Title: LogCHEM: interactive discriminative mining of chemical structure
Issue Date: 2008
Abstract: 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.
Subject: Engenharia do conhecimento, Tecnologia farmacêutica, Matemática
Knowledge engineering, Pharmaceutical technology, Mathematics
Scientific areas: Ciências exactas e naturais::Matemática
Natural sciences::Mathematics
Document Type: Artigo em Livro de Atas de Conferência Internacional
Rights: openAccess
Appears in Collections:FCUP - Artigo em Livro de Atas de Conferência Internacional
FEUP - Artigo em Livro de Atas de Conferência Internacional

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