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Knowledge Discovery in Variant Databases Using Inductive Logic Programming
Understanding the effects of genetic variation on the phenotype of an individual is a major goal of biomedical research, especially for the development of diagnostics and effective therapeutic solutions. In this work, we describe the use of a recent knowledge discovery from database (KDD) approach u...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Libertas Academica
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3615990/ https://www.ncbi.nlm.nih.gov/pubmed/23589683 http://dx.doi.org/10.4137/BBI.S11184 |
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author | Nguyen, Hoan Luu, Tien-Dao Poch, Olivier Thompson, Julie D. |
author_facet | Nguyen, Hoan Luu, Tien-Dao Poch, Olivier Thompson, Julie D. |
author_sort | Nguyen, Hoan |
collection | PubMed |
description | Understanding the effects of genetic variation on the phenotype of an individual is a major goal of biomedical research, especially for the development of diagnostics and effective therapeutic solutions. In this work, we describe the use of a recent knowledge discovery from database (KDD) approach using inductive logic programming (ILP) to automatically extract knowledge about human monogenic diseases. We extracted background knowledge from MSV3d, a database of all human missense variants mapped to 3D protein structure. In this study, we identified 8,117 mutations in 805 proteins with known three-dimensional structures that were known to be involved in human monogenic disease. Our results help to improve our understanding of the relationships between structural, functional or evolutionary features and deleterious mutations. Our inferred rules can also be applied to predict the impact of any single amino acid replacement on the function of a protein. The interpretable rules are available at http://decrypthon.igbmc.fr/kd4v/. |
format | Online Article Text |
id | pubmed-3615990 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Libertas Academica |
record_format | MEDLINE/PubMed |
spelling | pubmed-36159902013-04-15 Knowledge Discovery in Variant Databases Using Inductive Logic Programming Nguyen, Hoan Luu, Tien-Dao Poch, Olivier Thompson, Julie D. Bioinform Biol Insights Original Research Understanding the effects of genetic variation on the phenotype of an individual is a major goal of biomedical research, especially for the development of diagnostics and effective therapeutic solutions. In this work, we describe the use of a recent knowledge discovery from database (KDD) approach using inductive logic programming (ILP) to automatically extract knowledge about human monogenic diseases. We extracted background knowledge from MSV3d, a database of all human missense variants mapped to 3D protein structure. In this study, we identified 8,117 mutations in 805 proteins with known three-dimensional structures that were known to be involved in human monogenic disease. Our results help to improve our understanding of the relationships between structural, functional or evolutionary features and deleterious mutations. Our inferred rules can also be applied to predict the impact of any single amino acid replacement on the function of a protein. The interpretable rules are available at http://decrypthon.igbmc.fr/kd4v/. Libertas Academica 2013-03-18 /pmc/articles/PMC3615990/ /pubmed/23589683 http://dx.doi.org/10.4137/BBI.S11184 Text en © 2013 the author(s), publisher and licensee Libertas Academica Ltd. This is an open access article. Unrestricted non-commercial use is permitted provided the original work is properly cited. |
spellingShingle | Original Research Nguyen, Hoan Luu, Tien-Dao Poch, Olivier Thompson, Julie D. Knowledge Discovery in Variant Databases Using Inductive Logic Programming |
title | Knowledge Discovery in Variant Databases Using Inductive Logic Programming |
title_full | Knowledge Discovery in Variant Databases Using Inductive Logic Programming |
title_fullStr | Knowledge Discovery in Variant Databases Using Inductive Logic Programming |
title_full_unstemmed | Knowledge Discovery in Variant Databases Using Inductive Logic Programming |
title_short | Knowledge Discovery in Variant Databases Using Inductive Logic Programming |
title_sort | knowledge discovery in variant databases using inductive logic programming |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3615990/ https://www.ncbi.nlm.nih.gov/pubmed/23589683 http://dx.doi.org/10.4137/BBI.S11184 |
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