Evaluation of probabilistic and logical inference for a SNP annotation system
Autor: | Landon T. Detwiler, Terry H. Shen, Eithon Cadag, Peter Tarczy-Hornoch, Christopher S. Carlson |
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Rok vydání: | 2010 |
Předmět: |
Logic
Computer science Inference SNP annotation system Genome-wide association study Single-nucleotide polymorphism Health Informatics Computational biology computer.software_genre Polymorphism Single Nucleotide Article 03 medical and health sciences 0302 clinical medicine Logical conjunction Databases Genetic SNP evaluation 030304 developmental biology 0303 health sciences Models Statistical Single nucleotide polymorphisms (SNPs) Probabilistic logic Logical inference Computer Science Applications SNP annotation Federated data integration Probabilistic inference A priori and a posteriori Data mining computer 030217 neurology & neurosurgery Genome-Wide Association Study Data integration |
Zdroj: | Journal of Biomedical Informatics. 43(3):407-418 |
ISSN: | 1532-0464 |
DOI: | 10.1016/j.jbi.2009.12.002 |
Popis: | Genome wide association studies (GWAS) are an important approach to understanding the genetic mechanisms behind human diseases. Single nucleotide polymorphisms (SNPs) are the predominant markers used in genome wide association studies, and the ability to predict which SNPs are likely to be functional is important for both a priori and a posteriori analyses of GWA studies. This article describes the design, implementation and evaluation of a family of systems for the purpose of identifying SNPs that may cause a change in phenotypic outcomes. The methods described in this article characterize the feasibility of combinations of logical and probabilistic inference with federated data integration for both point and regional SNP annotation and analysis. Evaluations of the methods demonstrate the overall strong predictive value of logical, and logical with probabilistic, inference applied to the domain of SNP annotation. |
Databáze: | OpenAIRE |
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