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Open AccessJournal ArticleDOI

A new disease-specific machine learning approach for the prediction of cancer-causing missense variants

Emidio Capriotti, +1 more
- 01 Oct 2011 - 
- Vol. 98, Iss: 4, pp 310-317
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TLDR
A Support Vector Machine (SVM) classifier trained on a set of 3163 cancer-causing variants and an equal number of neutral polymorphisms is presented, which results in higher prediction accuracy and correlation coefficient in identifying cancer- Causing variants.
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This article is published in Genomics.The article was published on 2011-10-01 and is currently open access. It has received 75 citations till now. The article focuses on the topics: Single-nucleotide polymorphism.

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Journal ArticleDOI

UniRef clusters: a comprehensive and scalable alternative for improving sequence similarity searches

TL;DR: The results support the use of UniRef clusters as a comprehensive and scalable alternative to native sequence databases for similarity searches and reinforces its reliability for use in functional annotation.
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Predicting the functional, molecular, and phenotypic consequences of amino acid substitutions using hidden Markov models.

TL;DR: The Functional Analysis Through Hidden Markov Models (FATHMM) software and server is described: a species‐independent method with optional species‐specific weightings for the prediction of the functional effects of protein missense variants, demonstrating that FATHMM can be efficiently applied to high‐throughput/large‐scale human and nonhuman genome sequencing projects with the added benefit of phenotypic outcome associations.
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Applications of Support Vector Machine (SVM) Learning in Cancer Genomics.

TL;DR: The recent progress of SVMs in cancer genomic studies is reviewed and the strength of the SVM learning and its future perspective incancer genomic applications is comprehended.
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Identifying Mendelian disease genes with the Variant Effect Scoring Tool

TL;DR: The ability of an aggregate VEST gene score to identify candidate Mendelian disease genes, based on whole-exome sequencing of a small number of disease cases, demonstrates the potential power gain of aggregating bioinformatics variant scores into gene-level scores and the general utility of bio informatics in assisting the search for disease genes in large-scale exome sequencing studies.
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WS-SNPs&GO: a web server for predicting the deleterious effect of human protein variants using functional annotation

TL;DR: This work presents the web server implementation of SNPs&GO, a valuable tool that includes in a unique framework information derived from protein sequence, structure, evolutionary profile, and protein function.
References
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Journal ArticleDOI

Gapped BLAST and PSI-BLAST: a new generation of protein database search programs.

TL;DR: A new criterion for triggering the extension of word hits, combined with a new heuristic for generating gapped alignments, yields a gapped BLAST program that runs at approximately three times the speed of the original.
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Gene Ontology: tool for the unification of biology

TL;DR: The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing.
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The Pfam protein families database

TL;DR: The definition and use of family-specific, manually curated gathering thresholds are explained and some of the features of domains of unknown function (also known as DUFs) are discussed, which constitute a rapidly growing class of families within Pfam.
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Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls

Paul Burton, +195 more
- 07 Jun 2007 - 
TL;DR: This study has demonstrated that careful use of a shared control group represents a safe and effective approach to GWA analyses of multiple disease phenotypes; generated a genome-wide genotype database for future studies of common diseases in the British population; and shown that, provided individuals with non-European ancestry are excluded, the extent of population stratification in theBritish population is generally modest.
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A Map of Human Genome Variation From Population-Scale Sequencing

TL;DR: The 1000 Genomes Project aims to provide a deep characterization of human genome sequence variation as a foundation for investigating the relationship between genotype and phenotype as mentioned in this paper, and the results of the pilot phase of the project, designed to develop and compare different strategies for genomewide sequencing with high-throughput platforms.
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