GTB – an online genome tolerance browser

Background Accurate methods capable of predicting the impact of single nucleotide variants (SNVs) are assuming ever increasing importance. There exists a plethora of in silico algorithms designed to help identify and prioritize SNVs across the human genome for further investigation. However, no tool...

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Bibliographic Details
Published in:	BMC bioinformatics Vol. 18; no. 1; p. 20
Main Authors:	Shihab, Hashem A., Rogers, Mark F., Ferlaino, Michael, Campbell, Colin, Gaunt, Tom R.
Format:	Journal Article
Language:	English
Published:	London BioMed Central 06.01.2017 BioMed Central Ltd Springer Nature B.V
Subjects:	Algorithms Annotations Binding sites Bioinformatics Biomedical and Life Sciences Cancer Comparative genomics Computational Biology/Bioinformatics Computer Appl. in Life Sciences Databases, Genetic Funding Gene mutation Genome, Human Genomes Homeodomain Proteins - genetics Homeodomain Proteins - metabolism Humans Information management Internet Life Sciences Microarrays Models, Theoretical Mutation Neoplasms - diagnosis Neoplasms - genetics Receptors, LDL - genetics Receptors, LDL - metabolism Software Visualization Web Browser Web browsers Pathogenicity prediction Genome browser Genome tolerance Mutation Variant effect prediction SNVs Prediction algorithm
ISSN:	1471-2105, 1471-2105
Online Access:	Get full text
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