ArticleGenome medicine2014
Computational approaches to interpreting genomic sequence variation.
Article in Genome medicine, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
18 citing papers in PubMed.
- Pharmacogenomic landscape of TNF inhibitors in the Middle Eastern Qatari population.Frontiers in immunology · 2025Article
- Genetic Variants at PRKCG Splice and UTR Sites Promote Cancer Susceptibility by Disrupting Epigenetic and miRNA Regulatory Network.Journal of Cancer · 2024Article
- Role of non-coding variants in cardiovascular disease.Journal of cellular and molecular medicine · 2023Review
- Review
- A machine learning approach based on ACMG/AMP guidelines for genomic variant classification and prioritization.Scientific reports · 2022Article
- Clinical, Genetic and Functional Characterization of a NovelJournal of personalized medicine · 2022Article
- Conserved noncoding sequences provide insights into regulatory sequence and loss of gene expression in maize.Genome research · 2021Article
- Prediction of impacts of mutations on protein structure and interactions: SDM, a statistical approach, and mCSM, using machine learning.Protein science : a publication of the Protein Society · 2020Article
- Functional Assays Are Essential for Interpretation of Missense Variants Associated with Variable Expressivity.American journal of human genetics · 2018Article
- Clinical implications and considerations for evaluation of in silico algorithms for use with ACMG/AMP clinical variant interpretation guidelines.Genome medicine · 2017Article
- POSTAR: a platform for exploring post-transcriptional regulation coordinated by RNA-binding proteins.Nucleic acids research · 2017Article
- Reverse epitope mapping of the E2 glycoprotein in antibody associated hepatitis C virus.PloS one · 2017Article
- Mining the Unknown: Assigning Function to Noncoding Single Nucleotide Polymorphisms.Trends in genetics : TIG · 2017Review
- A Whole-Genome Analysis Framework for Effective Identification of Pathogenic Regulatory Variants in Mendelian Disease.American journal of human genetics · 2016Article
- KinMutRF: a random forest classifier of sequence variants in the human protein kinase superfamily.BMC genomics · 2016Article
- In Silico Functional Annotation of Genomic Variation.Current protocols in human genetics · 2016Review
- Recent Advances in the Molecular Genetics of Familial Hypertrophic Cardiomyopathy in South Asian Descendants.Frontiers in physiology · 2016Review
- The genetic landscape of cardiomyopathy and its role in heart failure.Cell metabolism · 2015Review
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Identifying sequence variants that play a mechanistic role in human disease and other phenotypes is a fundamental goal in human genetics and will be important in translating the results of variation studies. Experimental validation to confirm that a variant causes the biochemical changes responsible for a given disease or phenotype is considered the gold standard, but this cannot currently be applied to the 3 million or so variants expected in an individual genome. This has prompted the development of a wide variety of computational approaches that use several different sources of information to identify functional variation. Here, we review and assess the limitations of computational techniques for categorizing variants according to functional classes, prioritizing variants for experimental follow-up and generating hypotheses about the possible molecular mechanisms to inform downstream experiments. We discuss the main current bioinformatics approaches to identifying functional variation, including widely used algorithms for coding variation such as SIFT and PolyPhen and also novel techniques for interpreting variation across the genome.
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.