ArticlePloS one2013
Prediction of disease causing non-synonymous SNPs by the Artificial Neural Network Predictor NetDiseaseSNP.
Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Deep Prior Framework: integrating functional specificity with general plausibility for targeted protein evolution.Briefings in bioinformatics · 2026Article
- Variant Impact Predictor database (VIPdb), version 2: trends from three decades of genetic variant impact predictors.Human genomics · 2024Article
- Variant Impact Predictor database (VIPdb), version 2: Trends from 25 years of genetic variant impact predictors.bioRxiv : the preprint server for biology · 2024Article
- Interpreting protein variant effects with computational predictors and deep mutational scanning.Disease models & mechanisms · 2022Review
- SOD1 mutations associated with amyotrophic lateral sclerosis analysis of variant severity.Scientific reports · 2022Article
- Refinement of coding SNPs in the human aryl hydrocarbon receptor gene using ISNPranker: An integrative-SNP ranking web-tool.Computational biology and chemistry · 2021Article
- Missense mutations in EDA and EDAR genes cause dominant syndromic tooth agenesis.Molecular genetics & genomic medicine · 2021Article
- Tumor somatic mutations also existing as germline polymorphisms may help to identify functional SNPs from genome-wide association studies.Carcinogenesis · 2020Article
- MARK4 protein can explore the active-like conformations in its non-phosphorylated state.Scientific reports · 2019Article
- VIPdb, a genetic Variant Impact Predictor Database.Human mutation · 2019Article
- KinMutRF: a random forest classifier of sequence variants in the human protein kinase superfamily.BMC genomics · 2016Article
- Unraveling the Deleterious Effects of Cancer-Driven STK11 Mutants Through Conformational Sampling Approach.Cancer informatics · 2016Article
- Integrative analysis of functional genomic annotations and sequencing data to identify rare causal variants via hierarchical modeling.Frontiers in genetics · 2015Article
- Computational and experimental approaches to reveal the effects of single nucleotide polymorphisms with respect to disease diagnostics.International journal of molecular sciences · 2014Review
- Gene-specific function prediction for non-synonymous mutations in monogenic diabetes genes.PloS one · 2014Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We have developed a sequence conservation-based artificial neural network predictor called NetDiseaseSNP which classifies nsSNPs as disease-causing or neutral. Our method uses the excellent alignment generation algorithm of SIFT to identify related sequences and a combination of 31 features assessing sequence conservation and the predicted surface accessibility to produce a single score which can be used to rank nsSNPs based on their potential to cause disease. NetDiseaseSNP classifies successfully disease-causing and neutral mutations. In addition, we show that NetDiseaseSNP discriminates cancer driver and passenger mutations satisfactorily. Our method outperforms other state-of-the-art methods on several disease/neutral datasets as well as on cancer driver/passenger mutation datasets and can thus be used to pinpoint and prioritize plausible disease candidates among nsSNPs for further investigation. NetDiseaseSNP is publicly available as an online tool as well as a web service: http://www.cbs.dtu.dk/services/NetDiseaseSNP.
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