{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,12]],"date-time":"2026-04-12T19:49:37Z","timestamp":1776023377288,"version":"3.50.1"},"reference-count":136,"publisher":"Oxford University Press (OUP)","license":[{"start":{"date-parts":[[2020,2,4]],"date-time":"2020-02-04T00:00:00Z","timestamp":1580774400000},"content-version":"vor","delay-in-days":34,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004359","name":"Vetenskapsr\u00e5det","doi-asserted-by":"publisher","award":["VR 2015-02510"],"award-info":[{"award-number":["VR 2015-02510"]}],"id":[{"id":"10.13039\/501100004359","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002794","name":"Swedish Cancer Society","doi-asserted-by":"publisher","award":["CAN 2017\/699"],"award-info":[{"award-number":["CAN 2017\/699"]}],"id":[{"id":"10.13039\/501100002794","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61602332"],"award-info":[{"award-number":["61602332"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,1,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Development of new computational methods and testing their performance has to be carried out using experimental data. Only in comparison to existing knowledge can method performance be assessed. For that purpose, benchmark datasets with known and verified outcome are needed. High-quality benchmark datasets are valuable and may be difficult, laborious and time consuming to generate. VariBench and VariSNP are the two existing databases for sharing variation benchmark datasets used mainly for variation interpretation. They have been used for training and benchmarking predictors for various types of variations and their effects. VariBench was updated with 419 new datasets from 109 papers containing altogether 329\u2009014\u2009152 variants; however, there is plenty of redundancy between the datasets. VariBench is freely available at http:\/\/structure.bmc.lu.se\/VariBench\/. The contents of the datasets vary depending on information in the original source. The available datasets have been categorized into 20 groups and subgroups. There are datasets for insertions and deletions, substitutions in coding and non-coding region, structure mapped, synonymous and benign variants. Effect-specific datasets include DNA regulatory elements, RNA splicing, and protein property for aggregation, binding free energy, disorder and stability. Then there are several datasets for molecule-specific and disease-specific applications, as well as one dataset for variation phenotype effects. Variants are often described at three molecular levels (DNA, RNA and protein) and sometimes also at the protein structural level including relevant cross references and variant descriptions. The updated VariBench facilitates development and testing of new methods and comparison of obtained performances to previously published methods. We compared the performance of the pathogenicity\/tolerance predictor PON-P2 to several benchmark studies, and show that such comparisons are feasible and useful, however, there may be limitations due to lack of provided details and shared data.<\/jats:p>\n                  <jats:p>Database URL: http:\/\/structure.bmc.lu.se\/VariBench<\/jats:p>","DOI":"10.1093\/database\/baz117","type":"journal-article","created":{"date-parts":[[2019,9,4]],"date-time":"2019-09-04T15:26:54Z","timestamp":1567610814000},"source":"Crossref","is-referenced-by-count":43,"title":["Variation benchmark datasets: update, criteria, quality and applications"],"prefix":"10.1093","volume":"2020","author":[{"given":"Anasua","family":"Sarkar","sequence":"first","affiliation":[{"name":"Department of Experimental Medical Science, BMC B13, Lund University, SE-22 184 Lund, Sweden"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yang","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Soochow University, No1. Shizi Street, Suzhou, 215006 Jiangsu, China"},{"name":"Provincial Key Laboratory for Computer Information Processing Technology, No1. Shizi Street, Soochow University, Suzhou, 215006 Jiangsu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mauno","family":"Vihinen","sequence":"additional","affiliation":[{"name":"Department of Experimental Medical Science, BMC B13, Lund University, SE-22 184 Lund, Sweden"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2020,2,4]]},"reference":[{"key":"2020020405325725300_ref1","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1002\/humu.22204","article-title":"VariBench: a benchmark database for variations","volume":"34","author":"Nair","year":"2013","journal-title":"Hum. Mutat."},{"key":"2020020405325725300_ref2","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1002\/humu.22727","article-title":"VariSNP, a benchmark database for variations from dbSNP","volume":"36","author":"Schaafsma","year":"2015","journal-title":"Hum. Mutat."},{"key":"2020020405325725300_ref3","doi-asserted-by":"crossref","first-page":"308","DOI":"10.1093\/nar\/29.1.308","article-title":"dbSNP: the NCBI database of genetic variation","volume":"29","author":"Sherry","year":"2001","journal-title":"Nucleic Acids Res."},{"key":"2020020405325725300_ref4","doi-asserted-by":"crossref","first-page":"160018","DOI":"10.1038\/sdata.2016.18","article-title":"The FAIR guiding principles for scientific data management and stewardship","volume":"3","author":"Wilkinson","year":"2016","journal-title":"Sci. Data"},{"key":"2020020405325725300_ref5","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1038\/nmeth.2890","article-title":"MutationTaster2: mutation prediction for the deep-sequencing age","volume":"11","author":"Schwarz","year":"2014","journal-title":"Nat. Methods"},{"key":"2020020405325725300_ref6","doi-asserted-by":"crossref","first-page":"461","DOI":"10.1186\/s12859-018-2478-6","article-title":"Representativeness of variation benchmark datasets","volume":"19","author":"Schaafsma","year":"2018","journal-title":"BMC Bioinformatics"},{"key":"2020020405325725300_ref7","doi-asserted-by":"crossref","first-page":"553","DOI":"10.1093\/protein\/gzp030","article-title":"Assessing computational methods for predicting protein stability upon mutation: good on average but not in the details","volume":"22","author":"Potapov","year":"2009","journal-title":"Protein Eng. Des. Sel."},{"key":"2020020405325725300_ref8","doi-asserted-by":"crossref","first-page":"675","DOI":"10.1002\/humu.21242","article-title":"Performance of protein stability predictors","volume":"31","author":"Khan","year":"2010","journal-title":"Hum. Mutat."},{"key":"2020020405325725300_ref9","doi-asserted-by":"crossref","first-page":"358","DOI":"10.1002\/humu.21445","article-title":"Performance of mutation pathogenicity prediction methods on missense variants","volume":"32","author":"Thusberg","year":"2011","journal-title":"Hum. Mutat."},{"key":"2020020405325725300_ref10","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0117380","article-title":"PON-P2: prediction method for fast and reliable identification of harmful variants","volume":"10","author":"Niroula","year":"2015","journal-title":"PLoS One"},{"key":"2020020405325725300_ref11","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pcbi.1003440","article-title":"PredictSNP: robust and accurate consensus classifier for prediction of disease-related mutations","volume":"10","author":"Bendl","year":"2014","journal-title":"PLoS Comput. Biol."},{"key":"2020020405325725300_ref12","doi-asserted-by":"crossref","first-page":"1012","DOI":"10.1002\/humu.23048","article-title":"The complementarity between protein-specific and general pathogenicity predictors for amino acid substitutions","volume":"37","author":"Riera","year":"2016","journal-title":"Hum. Mutat."},{"key":"2020020405325725300_ref13","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pcbi.1004725","article-title":"Towards increasing the clinical relevance of in silico methods to predict pathogenic missense variants","volume":"12","author":"Masica","year":"2016","journal-title":"PLoS Comput. Biol."},{"key":"2020020405325725300_ref14","first-page":"1013","article-title":"The evaluation of tools used to predict the impact of missense variants is hindered by two types of circularity","volume":"37","author":"Grimm","year":"2015","journal-title":"Hum. Mutat."},{"key":"2020020405325725300_ref15","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1186\/1471-2164-10-122","article-title":"Prediction of disease-related mutations affecting protein localization","volume":"10","author":"Laurila","year":"2009","journal-title":"BMC Genomics"},{"key":"2020020405325725300_ref16","doi-asserted-by":"crossref","first-page":"794","DOI":"10.1002\/humu.22564","article-title":"Performance of protein disorder prediction programs on amino acid substitutions","volume":"35","author":"Ali","year":"2014","journal-title":"Hum. Mutat."},{"key":"2020020405325725300_ref17","doi-asserted-by":"crossref","first-page":"2032","DOI":"10.1093\/bioinformatics\/btw066","article-title":"PON-sol: prediction of effects of amino acid substitutions on protein solubility","volume":"32","author":"Yang","year":"2016","journal-title":"Bioinformatics"},{"key":"2020020405325725300_ref18","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pcbi.1006481","article-title":"How good are pathogenicity predictors in detecting benign variants?","volume":"15","author":"Niroula","year":"2019","journal-title":"PLoS Comput. Biol."},{"key":"2020020405325725300_ref19","doi-asserted-by":"crossref","DOI":"10.1186\/s12864-019-5865-0","article-title":"Benchmarking membrane proteins: subcellular localization and variant tolerance predictors","author":"Orioli","year":"2019","journal-title":"BMC Genomics"},{"key":"2020020405325725300_ref20","first-page":"1","article-title":"Bioinformatics identification of splice site signals and prediction of mutation effects","author":"Desmet","year":"2010","journal-title":"Res. Adv. Nucleic Acids Res"},{"key":"2020020405325725300_ref21","doi-asserted-by":"crossref","first-page":"13534","DOI":"10.1093\/nar\/gku1206","article-title":"In silico prediction of splice-altering single nucleotide variants in the human genome","volume":"42","author":"Jian","year":"2014","journal-title":"Nucleic Acids Res."},{"key":"2020020405325725300_ref22","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1038\/s41525-018-0044-9","article-title":"A phenotype centric benchmark of variant prioritisation tools","volume":"3","author":"Anderson","year":"2018","journal-title":"NPJ Genom. Med."},{"key":"2020020405325725300_ref23","doi-asserted-by":"crossref","first-page":"549","DOI":"10.1002\/humu.22976","article-title":"Human Variome project quality assessment criteria for variation databases","volume":"37","author":"Vihinen","year":"2016","journal-title":"Hum. Mutat."},{"key":"2020020405325725300_ref24","doi-asserted-by":"crossref","first-page":"D1079","DOI":"10.1093\/nar\/gku1071","article-title":"Genenames.org: the HGNC resources in 2015","volume":"43","author":"Gray","year":"2015","journal-title":"Nucleic Acids Res."},{"key":"2020020405325725300_ref25","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1002\/(SICI)1098-1004(200001)15:1<7::AID-HUMU4>3.0.CO;2-N","article-title":"Mutation nomenclature extensions and suggestions to describe complex mutations: a discussion","volume":"15","author":"Dunnen","year":"2000","journal-title":"Hum. Mutat."},{"key":"2020020405325725300_ref26","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1186\/gm145","article-title":"Locus reference genomic sequences: an improved basis for describing human DNA variants","volume":"2","author":"Dalgleish","year":"2010","journal-title":"Genome Med."},{"key":"2020020405325725300_ref27","doi-asserted-by":"crossref","first-page":"594","DOI":"10.1093\/nar\/gky1234","article-title":"RefSeq curation and annotation of stop codon recoding in vertebrates","volume":"47","author":"Rajput","year":"2019","journal-title":"Nucleic Acids Res."},{"key":"2020020405325725300_ref28","doi-asserted-by":"crossref","first-page":"356","DOI":"10.1101\/gr.157495.113","article-title":"Variation ontology for annotation of variation effects and mechanisms","volume":"24","author":"Vihinen","year":"2014","journal-title":"Genome Res."},{"key":"2020020405325725300_ref29","doi-asserted-by":"crossref","first-page":"D204","DOI":"10.1093\/nar\/gkj103","article-title":"ProTherm and ProNIT: thermodynamic databases for proteins and protein-nucleic acid interactions","volume":"34","author":"Kumar","year":"2006","journal-title":"Nucleic Acids Res."},{"key":"2020020405325725300_ref30","article-title":"PON-tstab: protein variant stability predictor. Importance of training data quality","volume":"19","author":"Yang","year":"2018","journal-title":"Int. J. Mol. Sci."},{"issue":"Suppl 4","key":"2020020405325725300_ref31","doi-asserted-by":"crossref","first-page":"S2","DOI":"10.1186\/1471-2164-13-S4-S2","article-title":"How to evaluate performance of prediction methods? Measures and their interpretation in variation effect analysis","volume":"13","author":"Vihinen","year":"2012","journal-title":"BMC Genomics"},{"key":"2020020405325725300_ref32","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1002\/humu.22253","article-title":"Guidelines for reporting and using prediction tools for genetic variation analysis","volume":"34","author":"Vihinen","year":"2013","journal-title":"Hum. Mutat."},{"key":"2020020405325725300_ref33","doi-asserted-by":"crossref","first-page":"831","DOI":"10.1093\/bib\/bbv082","article-title":"Correct machine learning on protein sequences: a peer-reviewing perspective","volume":"17","author":"Walsh","year":"2016","journal-title":"Brief. Bioinform."},{"key":"2020020405325725300_ref34","doi-asserted-by":"crossref","first-page":"579","DOI":"10.1002\/humu.22987","article-title":"Variation interpretation predictors: principles, types, performance, and choice","volume":"37","author":"Niroula","year":"2016","journal-title":"Hum. Mutat."},{"key":"2020020405325725300_ref35","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1002\/humu.23144","article-title":"How to define pathogenicity, health, and disease?","volume":"38","author":"Vihinen","year":"2017","journal-title":"Hum. Mutat."},{"key":"2020020405325725300_ref36","doi-asserted-by":"crossref","first-page":"357","DOI":"10.1002\/humu.23173","article-title":"Predicting severity of disease-causing variants","volume":"38","author":"Niroula","year":"2017","journal-title":"Hum. Mutat."},{"key":"2020020405325725300_ref37","doi-asserted-by":"crossref","first-page":"1908","DOI":"10.1093\/hmg\/ddu607","article-title":"Missense variants in CFTR nucleotide-binding domains predict quantitative phenotypes associated with cystic fibrosis disease severity","volume":"24","author":"Masica","year":"2015","journal-title":"Hum. Mol. Genet."},{"key":"2020020405325725300_ref38","doi-asserted-by":"crossref","first-page":"3395","DOI":"10.1093\/bioinformatics\/btv375","article-title":"AmyLoad: website dedicated to amyloidogenic protein fragments","volume":"31","author":"Wozniak","year":"2015","journal-title":"Bioinformatics"},{"key":"2020020405325725300_ref39","doi-asserted-by":"crossref","first-page":"1698","DOI":"10.1093\/bioinformatics\/btv027","article-title":"WALTZ-DB: a benchmark database of amyloidogenic hexapeptides","volume":"31","author":"Beerten","year":"2015","journal-title":"Bioinformatics"},{"key":"2020020405325725300_ref40","doi-asserted-by":"crossref","first-page":"4630","DOI":"10.1093\/nar\/gkl535","article-title":"Aberrant 3\u2032 splice sites in human disease genes: mutation pattern, nucleotide structure and comparison of computational tools that predict their utilization","volume":"34","author":"Vo\u0159echovsk\u00fd","year":"2006","journal-title":"Nucleic Acids Res."},{"key":"2020020405325725300_ref41","doi-asserted-by":"crossref","first-page":"4250","DOI":"10.1093\/nar\/gkm402","article-title":"Aberrant 5\u2032 splice sites in human disease genes: mutation pattern, nucleotide structure and comparison of computational tools that predict their utilization","volume":"35","author":"Buratti","year":"2007","journal-title":"Nucleic Acids Res."},{"key":"2020020405325725300_ref42","article-title":"SKEMPI 2.0: an updated benchmark of changes in protein-protein binding energy, kinetics and thermodynamics upon mutation","author":"Jankauskaite","year":"2018","journal-title":"Bioinformatics"},{"key":"2020020405325725300_ref43","doi-asserted-by":"crossref","first-page":"435","DOI":"10.1002\/humu.20166","article-title":"KinMutBase: a registry of disease-causing mutations in protein kinase domains","volume":"25","author":"Ortutay","year":"2005","journal-title":"Hum. Mutat."},{"key":"2020020405325725300_ref44","doi-asserted-by":"crossref","first-page":"bau104","DOI":"10.1093\/database\/bau104","article-title":"Kin-driver: a database of driver mutations in protein kinases","volume":"2014","author":"Simonetti","year":"2014","journal-title":"Database (Oxford)"},{"key":"2020020405325725300_ref45","doi-asserted-by":"crossref","DOI":"10.1093\/bib\/bby105","article-title":"dbCPM: a manually curated database for exploring the cancer passenger mutations","author":"Yue","year":"2018","journal-title":"Brief. Bioinform."},{"key":"2020020405325725300_ref46","doi-asserted-by":"crossref","first-page":"806","DOI":"10.1038\/nmeth.4000","article-title":"DoCM: a database of curated mutations in cancer","volume":"13","author":"Ainscough","year":"2016","journal-title":"Nat. Methods"},{"key":"2020020405325725300_ref47","article-title":"OncoKB: a Precision Oncology Knowledge Base","volume":"2017","author":"Chakravarty","journal-title":"JCO Precis. Oncol."},{"key":"2020020405325725300_ref48","doi-asserted-by":"crossref","first-page":"761","DOI":"10.1093\/bioinformatics\/btu703","article-title":"DANN: a deep learning approach for annotating the pathogenicity of genetic variants","volume":"31","author":"Quang","year":"2015","journal-title":"Bioinformatics"},{"key":"2020020405325725300_ref49","doi-asserted-by":"crossref","first-page":"7793","DOI":"10.1093\/nar\/gky678","article-title":"Performance evaluation of pathogenicity-computation methods for missense variants","volume":"46","author":"Li","year":"2018","journal-title":"Nucleic Acids Res."},{"key":"2020020405325725300_ref50","doi-asserted-by":"crossref","first-page":"405","DOI":"10.1038\/gim.2015.30","article-title":"Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology","volume":"17","author":"Richards","year":"2015","journal-title":"Genet. Med."},{"key":"2020020405325725300_ref51","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1186\/s13059-017-1353-5","article-title":"Evaluation of in silico algorithms for use with ACMG\/AMP clinical variant interpretation guidelines","volume":"18","author":"Ghosh","year":"2017","journal-title":"Genome Biol."},{"key":"2020020405325725300_ref52","doi-asserted-by":"crossref","first-page":"569","DOI":"10.1186\/s12864-017-3914-0","article-title":"Development of pathogenicity predictors specific for variants that do not comply with clinical guidelines for the use of computational evidence","volume":"18","author":"Campa","year":"2017","journal-title":"BMC Genomics"},{"key":"2020020405325725300_ref53","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1038\/ejhg.2016.129","article-title":"Improving the in silico assessment of pathogenicity for compensated variants","volume":"25","author":"Azevedo","year":"2016","journal-title":"Eur. J. Hum. Genet."},{"key":"2020020405325725300_ref54","doi-asserted-by":"crossref","first-page":"531","DOI":"10.1186\/s12859-017-1947-7","article-title":"PON-SC - program for identifying steric clashes caused by amino acid substitutions","volume":"18","author":"Calyseva","year":"2017","journal-title":"BMC Bioinformatics"},{"key":"2020020405325725300_ref55","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0171355","article-title":"Impact of genetic variation on three dimensional structure and function of proteins","volume":"12","author":"Bhattacharya","year":"2017","journal-title":"PLoS One"},{"key":"2020020405325725300_ref56","doi-asserted-by":"crossref","first-page":"2020","DOI":"10.1093\/nar\/gkw046","article-title":"PON-mt-tRNA: a multifactorial probability-based method for classification of mitochondrial tRNA variations","volume":"44","author":"Niroula","year":"2016","journal-title":"Nucleic Acids Res."},{"key":"2020020405325725300_ref57","doi-asserted-by":"crossref","first-page":"W127","DOI":"10.1093\/nar\/gky375","article-title":"Kinact: a computational approach for predicting activating missense mutations in protein kinases","volume":"46","author":"Rodrigues","year":"2018","journal-title":"Nucleic Acids Res."},{"issue":"Suppl 4","key":"2020020405325725300_ref58","doi-asserted-by":"crossref","first-page":"S3","DOI":"10.1186\/1471-2164-13-S4-S3","article-title":"Prioritization of pathogenic mutations in the protein kinase superfamily","volume":"13","author":"Izarzugaza","year":"2012","journal-title":"BMC Genomics"},{"key":"2020020405325725300_ref59","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1016\/j.ygeno.2007.03.006","article-title":"Distribution analysis of nonsynonymous polymorphisms within the human kinase gene family","volume":"90","author":"Torkamani","year":"2007","journal-title":"Genomics"},{"key":"2020020405325725300_ref60","doi-asserted-by":"crossref","first-page":"638","DOI":"10.1002\/humu.22791","article-title":"Characterization of all possible single nucleotide change \u2013caused amino acid substitutions in the kinase domain of Bruton tyrosine kinase","volume":"36","author":"V\u00e4liaho","year":"2015","journal-title":"Hum. Mutat."},{"key":"2020020405325725300_ref61","doi-asserted-by":"crossref","first-page":"1128","DOI":"10.1002\/humu.22900","article-title":"Classification of amino acid substitutions in mismatch repair proteins using PON-MMR2","volume":"36","author":"Niroula","year":"2015","journal-title":"Hum. Mutat."},{"key":"2020020405325725300_ref62","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1186\/s12881-015-0176-z","article-title":"Assessment of the predictive accuracy of five in silico prediction tools, alone or in combination, and two metaservers to classify long QT syndrome gene mutations","volume":"16","author":"Leong","year":"2015","journal-title":"BMC Med. Genet."},{"key":"2020020405325725300_ref63","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1016\/j.ajhg.2011.01.011","article-title":"Development and validation of a computational method for assessment of missense variants in hypertrophic cardiomyopathy","volume":"88","author":"Jordan","year":"2011","journal-title":"Am. J. Hum. Genet."},{"key":"2020020405325725300_ref64","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1186\/s12920-015-0125-x","article-title":"Harmful somatic amino acid substitutions affect key pathways in cancers","volume":"8","author":"Niroula","year":"2015","journal-title":"BMC Med. Genomics"},{"key":"2020020405325725300_ref65","doi-asserted-by":"crossref","first-page":"484","DOI":"10.1186\/s13059-014-0484-1","article-title":"Benchmarking mutation effect prediction algorithms using functionally validated cancer-related missense mutations","volume":"15","author":"Martelotto","year":"2014","journal-title":"Genome Biol."},{"key":"2020020405325725300_ref66","doi-asserted-by":"crossref","first-page":"W514","DOI":"10.1093\/nar\/gkx367","article-title":"Exploring background mutational processes to decipher cancer genetic heterogeneity","volume":"45","author":"Goncearenco","year":"2017","journal-title":"Nucleic Acids Res."},{"key":"2020020405325725300_ref67","first-page":"450","article-title":"Systematic functional annotation of somatic mutations in cancer. Cancer Cell","author":"Ng","year":"2018"},{"key":"2020020405325725300_ref68","article-title":"An optimized prediction framework to assess the functional impact of pharmacogenetic variants","author":"Zhou","year":"2018","journal-title":"Pharmacogenomics J."},{"key":"2020020405325725300_ref69","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0203553","article-title":"A Bayesian framework for efficient and accurate variant prediction","volume":"13","author":"Qian","year":"2018","journal-title":"PLoS One"},{"key":"2020020405325725300_ref70","doi-asserted-by":"crossref","first-page":"1570","DOI":"10.1038\/ng.3700","article-title":"Prospective functional classification of all possible missense variants in PPARG","volume":"48","author":"Majithia","year":"2016","journal-title":"Nat. Genet."},{"key":"2020020405325725300_ref71","doi-asserted-by":"crossref","first-page":"1085","DOI":"10.1002\/humu.23199","article-title":"PON-P and PON-P2 predictor performance in CAGI challenges: lessons learned","volume":"38","author":"Niroula","year":"2017","journal-title":"Hum. Mutat."},{"key":"2020020405325725300_ref72","doi-asserted-by":"crossref","DOI":"10.1002\/humu.23868","article-title":"Assessing computational predictions of the phenotypic effect of cystathionine-beta-synthase variants","author":"Kasak","year":"2019","journal-title":"Hum. Mutat."},{"key":"2020020405325725300_ref73","doi-asserted-by":"crossref","first-page":"4164","DOI":"10.1073\/pnas.1715896115","article-title":"Structural dynamics is a determinant of the functional significance of missense variants","volume":"115","author":"Ponzoni","year":"2018","journal-title":"Proc. Natl. Acad. Sci. U. S. A."},{"key":"2020020405325725300_ref74","doi-asserted-by":"crossref","first-page":"1599","DOI":"10.1093\/bioinformatics\/btu862","article-title":"DDIG-in: detecting disease-causing genetic variations due to frameshifting indels and nonsense mutations employing sequence and structural properties at nucleotide and protein levels","volume":"31","author":"Folkman","year":"2015","journal-title":"Bioinformatics"},{"key":"2020020405325725300_ref75","article-title":"ENTPRISE-X: predicting disease-associated frameshift and nonsense mutations","volume":"13","author":"Zhou","year":"2018","journal-title":"PLoS One"},{"key":"2020020405325725300_ref76","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1186\/1471-2105-15-111","article-title":"A comprehensive study of small non-frameshift insertions\/deletions in proteins and prediction of their phenotypic effects by a machine learning method (KD4i)","volume":"15","author":"Bermejo-Das-Neves","year":"2014","journal-title":"BMC Bioinformatics"},{"key":"2020020405325725300_ref77","article-title":"SIFT Indel: predictions for the functional effects of amino acid insertions\/deletions in proteins","volume":"8","author":"Hu","year":"2013","journal-title":"PLoS One"},{"key":"2020020405325725300_ref78","doi-asserted-by":"crossref","first-page":"1536","DOI":"10.1093\/bioinformatics\/btv009","article-title":"An integrative approach to predicting the functional effects of non-coding and coding sequence variation","volume":"31","author":"Shihab","year":"2015","journal-title":"Bioinformatics"},{"key":"2020020405325725300_ref79","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1186\/1479-7364-8-11","article-title":"Ranking non-synonymous single nucleotide polymorphisms based on disease concepts","volume":"8","author":"Shihab","year":"2014","journal-title":"Hum. Genomics"},{"key":"2020020405325725300_ref80","doi-asserted-by":"crossref","first-page":"2501","DOI":"10.1093\/nar\/gkw120","article-title":"Robust classification of protein variation using structural modelling and large-scale data integration","volume":"44","author":"Baugh","year":"2016","journal-title":"Nucleic Acids Res."},{"key":"2020020405325725300_ref81","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0192829","article-title":"Generalising better: applying deep learning to integrate deleteriousness prediction scores for whole-exome SNV studies","volume":"13","author":"Korvigo","year":"2018","journal-title":"PLoS One"},{"key":"2020020405325725300_ref82","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1186\/1471-2105-12-14","article-title":"Predicting disease-associated substitution of a single amino acid by analyzing residue interactions","volume":"12","author":"Li","year":"2011","journal-title":"BMC Bioinformatics"},{"key":"2020020405325725300_ref83","doi-asserted-by":"crossref","first-page":"2692","DOI":"10.1016\/j.jmb.2014.04.026","article-title":"SuSPect: enhanced prediction of single amino acid variant (SAV) phenotype using network features","volume":"426","author":"Yates","year":"2014","journal-title":"J. Mol. Biol."},{"key":"2020020405325725300_ref84","doi-asserted-by":"crossref","first-page":"10393","DOI":"10.1093\/nar\/gkx730","article-title":"MAPPIN: a method for annotating, predicting pathogenicity and mode of inheritance for nonsynonymous variants","volume":"45","author":"Gosalia","year":"2017","journal-title":"Nucleic Acids Res."},{"key":"2020020405325725300_ref85","doi-asserted-by":"crossref","first-page":"2125","DOI":"10.1093\/hmg\/ddu733","article-title":"Comparison and integration of deleteriousness prediction methods for nonsynonymous SNVs in whole exome sequencing studies","volume":"24","author":"Dong","year":"2015","journal-title":"Hum. Mol. Genet."},{"key":"2020020405325725300_ref86","doi-asserted-by":"crossref","first-page":"W247","DOI":"10.1093\/nar\/gkx369","article-title":"PhD-SNPg: a webserver and lightweight tool for scoring single nucleotide variants","volume":"45","author":"Capriotti","year":"2017","journal-title":"Nucleic Acids Res."},{"key":"2020020405325725300_ref87","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pcbi.1004962","article-title":"PredictSNP2: a unified platform for accurately evaluating SNP effects by exploiting the different characteristics of variants in distinct genomic regions","volume":"12","author":"Bendl","year":"2016","journal-title":"PLoS Comput. Biol."},{"key":"2020020405325725300_ref88","doi-asserted-by":"crossref","first-page":"1914","DOI":"10.1093\/bioinformatics\/btw086","article-title":"dbDSM: a manually curated database for deleterious synonymous mutations","volume":"32","author":"Wen","year":"2016","journal-title":"Bioinformatics"},{"key":"2020020405325725300_ref89","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1186\/s12920-018-0455-6","article-title":"Computational identification of deleterious synonymous variants in human genomes using a feature-based approach","volume":"12","author":"Shi","year":"2019","journal-title":"BMC Med. Genomics"},{"key":"2020020405325725300_ref90","doi-asserted-by":"crossref","first-page":"595","DOI":"10.1016\/j.ajhg.2016.07.005","article-title":"A whole-genome analysis framework for effective identification of pathogenic regulatory variants in Mendelian disease","volume":"99","author":"Smedley","year":"2016","journal-title":"Am. J. Hum. Genet."},{"issue":"Suppl 8","key":"2020020405325725300_ref91","doi-asserted-by":"crossref","first-page":"S3","DOI":"10.1186\/1471-2164-16-S8-S3","article-title":"Disease-associated variants in different categories of disease located in distinct regulatory elements","volume":"16","author":"Ma","year":"2015","journal-title":"BMC Genomics"},{"key":"2020020405325725300_ref92","doi-asserted-by":"crossref","first-page":"1183","DOI":"10.1002\/humu.21559","article-title":"Prediction of functional regulatory SNPs in monogenic and complex disease","volume":"32","author":"Zhao","year":"2011","journal-title":"Hum. Mutat."},{"key":"2020020405325725300_ref93","first-page":"2307","article-title":"Quantifying deleterious effects of regulatory variants","volume":"45","author":"Li","year":"2017","journal-title":"Nucleic Acids Res."},{"key":"2020020405325725300_ref94","doi-asserted-by":"crossref","first-page":"333","DOI":"10.1038\/s41588-018-0062-7","article-title":"The human noncoding genome defined by genetic diversity","volume":"50","author":"Iulio","year":"2018","journal-title":"Nat. Genet."},{"key":"2020020405325725300_ref95","doi-asserted-by":"crossref","first-page":"236","DOI":"10.1038\/s41467-017-00141-2","article-title":"Annotating pathogenic non-coding variants in genic regions","volume":"8","author":"Gelfman","year":"2017","journal-title":"Nat. Commun."},{"key":"2020020405325725300_ref96","doi-asserted-by":"crossref","DOI":"10.7717\/peerj.5742","article-title":"ShapeGTB: the role of local DNA shape in prioritization of functional variants in human promoters with machine learning","volume":"6","author":"Malkowska","year":"2018","journal-title":"PeerJ"},{"key":"2020020405325725300_ref97","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1186\/s13059-019-1634-2","article-title":"NCBoost classifies pathogenic non-coding variants in Mendelian diseases through supervised learning on purifying selection signals in humans","volume":"20","author":"Caron","year":"2019","journal-title":"Genome Biol."},{"key":"2020020405325725300_ref98","doi-asserted-by":"crossref","first-page":"1228","DOI":"10.1002\/humu.22101","article-title":"Guidelines for splicing analysis in molecular diagnosis derived from a set of 327 combined in silico\/in vitro studies on BRCA1 and BRCA2 variants","volume":"33","author":"Houdayer","year":"2012","journal-title":"Hum. Mutat."},{"key":"2020020405325725300_ref99","doi-asserted-by":"crossref","first-page":"e67","DOI":"10.1093\/nar\/gkp215","article-title":"Human splicing finder: an online bioinformatics tool to predict splicing signals","volume":"37","author":"Desmet","year":"2009","journal-title":"Nucleic Acids Res."},{"key":"2020020405325725300_ref100","doi-asserted-by":"crossref","first-page":"R19","DOI":"10.1186\/gb-2014-15-1-r19","article-title":"MutPred splice: machine learning-based prediction of exonic variants that disrupt splicing","volume":"15","author":"Mort","year":"2014","journal-title":"Genome Biol."},{"key":"2020020405325725300_ref101","first-page":"557","article-title":"Prediction of mutant mRNA splice isoforms by information theory-based exon definition","volume":"34","author":"Mucaki","year":"2013","journal-title":"Hum. Mutat."},{"key":"2020020405325725300_ref102","doi-asserted-by":"crossref","first-page":"975","DOI":"10.1002\/humu.20765","article-title":"Evaluation of in silico splice tools for decision-making in molecular diagnosis","volume":"29","author":"Houdayer","year":"2008","journal-title":"Hum. Mutat."},{"key":"2020020405325725300_ref103","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1016\/j.ymgme.2008.12.014","article-title":"Effects of intronic mutations in the LDLR gene on pre-mRNA splicing: comparison of wet-lab and bioinformatics analyses","volume":"96","author":"Holla","year":"2009","journal-title":"Mol. Genet. Metab."},{"key":"2020020405325725300_ref104","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1002\/humu.20811","article-title":"Intronic variants in BRCA1 and BRCA2 that affect RNA splicing can be reliably selected by splice-site prediction programs","volume":"30","author":"Vreeswijk","year":"2009","journal-title":"Hum. Mutat."},{"key":"2020020405325725300_ref105","doi-asserted-by":"crossref","first-page":"1052","DOI":"10.1038\/ejhg.2011.100","article-title":"Contribution of bioinformatics predictions and functional splicing assays to the interpretation of unclassified variants of the BRCA genes","volume":"19","author":"Thery","year":"2011","journal-title":"Eur. J. Hum. Genet."},{"key":"2020020405325725300_ref106","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0057173","article-title":"Comparative in vitro and in silico analyses of variants in splicing regions of BRCA1 and BRCA2 genes and characterization of novel pathogenic mutations","volume":"8","author":"Colombo","year":"2013","journal-title":"PLoS One"},{"key":"2020020405325725300_ref107","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0089570","article-title":"Exon first nucleotide mutations in splicing: evaluation of in silico prediction tools","volume":"9","author":"Grodecka","year":"2014","journal-title":"PLoS One"},{"key":"2020020405325725300_ref108","doi-asserted-by":"crossref","first-page":"5614058","DOI":"10.1155\/2016\/5614058","article-title":"Evaluation of bioinformatic programmes for the analysis of variants within splice site consensus regions","volume":"2016","author":"Tang","year":"2016","journal-title":"Adv Bioinformatics"},{"key":"2020020405325725300_ref109","doi-asserted-by":"crossref","first-page":"5389","DOI":"10.1021\/acs.jpcb.7b11367","article-title":"Flex ddG: Rosetta ensemble-based estimation of changes in protein-protein binding affinity upon mutation","volume":"122","author":"Barlow","year":"2018","journal-title":"J. Phys. Chem. B."},{"key":"2020020405325725300_ref110","doi-asserted-by":"crossref","first-page":"W306","DOI":"10.1093\/nar\/gki375","article-title":"I-Mutant2. 0: predicting stability changes upon mutation from the protein sequence or structure","volume":"33","author":"Capriotti","year":"2005","journal-title":"Nucleic Acids Res."},{"key":"2020020405325725300_ref111","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1002\/bip.20462","article-title":"Average assignment method for predicting the stability of protein mutants","volume":"82","author":"Saraboji","year":"2006","journal-title":"Biopolymers"},{"key":"2020020405325725300_ref112","doi-asserted-by":"crossref","first-page":"1292","DOI":"10.1093\/bioinformatics\/btm100","article-title":"iPTREE-STAB: interpretable decision tree based method for predicting protein stability changes upon mutations","volume":"23","author":"Huang","year":"2007","journal-title":"Bioinformatics"},{"issue":"Suppl 2","key":"2020020405325725300_ref113","doi-asserted-by":"crossref","first-page":"S6","DOI":"10.1186\/1471-2105-9-S2-S6","article-title":"A three-state prediction of single point mutations on protein stability changes","volume":"9","author":"Capriotti","year":"2008","journal-title":"BMC Bioinformatics"},{"key":"2020020405325725300_ref114","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1186\/1471-2105-12-151","article-title":"PoPMuSiC 2. 1: a web server for the estimation of protein stability changes upon mutation and sequence optimality","volume":"12","author":"Dehouck","year":"2011","journal-title":"BMC Bioinformatics"},{"key":"2020020405325725300_ref115","doi-asserted-by":"crossref","first-page":"664","DOI":"10.1093\/bioinformatics\/bts005","article-title":"Predicting folding free energy changes upon single point mutations","volume":"28","author":"Zhang","year":"2012","journal-title":"Bioinformatics"},{"key":"2020020405325725300_ref116","doi-asserted-by":"crossref","first-page":"847","DOI":"10.1007\/s00726-012-1407-7","article-title":"Structure-based prediction of the effects of a missense variant on protein stability","volume":"44","author":"Yang","year":"2013","journal-title":"Amino Acids"},{"key":"2020020405325725300_ref117","doi-asserted-by":"crossref","first-page":"1394","DOI":"10.1016\/j.jmb.2016.01.012","article-title":"EASE-MM: sequence-based prediction of mutation-induced stability changes with feature-based multiple models","volume":"428","author":"Folkman","year":"2016","journal-title":"J. Mol. Biol."},{"key":"2020020405325725300_ref118","doi-asserted-by":"crossref","DOI":"10.1038\/srep23257","article-title":"Predicting protein thermal stability changes upon point mutations using statistical potentials: introducing HoTMuSiC","volume":"6","author":"Pucci","year":"2016","journal-title":"Sci. Rep."},{"key":"2020020405325725300_ref119","doi-asserted-by":"crossref","first-page":"512","DOI":"10.3390\/ijms17040512","article-title":"SAAFEC: predicting the effect of single point mutations on protein folding free energy using a knowledge-modified MM\/PBSA approach","volume":"17","author":"Getov","year":"2016","journal-title":"Int. J. Mol. Sci."},{"key":"2020020405325725300_ref120","doi-asserted-by":"crossref","first-page":"2936","DOI":"10.1093\/bioinformatics\/btw361","article-title":"STRUM: structure-based prediction of protein stability changes upon single-point mutation","volume":"32","author":"Quan","year":"2016","journal-title":"Bioinformatics"},{"key":"2020020405325725300_ref121","doi-asserted-by":"crossref","first-page":"14349","DOI":"10.1074\/jbc.M117.784165","article-title":"Computational tools help improve protein stability but with a solubility tradeoff","volume":"292","author":"Broom","year":"2017","journal-title":"J. Biol. Chem."},{"key":"2020020405325725300_ref122","doi-asserted-by":"crossref","first-page":"2002","DOI":"10.1093\/bioinformatics\/btn353","article-title":"Accurate prediction of stability changes in protein mutants by combining machine learning with structure based computational mutagenesis","volume":"24","author":"Masso","year":"2008","journal-title":"Bioinformatics"},{"key":"2020020405325725300_ref123","doi-asserted-by":"crossref","first-page":"335","DOI":"10.1093\/bioinformatics\/btt691","article-title":"mCSM: predicting the effects of mutations in proteins using graph-based signatures","volume":"30","author":"Pires","year":"2014","journal-title":"Bioinformatics"},{"key":"2020020405325725300_ref124","doi-asserted-by":"crossref","DOI":"10.1093\/bioinformatics\/bty348","article-title":"Quantification of biases in predictions of protein stability changes upon mutations","author":"Pucci","year":"2018","journal-title":"Bioinformatics"},{"key":"2020020405325725300_ref125","doi-asserted-by":"crossref","first-page":"14116","DOI":"10.1073\/pnas.202485799","article-title":"A simple physical model for binding energy hot spots in protein-protein complexes","volume":"99","author":"Kortemme","year":"2002","journal-title":"Proc. Natl. Acad. Sci. U. S. A."},{"key":"2020020405325725300_ref126","doi-asserted-by":"crossref","first-page":"830","DOI":"10.1002\/prot.22921","article-title":"Role of conformational sampling in computing mutation-induced changes in protein structure and stability","volume":"79","author":"Kellogg","year":"2011","journal-title":"Proteins"},{"key":"2020020405325725300_ref127","doi-asserted-by":"crossref","first-page":"2181","DOI":"10.1093\/bioinformatics\/btp370","article-title":"Reliable prediction of protein thermostability change upon double mutation from amino acid sequence","volume":"25","author":"Huang","year":"2009","journal-title":"Bioinformatics"},{"key":"2020020405325725300_ref128","doi-asserted-by":"crossref","first-page":"2918","DOI":"10.1093\/bioinformatics\/btm437","article-title":"Accurate prediction of deleterious protein kinase polymorphisms","volume":"23","author":"Torkamani","year":"2007","journal-title":"Bioinformatics"},{"key":"2020020405325725300_ref129","doi-asserted-by":"crossref","first-page":"969","DOI":"10.1089\/cmb.2016.0058","article-title":"PTENpred: a designer protein impact predictor for PTEN-related disorders","volume":"23","author":"Johnston","year":"2016","journal-title":"J. Comput. Biol."},{"key":"2020020405325725300_ref130","doi-asserted-by":"crossref","first-page":"1029","DOI":"10.1038\/gim.2015.208","article-title":"Establishing the precise evolutionary history of a gene improves prediction of disease-causing missense mutations","volume":"18","author":"Adebali","year":"2016","journal-title":"Genet. Med."},{"key":"2020020405325725300_ref131","doi-asserted-by":"crossref","first-page":"709","DOI":"10.1002\/cpt.1020","article-title":"Gene-specific variant classifier (DPYD-Varifier) to identify deleterious alleles of dihydropyrimidine dehydrogenase","volume":"104","author":"Shrestha","year":"2018","journal-title":"Clin. Pharmacol. Ther."},{"key":"2020020405325725300_ref132","doi-asserted-by":"crossref","first-page":"572","DOI":"10.1016\/j.ejmg.2017.08.005","article-title":"BRCA1\/2 missense mutations and the value of in-silico analyses","volume":"60","author":"Sadowski","year":"2017","journal-title":"Eur. J. Med. Genet."},{"key":"2020020405325725300_ref133","doi-asserted-by":"crossref","first-page":"4023","DOI":"10.1016\/j.jmb.2013.07.037","article-title":"A gene-specific method for predicting hemophilia-causing point mutations","volume":"425","author":"Hamasaki-Katagiri","year":"2013","journal-title":"J. Mol. Biol."},{"key":"2020020405325725300_ref134","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1186\/1755-8794-7-47","article-title":"MutaCYP: classification of missense mutations in human cytochromes P450","volume":"7","author":"Fechter","year":"2014","journal-title":"BMC Med. Genomics"},{"key":"2020020405325725300_ref135","doi-asserted-by":"crossref","first-page":"2181","DOI":"10.1093\/bioinformatics\/btr365","article-title":"KvSNP: accurately predicting the effect of genetic variants in voltage-gated potassium channels","volume":"27","author":"Stead","year":"2011","journal-title":"Bioinformatics"},{"key":"2020020405325725300_ref136","doi-asserted-by":"crossref","first-page":"450","DOI":"10.1016\/j.ccell.2018.01.021","article-title":"Systematic functional annotation of somatic mutations in cancer","volume":"33","author":"Ng","year":"2018","journal-title":"Cancer Cell"}],"container-title":["Database"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/academic.oup.com\/database\/article-pdf\/doi\/10.1093\/database\/baz117\/32322837\/baz117.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"http:\/\/academic.oup.com\/database\/article-pdf\/doi\/10.1093\/database\/baz117\/32322837\/baz117.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,2,4]],"date-time":"2020-02-04T05:33:44Z","timestamp":1580794424000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/database\/article\/doi\/10.1093\/database\/baz117\/5710862"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,1,1]]},"references-count":136,"URL":"https:\/\/doi.org\/10.1093\/database\/baz117","relation":{"has-preprint":[{"id-type":"doi","id":"10.1101\/634766","asserted-by":"object"}]},"ISSN":["1758-0463"],"issn-type":[{"value":"1758-0463","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2020]]},"published":{"date-parts":[[2020,1,1]]},"article-number":"baz117"}}