A method and server for predicting damaging missense mutations.

SIFT: predicting amino acid changes that affect protein function

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Human non-synonymous SNPs: server and survey

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Predicting the insurgence of human genetic diseases associated to single point protein mutations with support vector machines and evolutionary information

Capriotti, E., Calabrese, R., & Casadio, R. (2006) · Bioinformatics · doi:10.1093/bioinformatics/btl423 · Cited by 940 · see citing works

SNPs3D: Candidate gene and SNP selection for association studies

Yue, P., Melamud, E., & Moult, J. (2006) · BMC Bioinformatics · doi:10.1186/1471-2105-7-166 · Cited by 460 · see citing works

SNAP predicts effect of mutations on protein function

Bromberg, Y., Yachdav, G., & Rost, B. (2008) · Bioinformatics · doi:10.1093/bioinformatics/btn435 · Cited by 262 · see citing works

Hypermutable Non-Synonymous Sites Are under Stronger Negative Selection

Schmidt, S., Gerasimova, A. V., Kondrashov, F. A., Adzhubei, I. A., Kondrashov, A. S., & Sunyaev, S. R. (2008) · PLoS Genetics · doi:10.1371/journal.pgen.1000281 · Cited by 34 · see citing works

Correction: Hypermutable Non-Synonymous Sites Are under Stronger Negative Selection

Schmidt, S., Gerasimova, A. V., Kondrashov, F. A., Adzhubei, I. A., Kondrashov, A. S., & Sunyaev, S. R. (2008) · PLoS Genetics · doi:10.1371/annotation/a81b1fab-890c-447b-a308-5bc8ca3eb21d · Cited by 10 · see citing works

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

Richards, S., Aziz, N., Bale, S., Bick, D., Das, S., Gastier-Foster, J., Grody, W. W., Hegde, M., Lyon, E., Spector, E., et al. (2015) · Genetics in Medicine · doi:10.1038/gim.2015.30 · Cited by 32,594 · see citing works

The Phyre2 web portal for protein modeling, prediction and analysis

Kelley, L. A., Mezulis, S., Yates, C. M., Wass, M. N., & Sternberg, M. J. E. (2015) · Nature Protocols · doi:10.1038/nprot.2015.053 · Cited by 9,652 · see citing works

The Ensembl Variant Effect Predictor

McLaren, W., Gil, L., Hunt, S. E., Riat, H. S., Ritchie, G. R. S., Thormann, A., Flicek, P., & Cunningham, F. (2016) · Genome Biology · doi:10.1186/s13059-016-0974-4 · Cited by 8,099 · see citing works

Mutational landscape determines sensitivity to PD-1 blockade in non–small cell lung cancer

Rizvi, N. A., Hellmann, M. D., Snyder, A., Kvistborg, P., Makarov, V., Havel, J. J., Lee, W., Yuan, J., Wong, P., Ho, T. S., et al. (2015) · Science · doi:10.1126/science.aaa1348 · Cited by 7,802 · see citing works

A general framework for estimating the relative pathogenicity of human genetic variants

Kircher, M., Witten, D. M., Jain, P., O'Roak, B. J., Cooper, G. M., & Shendure, J. (2014) · Nature Genetics · doi:10.1038/ng.2892 · Cited by 6,183 · see citing works

Genetic studies of body mass index yield new insights for obesity biology

Study, T. L. C., Locke, A. E., The ADIPOGen Consortium, The AGEN-BMI Working Group, The CARDIOGRAMplusC4D Consortium, The CKDGen Consortium, The, G. L. G. C., The, I. C. B. P., The MAGIC Investigators, The MuTHER Consortium, et al. (2015) · Nature · doi:10.1038/nature14177 · Cited by 4,534 · see citing works

Predicting Functional Effect of Human Missense Mutations Using PolyPhen‐2

Adzhubei, I., Jordan, D. M., & Sunyaev, S. R. (2013) · Current Protocols in Human Genetics · doi:10.1002/0471142905.hg0720s76 · Cited by 3,705 · see citing works

CADD: predicting the deleteriousness of variants throughout the human genome

Rentzsch, P., Witten, D., Cooper, G. M., Shendure, J., & Kircher, M. (2019) · Nucleic Acids Research · doi:10.1093/nar/gky1016 · Cited by 3,534 · see citing works

<i>TREM2</i> Variants in Alzheimer's Disease

Guerreiro, R., Wojtas, A., Bras, J., Carrasquillo, M., Rogaeva, E., Majounie, E., Cruchaga, C., Sassi, C., Kauwe, J. S. K., Younkin, S., et al. (2013) · New England Journal of Medicine · doi:10.1056/nejmoa1211851 · Cited by 3,020 · see citing works

MutationTaster evaluates disease-causing potential of sequence alterations

Schwarz, J. M., Rödelsperger, C., Schuelke, M., & Seelow, D. (2010) · Nature Methods · doi:10.1038/nmeth0810-575 · Cited by 2,975 · see citing works

Genetic meta-analysis of diagnosed Alzheimer’s disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing

Alzheimer Disease Genetics Consortium (ADGC), Kunkle, B. W., The European Alzheimer’s Disease Initiative (EADI), Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium (CHARGE), Genetic and Environmental Risk in AD/Defining Genetic, P. A. E. R. F. A. D. C. (., Grenier-Boley, B., Sims, R., Bis, J. C., Damotte, V., Naj, A. C., et al. (2019) · Nature Genetics · doi:10.1038/s41588-019-0358-2 · Cited by 2,946 · see citing works

REVEL: An Ensemble Method for Predicting the Pathogenicity of Rare Missense Variants

Ioannidis, N. M., Rothstein, J. H., Pejaver, V., Middha, S., McDonnell, S. K., Baheti, S., Musolf, A., Li, Q., Holzinger, E., Karyadi, D., et al. (2016) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2016.08.016 · Cited by 2,908 · see citing works

Predicting the Functional Effect of Amino Acid Substitutions and Indels

Choi, Y., Sims, G. E., Murphy, S., Miller, J. R., & Chan, A. P. (2012) · PLoS ONE · doi:10.1371/journal.pone.0046688 · Cited by 2,890 · see citing works

Synaptic, transcriptional and chromatin genes disrupted in autism

Study, T. D., De Rubeis, S., Autism, H. M. C. F., UK10K Consortium, The Autism Sequencing Consortium, He, X., Goldberg, A. P., Poultney, C. S., Samocha, K., Ercument Cicek, A., et al. (2014) · Nature · doi:10.1038/nature13772 · Cited by 2,746 · see citing works

Annotation of functional variation in personal genomes using RegulomeDB

Boyle, A. P., Hong, E. L., Hariharan, M., Cheng, Y., Schaub, M. A., Kasowski, M., Karczewski, K. J., Park, J., Hitz, B. C., Weng, S., et al. (2012) · Genome Research · doi:10.1101/gr.137323.112 · Cited by 2,722 · see citing works

A landscape of driver mutations in melanoma

Hodis, E., Watson, I. R., Kryukov, G. V., Arold, S. T., Imielinski, M., Theurillat, J.-P., Nickerson, E., Auclair, D., Li, L., Place, C., et al. (2012) · Cell · doi:10.1016/j.cell.2012.06.024 · Cited by 2,610 · see citing works

Ensembl 2018

Zerbino, D. R., Achuthan, P., Akanni, W., Amode, M. R., Barrell, D., Bhai, J., Billis, K., Cummins, C., Gall, A., Girón, C. G., et al. (2018) · Nucleic Acids Research · doi:10.1093/nar/gkx1098 · Cited by 2,605 · see citing works

PROVEAN web server: a tool to predict the functional effect of amino acid substitutions and indels

Choi, Y., & Chan, A. P.-Y. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv195 · Cited by 2,560 · see citing works

The Mutational Landscape of Head and Neck Squamous Cell Carcinoma

Stransky, N., Egloff, A. M., Tward, A. D., Kostic, A. D., Cibulskis, K., Sivachenko, A., Kryukov, G. V., Lawrence, M. S., Sougnez, C. L., McKenna, A., et al. (2011) · Science · doi:10.1126/science.1208130 · Cited by 2,500 · see citing works

SIFT web server: predicting effects of amino acid substitutions on proteins

Sim, N.-L., Kumar, P. N., Hu, J., Henikoff, S., Schneider, G., & Ng, P. C. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks539 · Cited by 2,419 · see citing works

Large-Scale Exome Sequencing Study Implicates Both Developmental and Functional Changes in the Neurobiology of Autism

Satterstrom, F. K., Kosmicki, J. A., Wang, J., Breen, M. S., De Rubeis, S., An, J.-Y., Peng, M., Collins, R., Grove, J., Klei, L., et al. (2020) · Cell · doi:10.1016/j.cell.2019.12.036 · Cited by 2,321 · see citing works

HaploReg: a resource for exploring chromatin states, conservation, and regulatory motif alterations within sets of genetically linked variants

Ward, L. D., & Kellis, M. (2012) · Nucleic Acids Research · doi:10.1093/nar/gkr917 · Cited by 2,229 · see citing works

De novo mutations revealed by whole-exome sequencing are strongly associated with autism

Sanders, S. J., Murtha, M. T., Gupta, A. R., Murdoch, J. D., Raubeson, M. J., Willsey, A. J., Ercan-Sencicek, A. G., DiLullo, N. M., Parikshak, N. N., Stein, J. L., et al. (2012) · Nature · doi:10.1038/nature10945 · Cited by 2,084 · see citing works

Common variants at ABCA7, MS4A6A/MS4A4E, EPHA1, CD33 and CD2AP are associated with Alzheimer's disease

Initiative, T. A. D. N., Hollingworth, P., CHARGE consortium, EADI1 consortium, Harold, D., Sims, R., Gerrish, A., Lambert, J.-C., Carrasquillo, M. M., Abraham, R., et al. (2011) · Nature Genetics · doi:10.1038/ng.803 · Cited by 1,997 · see citing works

A high-coverage genome sequence from an archaic denisovan individual

Meyer, M., Kircher, M., Gansauge, M.-T., Li, H., Racimo, F., Mallick, S., Schraiber, J. G., Jay, F., Prüfer, K., de Filippo, C., et al. (2012) · Science · doi:10.1126/science.1224344 · Cited by 1,967 · see citing works

Exome sequencing of hepatocellular carcinomas identifies new mutational signatures and potential therapeutic targets

Schulze, K., Imbeaud, S., Letouzé, E., Alexandrov, L. B., Calderaro, J., Rebouissou, S., Couchy, G., Meiller, C., Shinde, J., Soysouvanh, F., et al. (2015) · Nature Genetics · doi:10.1038/ng.3252 · Cited by 1,803 · see citing works

Mapping the Hallmarks of Lung Adenocarcinoma with Massively Parallel Sequencing

Imielinski, M., Berger, A. H., Hammerman, P. S., Hernandez, B., Pugh, T. J., Hodis, E., Cho, J., Suh, J., Capelletti, M., Sivachenko, A., et al. (2012) · Cell · doi:10.1016/j.cell.2012.08.029 · Cited by 1,789 · see citing works

Patterns and rates of exonic de novo mutations in autism spectrum disorders

Neale, B. M., Kou, Y., Liu, L., Ma’ayan, A., Samocha, K. E., Sabo, A., Lin, C.-F., Stevens, C., Wang, L.-S., Makarov, V., et al. (2012) · Nature · doi:10.1038/nature11011 · Cited by 1,734 · see citing works

Exome sequencing as a tool for Mendelian disease gene discovery

Bamshad, M. J., Ng, S. B. H., Bigham, A. W., Tabor, H. K., Emond, M. J., Nickerson, D. A., & Shendure, J. (2011) · Nature Reviews Genetics · doi:10.1038/nrg3031 · Cited by 1,659 · see citing works

Evolution and functional impact of rare coding variation from deep sequencing of human exomes

Tennessen, J. A., Bigham, A. W., O’Connor, T. D., Fu, W., Kenny, E. E., Gravel, S., McGee, S., Do, R., Liu, X., Jun, G., et al. (2012) · Science · doi:10.1126/science.1219240 · Cited by 1,613 · see citing works

SIFT missense predictions for genomes

Vaser, R., Adusumalli, S., Leng, S. N., Sikic, M., & Ng, P. C. (2016) · Nature Protocols · doi:10.1038/nprot.2015.123 · Cited by 1,510 · see citing works

Integrated analysis of somatic mutations and focal copy-number changes identifies key genes and pathways in hepatocellular carcinoma

Guichard, C., Amaddeo, G., Imbeaud, S., Ladeiro, Y., Pelletier, L., Benmaad, I., Caldéraro, J., Bioulac‐Sage, P., Letexier, M., Degos, F., et al. (2012) · Nature Genetics · doi:10.1038/ng.2256 · Cited by 1,451 · see citing works

Association analysis identifies 65 new breast cancer risk loci

Michailidou, K., Lindström, S., Dennis, J., Beesley, J., Hui, S., Kar, S., Lemaçon, A., Soucy, P., Glubb, D. M., Rostamianfar, A., et al. (2017) · Nature · doi:10.1038/nature24284 · Cited by 1,380 · see citing works

Tumor aneuploidy correlates with markers of immune evasion and with reduced response to immunotherapy

Davoli, T., Uno, H., Wooten, E. C., & Elledge, S. J. (2017) · Science · doi:10.1126/science.aaf8399 · Cited by 1,325 · see citing works

Predicting the Functional, Molecular, and Phenotypic Consequences of Amino Acid Substitutions using Hidden Markov Models

Shihab, H. A., Gough, J., Cooper, D. N., Stenson, P. D., Barker, G., Edwards, K. J., Day, I. N. M., & Gaunt, T. R. (2012) · Human Mutation · doi:10.1002/humu.22225 · Cited by 1,319 · see citing works

Guidelines for investigating causality of sequence variants in human disease

MacArthur, D. G., Manolio, T. A., Dimmock, D. P., Rehm, H. L., Shendure, J., Abecasis, G. R., Adams, D. R., Altman, R. B., Antonarakis, S. E., Ashley, E. A., et al. (2014) · Nature · doi:10.1038/nature13127 · Cited by 1,224 · see citing works

Personal omics profiling reveals dynamic molecular and medical phenotypes

Chen, R., Mias, G. I., Li-Pook-Than, J., Jiang, L., Lam, H. Y. K., Chen, R., Miriami, E., Karczewski, K. J., Hariharan, M., Dewey, F. E., et al. (2012) · Cell · doi:10.1016/j.cell.2012.02.009 · Cited by 1,291 · see citing works

The human splicing code reveals new insights into the genetic determinants of disease

Xiong, H. Y., Alipanahi, B., Lee, L. J., Bretschneider, H., Merico, D., Yuen, R. K. C., Hua, Y., Gueroussov, S., Najafabadi, H. S., Hughes, T., et al. (2014) · Science · doi:10.1126/science.1254806 · Cited by 1,225 · see citing works

Exome sequencing in sporadic autism spectrum disorders identifies severe de novo mutations

O'Roak, B. J., Deriziotis, P., Lee, C., Vives, L., Schwartz, J. J., Girirajan, S., Karakoc, E., MacKenzie, A. P., Ng, S. B., Baker, C., et al. (2011) · Nature Genetics · doi:10.1038/ng.835 · Cited by 1,203 · see citing works

The genetic landscape of high-risk neuroblastoma

Pugh, T. J., Morozova, O., Attiyeh, E. F., Asgharzadeh, S., Wei, J. S., Auclair, D., Carter, S. L., Cibulskis, K., Hanna, M., Kieżun, A., et al. (2013) · Nature Genetics · doi:10.1038/ng.2529 · Cited by 1,170 · see citing works

Ensembl 2020

Yates, A. D., Achuthan, P., Akanni, W. A., Allen, J., Allen, J., Álvarez-Jarreta, J., Amode, M. R., Armean, I. M., Azov, A. G., Bennett, R., et al. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz966 · Cited by 1,162 · see citing works

Comparison and integration of deleteriousness prediction methods for nonsynonymous SNVs in whole exome sequencing studies

Dong, C., Wei, P., Jian, X., Gibbs, R. A., Boerwinkle, E., Wang, K., & Liu, X. (2014) · Human Molecular Genetics · doi:10.1093/hmg/ddu733 · Cited by 1,106 · see citing works

Chemoresistance Evolution in Triple-Negative Breast Cancer Delineated by Single-Cell Sequencing

Kim, C. R., Gao, R., Sei, E., Brandt, R., Hartman, J., Hatschek, T., Crosetto, N., Foukakis, T., & Navin, N. E. (2018) · Cell · doi:10.1016/j.cell.2018.03.041 · Cited by 1,091 · see citing works

Advances in understanding cancer genomes through second-generation sequencing

Meyerson, M. M., Gabriel, S., & Getz, G. A. (2010) · Nature Reviews Genetics · doi:10.1038/nrg2841 · Cited by 1,114 · see citing works

Pleiotropy in complex traits: challenges and strategies

Solovieff, N., Cotsapas, C., Lee, P. H., Purcell, S. M., & Smoller, J. W. (2013) · Nature Reviews Genetics · doi:10.1038/nrg3461 · Cited by 1,085 · see citing works

Optimal Unified Approach for Rare-Variant Association Testing with Application to Small-Sample Case-Control Whole-Exome Sequencing Studies

Lee, S., Emond, M. J., Bamshad, M. J., Barnes, K. C., Rieder, M. J., Nickerson, D. A., Christiani, D. C., Wurfel, M. M., & Lin, X. (2012) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2012.06.007 · Cited by 1,040 · see citing works

mCSM: Predicting the effects of mutations in proteins using graph-based signatures

Pires, D. E. V., Ascher, D. B., & Blundell, T. L. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btt691 · Cited by 1,066 · see citing works

InterVar: Clinical Interpretation of Genetic Variants by the 2015 ACMG-AMP Guidelines

Li, Q., & Wang, K. (2017) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2017.01.004 · Cited by 1,035 · see citing works

Rare-Variant Association Analysis: Study Designs and Statistical Tests

Lee, S., Abecasis, G. R., Boehnke, M., & Lin, X. (2014) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2014.06.009 · Cited by 1,042 · see citing works

Clonal evolution in breast cancer revealed by single nucleus genome sequencing

Wang, Y., Waters, J., Leung, M. L., Unruh, A., Roh, W., Shi, X., Chen, K., Scheet, P., Vattathil, S., Liang, H., et al. (2014) · Nature · doi:10.1038/nature13600 · Cited by 1,029 · see citing works

dbNSFP v3.0: A One-Stop Database of Functional Predictions and Annotations for Human Nonsynonymous and Splice-Site SNVs

Liu, X., Wu, C., Li, C., & Boerwinkle, E. (2015) · Human Mutation · doi:10.1002/humu.22932 · Cited by 957 · see citing works

Acquired Resistance and Clonal Evolution in Melanoma during BRAF Inhibitor Therapy

Shi, H., Hugo, W., Kong, X., Hong, A., Koya, R. C., Moriceau, G., Chodon, T., Guo, R., Johnson, D. B., Dahlman, K. B., et al. (2014) · Cancer Discovery · doi:10.1158/2159-8290.cd-13-0642 · Cited by 982 · see citing works

Exome sequencing in amyotrophic lateral sclerosis identifies risk genes and pathways

Cirulli, E. T., Lasseigne, B. N., Petrovski, S., Sapp, P. C., Dion, P. A., Leblond, C. S., Couthouis, J., Lu, Y.-F., Wang, Q., Krueger, B. J., et al. (2015) · Science · doi:10.1126/science.aaa3650 · Cited by 966 · see citing works

Analysis of 6,515 exomes reveals the recent origin of most human protein-coding variants

Fu, W., O’Connor, T. D., Jun, G., Kang, H. M., Abecasis, G. R., Leal, S. M., Gabriel, S., Rieder, M. J., Altshuler, D., Shendure, J., et al. (2012) · Nature · doi:10.1038/nature11690 · Cited by 951 · see citing works

Predicting Secretory Proteins with SignalP

Nielsen, H. (2017) · Methods in molecular biology · doi:10.1007/978-1-4939-7015-5_6 · Cited by 932 · see citing works

Identification of seven loci affecting mean telomere length and their association with disease

CARDIoGRAM consortium, Codd, V., Nelson, C. P., Albrecht, E., Mangino, M., Deelen, J., Buxton, J. L., Hottenga, J. J., Fischer, K., Esko, T., et al. (2013) · Nature Genetics · doi:10.1038/ng.2528 · Cited by 933 · see citing works

Inferring the molecular and phenotypic impact of amino acid variants with MutPred2

Pejaver, V., Urresti, J., Lugo-Martinez, J., Pagel, K. A., Lin, G. N., Nam, H.-J., Mort, M., Cooper, D. N., Sebat, J., Iakoucheva, L. M., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-19669-x · Cited by 923 · see citing works

Genic Intolerance to Functional Variation and the Interpretation of Personal Genomes

Petrovski, S., Wang, Q., Heinzen, E. L., Allen, A. S., & Goldstein, D. B. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003709 · Cited by 901 · see citing works

A Mutation in VPS35, Encoding a Subunit of the Retromer Complex, Causes Late-Onset Parkinson Disease

Zimprich, A. A., Benet‐Pagès, A., Struhal, W., Graf, E., Eck, S. H., Offman, M. N., Haubenberger, D., Spielberger, S., Schulte, E. C., Lichtner, P., et al. (2011) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2011.06.008 · Cited by 885 · see citing works

Sequencing of neuroblastoma identifies chromothripsis and defects in neuritogenesis genes

Molenaar, J. J., Köster, J., Zwijnenburg, D. A., Sluis, P. V., Valentijn, L. J., van der Ploeg, I., Hamdi, M., van Nes, J., Westerman, B. A., van Arkel, J., et al. (2012) · Nature · doi:10.1038/nature10910 · Cited by 869 · see citing works

Ensembl 2013

Flicek, P., Ahmed, I., Amode, M. R., Barrell, D. G., Beal, K. M., Brent, S., Carvalho‐Silva, D., Clapham, P., Coates, G. M. P., Fairley, S., et al. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1236 · Cited by 869 · see citing works

Genome sequencing of pediatric medulloblastoma links catastrophic DNA rearrangements with TP53 mutations

Rausch, T., Jones, D. T. W., Zapatka, M., Stütz, A. M., Zichner, T., Weischenfeldt, J., Jäger, N., Remke, M., Shih, D., Northcott, P. A., et al. (2012) · Cell · doi:10.1016/j.cell.2011.12.013 · Cited by 865 · see citing works

Genomic variant annotation and prioritization with ANNOVAR and wANNOVAR

Yang, H., & Wang, K. (2015) · Nature Protocols · doi:10.1038/nprot.2015.105 · Cited by 845 · see citing works

Identification of multiple risk variants for ankylosing spondylitis through high-density genotyping of immune-related loci

Cortés, A., Hadler, J. S., Robinson, P. C., Leo, P., Cremin, K., Pryce, K., Harris, J., Bradbury, L. A., Kenna, T., Yang, J., et al. (2013) · Nature Genetics · doi:10.1038/ng.2667 · Cited by 855 · see citing works

PredictSNP: Robust and Accurate Consensus Classifier for Prediction of Disease-Related Mutations

Bendl, J. M., Štourač, J., Šalanda, O., Pavelka, A., Wieben, E. D., Zendulka, J., Brezovský, J., & Damborský, J. (2014) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003440 · Cited by 850 · see citing works

M-CAP eliminates a majority of variants of uncertain significance in clinical exomes at high sensitivity

Jagadeesh, K. A., Wenger, A. M., Berger, M. J., Guturu, H., Stenson, P. D., Cooper, D. N., Bernstein, J. A., & Bejerano, G. (2016) · Nature Genetics · doi:10.1038/ng.3703 · Cited by 831 · see citing works

Whole genome sequencing resource identifies 18 new candidate genes for autism spectrum disorder

C Yuen, R. K., Merico, D., Bookman, M., L Howe, J., Thiruvahindrapuram, B., Patel, R. V., Whitney, J., Deflaux, N., Bingham, J., Wang, Z., et al. (2017) · Nature Neuroscience · doi:10.1038/nn.4524 · Cited by 844 · see citing works

Whole-genome sequencing of 234 bulls facilitates mapping of monogenic and complex traits in cattle

Daetwyler, H. D., Capitan, A., Pausch, H., Stothard, P., van Binsbergen, R., Brøndum, R. F., Liao, X., Djari, A., Rodriguez, S. C., Grohs, C., et al. (2014) · Nature Genetics · doi:10.1038/ng.3034 · Cited by 838 · see citing works

Pathogenic Germline Variants in 10,389 Adult Cancers

Huang, K., Mashl, R. J., Wu, Y., Ritter, D., Wang, J., Oh, C., Paczkowska, M., Reynolds, S. M., Wyczalkowski, M. A., Oak, N., et al. (2018) · Cell · doi:10.1016/j.cell.2018.03.039 · Cited by 838 · see citing works

dbNSFP: A lightweight database of human nonsynonymous SNPs and their functional predictions

Liu, X., Jian, X., & Boerwinkle, E. (2011) · Human Mutation · doi:10.1002/humu.21517 · Cited by 816 · see citing works

Ensembl 2012

Flicek, P., Amode, M. R., Barrell, D. G., Beal, K. M., Brent, S., Carvalho‐Silva, D., Clapham, P., Coates, G. M. P., Fairley, S., Fitzgerald, S. F., et al. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr991 · Cited by 818 · see citing works

Cumulative haploinsufficiency and triplosensitivity drive aneuploidy patterns and shape the cancer genome

Davoli, T., Xu, A. W., Mengwasser, K. E., Sack, L. M., Yoon, J. C., Park, P. J., & Elledge, S. J. (2013) · Cell · doi:10.1016/j.cell.2013.10.011 · Cited by 815 · see citing works

Exome sequencing identifies somatic mutations of DNA methyltransferase gene DNMT3A in acute monocytic leukemia

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Exploiting the Mutanome for Tumor Vaccination

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