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For: Hoskins RA, Repo S, Barsky D, Andreoletti G, Moult J, Brenner SE. Reports from CAGI: The Critical Assessment of Genome Interpretation. Hum Mutat 2017;38:1039-41. [PMID: 28817245 DOI: 10.1002/humu.23290] [Cited by in Crossref: 31] [Cited by in F6Publishing: 21] [Article Influence: 7.8] [Reference Citation Analysis]
Number Citing Articles
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10 Seaby EG, Ennis S. Challenges in the diagnosis and discovery of rare genetic disorders using contemporary sequencing technologies. Brief Funct Genomics 2020;19:243-58. [PMID: 32393978 DOI: 10.1093/bfgp/elaa009] [Cited by in Crossref: 5] [Cited by in F6Publishing: 3] [Article Influence: 5.0] [Reference Citation Analysis]
11 Wells DK, van Buuren MM, Dang KK, Hubbard-Lucey VM, Sheehan KCF, Campbell KM, Lamb A, Ward JP, Sidney J, Blazquez AB, Rech AJ, Zaretsky JM, Comin-Anduix B, Ng AHC, Chour W, Yu TV, Rizvi H, Chen JM, Manning P, Steiner GM, Doan XC, Merghoub T, Guinney J, Kolom A, Selinsky C, Ribas A, Hellmann MD, Hacohen N, Sette A, Heath JR, Bhardwaj N, Ramsdell F, Schreiber RD, Schumacher TN, Kvistborg P, Defranoux NA; Tumor Neoantigen Selection Alliance. Key Parameters of Tumor Epitope Immunogenicity Revealed Through a Consortium Approach Improve Neoantigen Prediction. Cell 2020;183:818-834.e13. [PMID: 33038342 DOI: 10.1016/j.cell.2020.09.015] [Cited by in Crossref: 52] [Cited by in F6Publishing: 49] [Article Influence: 26.0] [Reference Citation Analysis]
12 Tarca AL, Pataki BÁ, Romero R, Sirota M, Guan Y, Kutum R, Gomez-Lopez N, Done B, Bhatti G, Yu T, Andreoletti G, Chaiworapongsa T, Hassan SS, Hsu CD, Aghaeepour N, Stolovitzky G, Csabai I, Costello JC; DREAM Preterm Birth Prediction Challenge Consortium. Crowdsourcing assessment of maternal blood multi-omics for predicting gestational age and preterm birth. Cell Rep Med 2021;2:100323. [PMID: 34195686 DOI: 10.1016/j.xcrm.2021.100323] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
13 Niroula A, Vihinen M. How good are pathogenicity predictors in detecting benign variants? PLoS Comput Biol 2019;15:e1006481. [PMID: 30742610 DOI: 10.1371/journal.pcbi.1006481] [Cited by in Crossref: 26] [Cited by in F6Publishing: 21] [Article Influence: 8.7] [Reference Citation Analysis]
14 Padilla N, Moles-Fernández A, Riera C, Montalban G, Özkan S, Ootes L, Bonache S, Díez O, Gutiérrez-Enríquez S, de la Cruz X. BRCA1- and BRCA2-specific in silico tools for variant interpretation in the CAGI 5 ENIGMA challenge. Hum Mutat 2019;40:1593-611. [PMID: 31112341 DOI: 10.1002/humu.23802] [Cited by in Crossref: 6] [Cited by in F6Publishing: 4] [Article Influence: 2.0] [Reference Citation Analysis]
15 Adhikari AN. Gene-specific features enhance interpretation of mutational impact on acid α-glucosidase enzyme activity. Hum Mutat 2019;40:1507-18. [PMID: 31228295 DOI: 10.1002/humu.23846] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 0.7] [Reference Citation Analysis]
16 Clark WT, Kasak L, Bakolitsa C, Hu Z, Andreoletti G, Babbi G, Bromberg Y, Casadio R, Dunbrack R, Folkman L, Ford CT, Jones D, Katsonis P, Kundu K, Lichtarge O, Martelli PL, Mooney SD, Nodzak C, Pal LR, Radivojac P, Savojardo C, Shi X, Zhou Y, Uppal A, Xu Q, Yin Y, Pejaver V, Wang M, Wei L, Moult J, Yu GK, Brenner SE, LeBowitz JH. Assessment of predicted enzymatic activity of α-N-acetylglucosaminidase variants of unknown significance for CAGI 2016. Hum Mutat 2019;40:1519-29. [PMID: 31342580 DOI: 10.1002/humu.23875] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 2.0] [Reference Citation Analysis]
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18 Hu Z, Yu C, Furutsuki M, Andreoletti G, Ly M, Hoskins R, Adhikari AN, Brenner SE. VIPdb, a genetic Variant Impact Predictor Database. Hum Mutat 2019;40:1202-14. [PMID: 31283070 DOI: 10.1002/humu.23858] [Cited by in Crossref: 13] [Cited by in F6Publishing: 11] [Article Influence: 4.3] [Reference Citation Analysis]
19 Pal LR, Kundu K, Yin Y, Moult J. Matching whole genomes to rare genetic disorders: Identification of potential causative variants using phenotype-weighted knowledge in the CAGI SickKids5 clinical genomes challenge. Hum Mutat 2020;41:347-62. [PMID: 31680375 DOI: 10.1002/humu.23933] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
20 Katsonis P, Lichtarge O. CAGI5: Objective performance assessments of predictions based on the Evolutionary Action equation. Hum Mutat 2019;40:1436-54. [PMID: 31317604 DOI: 10.1002/humu.23873] [Cited by in Crossref: 9] [Cited by in F6Publishing: 9] [Article Influence: 3.0] [Reference Citation Analysis]
21 Cao Y, Sun Y, Karimi M, Chen H, Moronfoye O, Shen Y. Predicting pathogenicity of missense variants with weakly supervised regression. Hum Mutat 2019;40:1579-92. [PMID: 31144781 DOI: 10.1002/humu.23826] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 1.3] [Reference Citation Analysis]
22 Kim HY, Jeon W, Kim D. An enhanced variant effect predictor based on a deep generative model and the Born-Again Networks. Sci Rep 2021;11:19127. [PMID: 34580383 DOI: 10.1038/s41598-021-98693-3] [Reference Citation Analysis]
23 Li G, Panday SK, Alexov E. SAAFEC-SEQ: A Sequence-Based Method for Predicting the Effect of Single Point Mutations on Protein Thermodynamic Stability. Int J Mol Sci 2021;22:E606. [PMID: 33435356 DOI: 10.3390/ijms22020606] [Cited by in Crossref: 5] [Cited by in F6Publishing: 4] [Article Influence: 5.0] [Reference Citation Analysis]