219 related articles for article (PubMed ID: 30742610)
1. How good are pathogenicity predictors in detecting benign variants?
Niroula A; Vihinen M
PLoS Comput Biol; 2019 Feb; 15(2):e1006481. PubMed ID: 30742610
[TBL] [Abstract][Full Text] [Related]
2. Using high-resolution variant frequencies to empower clinical genome interpretation.
Whiffin N; Minikel E; Walsh R; O'Donnell-Luria AH; Karczewski K; Ing AY; Barton PJR; Funke B; Cook SA; MacArthur D; Ware JS
Genet Med; 2017 Oct; 19(10):1151-1158. PubMed ID: 28518168
[TBL] [Abstract][Full Text] [Related]
3. Pathogenic variant burden in the ExAC database: an empirical approach to evaluating population data for clinical variant interpretation.
Kobayashi Y; Yang S; Nykamp K; Garcia J; Lincoln SE; Topper SE
Genome Med; 2017 Feb; 9(1):13. PubMed ID: 28166811
[TBL] [Abstract][Full Text] [Related]
4. Problems in variation interpretation guidelines and in their implementation in computational tools.
Vihinen M
Mol Genet Genomic Med; 2020 Sep; 8(9):e1206. PubMed ID: 32160417
[TBL] [Abstract][Full Text] [Related]
5. UMD-Predictor: A High-Throughput Sequencing Compliant System for Pathogenicity Prediction of any Human cDNA Substitution.
Salgado D; Desvignes JP; Rai G; Blanchard A; Miltgen M; Pinard A; Lévy N; Collod-Béroud G; Béroud C
Hum Mutat; 2016 May; 37(5):439-46. PubMed ID: 26842889
[TBL] [Abstract][Full Text] [Related]
6. PON-P and PON-P2 predictor performance in CAGI challenges: Lessons learned.
Niroula A; Vihinen M
Hum Mutat; 2017 Sep; 38(9):1085-1091. PubMed ID: 28224672
[TBL] [Abstract][Full Text] [Related]
7. GAVIN: Gene-Aware Variant INterpretation for medical sequencing.
van der Velde KJ; de Boer EN; van Diemen CC; Sikkema-Raddatz B; Abbott KM; Knopperts A; Franke L; Sijmons RH; de Koning TJ; Wijmenga C; Sinke RJ; Swertz MA
Genome Biol; 2017 Jan; 18(1):6. PubMed ID: 28093075
[TBL] [Abstract][Full Text] [Related]
8. Benchmarking subcellular localization and variant tolerance predictors on membrane proteins.
Orioli T; Vihinen M
BMC Genomics; 2019 Jul; 20(Suppl 8):547. PubMed ID: 31307390
[TBL] [Abstract][Full Text] [Related]
9. ClinPred: Prediction Tool to Identify Disease-Relevant Nonsynonymous Single-Nucleotide Variants.
Alirezaie N; Kernohan KD; Hartley T; Majewski J; Hocking TD
Am J Hum Genet; 2018 Oct; 103(4):474-483. PubMed ID: 30220433
[TBL] [Abstract][Full Text] [Related]
10. Comparison of Pathogenicity Prediction Tools on Somatic Variants.
Suybeng V; Koeppel F; Harlé A; Rouleau E
J Mol Diagn; 2020 Dec; 22(12):1383-1392. PubMed ID: 33011441
[TBL] [Abstract][Full Text] [Related]
11. Classification of Amino Acid Substitutions in Mismatch Repair Proteins Using PON-MMR2.
Niroula A; Vihinen M
Hum Mutat; 2015 Dec; 36(12):1128-34. PubMed ID: 26333163
[TBL] [Abstract][Full Text] [Related]
12. Variation Interpretation Predictors: Principles, Types, Performance, and Choice.
Niroula A; Vihinen M
Hum Mutat; 2016 Jun; 37(6):579-97. PubMed ID: 26987456
[TBL] [Abstract][Full Text] [Related]
13. PON-P2: prediction method for fast and reliable identification of harmful variants.
Niroula A; Urolagin S; Vihinen M
PLoS One; 2015; 10(2):e0117380. PubMed ID: 25647319
[TBL] [Abstract][Full Text] [Related]
14. Many amino acid substitution variants identified in DNA repair genes during human population screenings are predicted to impact protein function.
Xi T; Jones IM; Mohrenweiser HW
Genomics; 2004 Jun; 83(6):970-9. PubMed ID: 15177551
[TBL] [Abstract][Full Text] [Related]
15. The Complementarity Between Protein-Specific and General Pathogenicity Predictors for Amino Acid Substitutions.
Riera C; Padilla N; de la Cruz X
Hum Mutat; 2016 Oct; 37(10):1013-24. PubMed ID: 27397615
[TBL] [Abstract][Full Text] [Related]
16. Exome sequencing analysis: a guide to disease variant detection.
Isakov O; Perrone M; Shomron N
Methods Mol Biol; 2013; 1038():137-58. PubMed ID: 23872973
[TBL] [Abstract][Full Text] [Related]
17. Prevalence of Titin Truncating Variants in General Population.
Akinrinade O; Koskenvuo JW; Alastalo TP
PLoS One; 2015; 10(12):e0145284. PubMed ID: 26701604
[TBL] [Abstract][Full Text] [Related]
18. Targeted 46-gene and clinical exome sequencing for mutations causing cardiomyopathies.
Waldmüller S; Schroeder C; Sturm M; Scheffold T; Imbrich K; Junker S; Frische C; Hofbeck M; Bauer P; Bonin M; Gawaz M; Gramlich M
Mol Cell Probes; 2015 Oct; 29(5):308-14. PubMed ID: 25979592
[TBL] [Abstract][Full Text] [Related]
19. Analysis of 60 706 Exomes Questions the Role of De Novo Variants Previously Implicated in Cardiac Disease.
Paludan-Müller C; Ahlberg G; Ghouse J; Svendsen JH; Haunsø S; Olesen MS
Circ Cardiovasc Genet; 2017 Dec; 10(6):. PubMed ID: 29237690
[TBL] [Abstract][Full Text] [Related]
20. Development of pathogenicity predictors specific for variants that do not comply with clinical guidelines for the use of computational evidence.
de la Campa EÁ; Padilla N; de la Cruz X
BMC Genomics; 2017 Aug; 18(Suppl 5):569. PubMed ID: 28812538
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
