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Items: 1 to 20 of 91

1.

Prediction of deleterious mutations in coding regions of mammals with transfer learning.

Plekhanova E, Nuzhdin SV, Utkin LV, Samsonova MG.

Evol Appl. 2018 May 9;12(1):18-28. doi: 10.1111/eva.12607. eCollection 2019 Jan.

2.

A Pipeline for Classifying Deleterious Coding Mutations in Agricultural Plants.

Kovalev MS, Igolkina AA, Samsonova MG, Nuzhdin SV.

Front Plant Sci. 2018 Nov 28;9:1734. doi: 10.3389/fpls.2018.01734. eCollection 2018.

3.

Machine learning classifier for identification of damaging missense mutations exclusive to human mitochondrial DNA-encoded polypeptides.

Martín-Navarro A, Gaudioso-Simón A, Álvarez-Jarreta J, Montoya J, Mayordomo E, Ruiz-Pesini E.

BMC Bioinformatics. 2017 Mar 7;18(1):158. doi: 10.1186/s12859-017-1562-7.

4.

Identification of deleterious mutations within three human genomes.

Chun S, Fay JC.

Genome Res. 2009 Sep;19(9):1553-61. doi: 10.1101/gr.092619.109. Epub 2009 Jul 14.

5.

PredictSNP: robust and accurate consensus classifier for prediction of disease-related mutations.

Bendl J, Stourac J, Salanda O, Pavelka A, Wieben ED, Zendulka J, Brezovsky J, Damborsky J.

PLoS Comput Biol. 2014 Jan;10(1):e1003440. doi: 10.1371/journal.pcbi.1003440. Epub 2014 Jan 16.

6.
7.

Accumulation of slightly deleterious mutations in mitochondrial protein-coding genes of large versus small mammals.

Popadin K, Polishchuk LV, Mamirova L, Knorre D, Gunbin K.

Proc Natl Acad Sci U S A. 2007 Aug 14;104(33):13390-5. Epub 2007 Aug 6.

8.

Comparison of machine learning techniques to predict all-cause mortality using fitness data: the Henry ford exercIse testing (FIT) project.

Sakr S, Elshawi R, Ahmed AM, Qureshi WT, Brawner CA, Keteyian SJ, Blaha MJ, Al-Mallah MH.

BMC Med Inform Decis Mak. 2017 Dec 19;17(1):174. doi: 10.1186/s12911-017-0566-6.

9.

Identification of deleterious synonymous variants in human genomes.

Buske OJ, Manickaraj A, Mital S, Ray PN, Brudno M.

Bioinformatics. 2013 Aug 1;29(15):1843-50. doi: 10.1093/bioinformatics/btt308. Epub 2013 Jun 4. Erratum in: Bioinformatics. 2015 Mar 1;31(5):799.

PMID:
23736532
10.

Positional conservation and amino acids shape the correct diagnosis and population frequencies of benign and damaging personal amino acid mutations.

Kumar S, Suleski MP, Markov GJ, Lawrence S, Marco A, Filipski AJ.

Genome Res. 2009 Sep;19(9):1562-9. doi: 10.1101/gr.091991.109. Epub 2009 Jun 22.

11.

A neural network multi-task learning approach to biomedical named entity recognition.

Crichton G, Pyysalo S, Chiu B, Korhonen A.

BMC Bioinformatics. 2017 Aug 15;18(1):368. doi: 10.1186/s12859-017-1776-8.

12.

Assessment of computational methods for predicting the effects of missense mutations in human cancers.

Gnad F, Baucom A, Mukhyala K, Manning G, Zhang Z.

BMC Genomics. 2013;14 Suppl 3:S7. doi: 10.1186/1471-2164-14-S3-S7. Epub 2013 May 28.

13.

Classifying injury narratives of large administrative databases for surveillance-A practical approach combining machine learning ensembles and human review.

Marucci-Wellman HR, Corns HL, Lehto MR.

Accid Anal Prev. 2017 Jan;98:359-371. doi: 10.1016/j.aap.2016.10.014. Epub 2016 Nov 15.

14.

Small fitness effect of mutations in highly conserved non-coding regions.

Kryukov GV, Schmidt S, Sunyaev S.

Hum Mol Genet. 2005 Aug 1;14(15):2221-9. Epub 2005 Jun 30.

PMID:
15994173
15.

Mammalian genomic regulatory regions predicted by utilizing human genomics, transcriptomics, and epigenetics data.

Nguyen QH, Tellam RL, Naval-Sanchez M, Porto-Neto LR, Barendse W, Reverter A, Hayes B, Kijas J, Dalrymple BP.

Gigascience. 2018 Mar 1;7(3):1-17. doi: 10.1093/gigascience/gix136.

16.

Subtype prediction in pediatric acute myeloid leukemia: classification using differential network rank conservation revisited.

Obulkasim A, Fornerod M, Zwaan MC, Reinhardt D, van den Heuvel-Eibrink MM.

BMC Bioinformatics. 2015 Sep 23;16:305. doi: 10.1186/s12859-015-0737-3.

17.

A novel end-to-end classifier using domain transferred deep convolutional neural networks for biomedical images.

Pang S, Yu Z, Orgun MA.

Comput Methods Programs Biomed. 2017 Mar;140:283-293. doi: 10.1016/j.cmpb.2016.12.019. Epub 2017 Jan 6.

PMID:
28254085
18.

Improving classification of mature microRNA by solving class imbalance problem.

Wang Y, Li X, Tao B.

Sci Rep. 2016 May 16;6:25941. doi: 10.1038/srep25941.

19.

Prediction and interpretation of deleterious coding variants in terms of protein structural stability.

Ancien F, Pucci F, Godfroid M, Rooman M.

Sci Rep. 2018 Mar 14;8(1):4480. doi: 10.1038/s41598-018-22531-2.

20.

A new disease-specific machine learning approach for the prediction of cancer-causing missense variants.

Capriotti E, Altman RB.

Genomics. 2011 Oct;98(4):310-7. doi: 10.1016/j.ygeno.2011.06.010. Epub 2011 Jul 7.

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