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Items: 1 to 20 of 77

1.

Novel phenotype-disease matching tool for rare genetic diseases.

Chen J, Xu H, Jegga A, Zhang K, White PS, Zhang G.

Genet Med. 2018 Jun 12. doi: 10.1038/s41436-018-0050-4. [Epub ahead of print]

PMID:
29895857
2.

Improving disease gene prioritization by comparing the semantic similarity of phenotypes in mice with those of human diseases.

Oellrich A, Hoehndorf R, Gkoutos GV, Rebholz-Schuhmann D.

PLoS One. 2012;7(6):e38937. doi: 10.1371/journal.pone.0038937. Epub 2012 Jun 14.

3.

Phrank measures phenotype sets similarity to greatly improve Mendelian diagnostic disease prioritization.

Jagadeesh KA, Birgmeier J, Guturu H, Deisseroth CA, Wenger AM, Bernstein JA, Bejerano G.

Genet Med. 2018 Jul 12. doi: 10.1038/s41436-018-0072-y. [Epub ahead of print]

PMID:
29997393
4.

ClinPhen extracts and prioritizes patient phenotypes directly from medical records to expedite genetic disease diagnosis.

Deisseroth CA, Birgmeier J, Bodle EE, Kohler JN, Matalon DR, Nazarenko Y, Genetti CA, Brownstein CA, Schmitz-Abe K, Schoch K, Cope H, Signer R; Undiagnosed Diseases Network, Martinez-Agosto JA, Shashi V, Beggs AH, Wheeler MT, Bernstein JA, Bejerano G.

Genet Med. 2018 Dec 5. doi: 10.1038/s41436-018-0381-1. [Epub ahead of print]

PMID:
30514889
5.

Clinical diagnostics in human genetics with semantic similarity searches in ontologies.

Köhler S, Schulz MH, Krawitz P, Bauer S, Dölken S, Ott CE, Mundlos C, Horn D, Mundlos S, Robinson PN.

Am J Hum Genet. 2009 Oct;85(4):457-64. doi: 10.1016/j.ajhg.2009.09.003.

6.

Linking human diseases to animal models using ontology-based phenotype annotation.

Washington NL, Haendel MA, Mungall CJ, Ashburner M, Westerfield M, Lewis SE.

PLoS Biol. 2009 Nov;7(11):e1000247. doi: 10.1371/journal.pbio.1000247. Epub 2009 Nov 24.

7.

GeneYenta: a phenotype-based rare disease case matching tool based on online dating algorithms for the acceleration of exome interpretation.

Gottlieb MM, Arenillas DJ, Maithripala S, Maurer ZD, Tarailo Graovac M, Armstrong L, Patel M, van Karnebeek C, Wasserman WW.

Hum Mutat. 2015 Apr;36(4):432-8. doi: 10.1002/humu.22772. Epub 2015 Mar 19.

PMID:
25703386
8.

Linking rare and common disease: mapping clinical disease-phenotypes to ontologies in therapeutic target validation.

Sarntivijai S, Vasant D, Jupp S, Saunders G, Bento AP, Gonzalez D, Betts J, Hasan S, Koscielny G, Dunham I, Parkinson H, Malone J.

J Biomed Semantics. 2016 Mar 23;7:8. doi: 10.1186/s13326-016-0051-7. eCollection 2016.

9.

A visual and curatorial approach to clinical variant prioritization and disease gene discovery in genome-wide diagnostics.

James RA, Campbell IM, Chen ES, Boone PM, Rao MA, Bainbridge MN, Lupski JR, Yang Y, Eng CM, Posey JE, Shaw CA.

Genome Med. 2016 Feb 2;8(1):13. doi: 10.1186/s13073-016-0261-8.

10.

A new method to measure the semantic similarity from query phenotypic abnormalities to diseases based on the human phenotype ontology.

Gong X, Jiang J, Duan Z, Lu H.

BMC Bioinformatics. 2018 May 8;19(Suppl 4):162. doi: 10.1186/s12859-018-2064-y.

11.

Text-mined phenotype annotation and vector-based similarity to improve identification of similar phenotypes and causative genes in monogenic disease patients.

Saklatvala JR, Dand N, Simpson MA.

Hum Mutat. 2018 May;39(5):643-652. doi: 10.1002/humu.23413. Epub 2018 Mar 15.

PMID:
29460986
12.

HPOSim: an R package for phenotypic similarity measure and enrichment analysis based on the human phenotype ontology.

Deng Y, Gao L, Wang B, Guo X.

PLoS One. 2015 Feb 9;10(2):e0115692. doi: 10.1371/journal.pone.0115692. eCollection 2015.

13.

Semantic Disease Gene Embeddings (SmuDGE): phenotype-based disease gene prioritization without phenotypes.

Alshahrani M, Hoehndorf R.

Bioinformatics. 2018 Sep 1;34(17):i901-i907. doi: 10.1093/bioinformatics/bty559.

14.

GeneMatcher: a matching tool for connecting investigators with an interest in the same gene.

Sobreira N, Schiettecatte F, Valle D, Hamosh A.

Hum Mutat. 2015 Oct;36(10):928-30. doi: 10.1002/humu.22844. Epub 2015 Aug 13.

15.

Use of model organism and disease databases to support matchmaking for human disease gene discovery.

Mungall CJ, Washington NL, Nguyen-Xuan J, Condit C, Smedley D, Köhler S, Groza T, Shefchek K, Hochheiser H, Robinson PN, Lewis SE, Haendel MA.

Hum Mutat. 2015 Oct;36(10):979-84. doi: 10.1002/humu.22857. Epub 2015 Sep 8.

16.

Clinical interpretation of CNVs with cross-species phenotype data.

Köhler S, Schoeneberg U, Czeschik JC, Doelken SC, Hehir-Kwa JY, Ibn-Salem J, Mungall CJ, Smedley D, Haendel MA, Robinson PN.

J Med Genet. 2014 Nov;51(11):766-772. doi: 10.1136/jmedgenet-2014-102633. Epub 2014 Oct 3.

17.

Querying phenotype-genotype relationships on patient datasets using semantic web technology: the example of Cerebrotendinous xanthomatosis.

Taboada M, Martínez D, Pilo B, Jiménez-Escrig A, Robinson PN, Sobrido MJ.

BMC Med Inform Decis Mak. 2012 Jul 31;12:78. doi: 10.1186/1472-6947-12-78.

18.

Construction and accessibility of a cross-species phenotype ontology along with gene annotations for biomedical research.

Köhler S, Doelken SC, Ruef BJ, Bauer S, Washington N, Westerfield M, Gkoutos G, Schofield P, Smedley D, Lewis SE, Robinson PN, Mungall CJ.

Version 2. F1000Res. 2013 Feb 1 [revised 2014 Jan 1];2:30. doi: 10.12688/f1000research.2-30.v2. eCollection 2013.

19.

An ontology for Autism Spectrum Disorder (ASD) to infer ASD phenotypes from Autism Diagnostic Interview-Revised data.

Mugzach O, Peleg M, Bagley SC, Guter SJ, Cook EH, Altman RB.

J Biomed Inform. 2015 Aug;56:333-47. doi: 10.1016/j.jbi.2015.06.026. Epub 2015 Jul 4.

20.

Computer-assisted initial diagnosis of rare diseases.

Alves R, Piñol M, Vilaplana J, Teixidó I, Cruz J, Comas J, Vilaprinyo E, Sorribas A, Solsona F.

PeerJ. 2016 Jul 21;4:e2211. doi: 10.7717/peerj.2211. eCollection 2016.

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