138 related articles for article (PubMed ID: 24788269)
1. Integrative literature and data mining to rank disease candidate genes.
Wu C; Zhu C; Jegga AG
Methods Mol Biol; 2014; 1159():207-26. PubMed ID: 24788269
[TBL] [Abstract][Full Text] [Related]
2. Candidate gene discovery and prioritization in rare diseases.
Jegga AG
Methods Mol Biol; 2014; 1168():295-312. PubMed ID: 24870143
[TBL] [Abstract][Full Text] [Related]
3. Recent approaches to the prioritization of candidate disease genes.
Doncheva NT; Kacprowski T; Albrecht M
Wiley Interdiscip Rev Syst Biol Med; 2012; 4(5):429-42. PubMed ID: 22689539
[TBL] [Abstract][Full Text] [Related]
4. Integrative data mining highlights candidate genes for monogenic myopathies.
Abath Neto O; Tassy O; Biancalana V; Zanoteli E; Pourquié O; Laporte J
PLoS One; 2014; 9(10):e110888. PubMed ID: 25353622
[TBL] [Abstract][Full Text] [Related]
5. Prioritization of candidate genes for periodontitis using multiple computational tools.
Zhan Y; Zhang R; Lv H; Song X; Xu X; Chai L; Lv W; Shang Z; Jiang Y; Zhang R
J Periodontol; 2014 Aug; 85(8):1059-69. PubMed ID: 24476546
[TBL] [Abstract][Full Text] [Related]
6. Phenotype mining for functional genomics and gene discovery.
Groth P; Leser U; Weiss B
Methods Mol Biol; 2011; 760():159-73. PubMed ID: 21779996
[TBL] [Abstract][Full Text] [Related]
7. Prediction of drug gene associations via ontological profile similarity with application to drug repositioning.
Kissa M; Tsatsaronis G; Schroeder M
Methods; 2015 Mar; 74():71-82. PubMed ID: 25498216
[TBL] [Abstract][Full Text] [Related]
8. Analysis of biological processes and diseases using text mining approaches.
Krallinger M; Leitner F; Valencia A
Methods Mol Biol; 2010; 593():341-82. PubMed ID: 19957157
[TBL] [Abstract][Full Text] [Related]
9. Conceptual thinking for in silico prioritization of candidate disease genes.
Tiffin N
Methods Mol Biol; 2011; 760():175-87. PubMed ID: 21779997
[TBL] [Abstract][Full Text] [Related]
10. A prioritization analysis of disease association by data-mining of functional annotation of human genes.
Taniya T; Tanaka S; Yamaguchi-Kabata Y; Hanaoka H; Yamasaki C; Maekawa H; Barrero RA; Lenhard B; Datta MW; Shimoyama M; Bumgarner R; Chakraborty R; Hopkinson I; Jia L; Hide W; Auffray C; Minoshima S; Imanishi T; Gojobori T
Genomics; 2012 Jan; 99(1):1-9. PubMed ID: 22019378
[TBL] [Abstract][Full Text] [Related]
11. Combining literature text mining with microarray data: advances for system biology modeling.
Faro A; Giordano D; Spampinato C
Brief Bioinform; 2012 Jan; 13(1):61-82. PubMed ID: 21677032
[TBL] [Abstract][Full Text] [Related]
12. Functional genomics and proteomics in the clinical neurosciences: data mining and bioinformatics.
Phan JH; Quo CF; Wang MD
Prog Brain Res; 2006; 158():83-108. PubMed ID: 17027692
[TBL] [Abstract][Full Text] [Related]
13. Gelsius: a literature-based workflow for determining quantitative associations between genes and biological processes.
Abate F; Acquaviva A; Ficarra E; Piva R; Macii E
IEEE/ACM Trans Comput Biol Bioinform; 2013; 10(3):619-31. PubMed ID: 24091396
[TBL] [Abstract][Full Text] [Related]
14. Mining emerging biomedical literature for understanding disease associations in drug discovery.
Rajpal DK; Qu XA; Freudenberg JM; Kumar VD
Methods Mol Biol; 2014; 1159():171-206. PubMed ID: 24788268
[TBL] [Abstract][Full Text] [Related]
15. The prediction of candidate genes for cervix related cancer through gene ontology and graph theoretical approach.
Hindumathi V; Kranthi T; Rao SB; Manimaran P
Mol Biosyst; 2014 Jun; 10(6):1450-60. PubMed ID: 24647578
[TBL] [Abstract][Full Text] [Related]
16. Text mining in livestock animal science: introducing the potential of text mining to animal sciences.
Sahadevan S; Hofmann-Apitius M; Schellander K; Tesfaye D; Fluck J; Friedrich CM
J Anim Sci; 2012 Oct; 90(10):3666-76. PubMed ID: 22665627
[TBL] [Abstract][Full Text] [Related]
17. Integrative mining of traditional Chinese medicine literature and MEDLINE for functional gene networks.
Zhou X; Liu B; Wu Z; Feng Y
Artif Intell Med; 2007 Oct; 41(2):87-104. PubMed ID: 17804209
[TBL] [Abstract][Full Text] [Related]
18. Contribution of genomics to the understanding of physiological functions.
Hocquette JF; Cassar-Malek I; Scalbert A; Guillou F
J Physiol Pharmacol; 2009 Oct; 60 Suppl 3():5-16. PubMed ID: 19996478
[TBL] [Abstract][Full Text] [Related]
19. Web tools for the prioritization of candidate disease genes.
Oti M; Ballouz S; Wouters MA
Methods Mol Biol; 2011; 760():189-206. PubMed ID: 21779998
[TBL] [Abstract][Full Text] [Related]
20. Prioritization of candidate disease genes by enlarging the seed set and fusing information of the network topology and gene expression.
Zhang SW; Shao DD; Zhang SY; Wang YB
Mol Biosyst; 2014 Jun; 10(6):1400-8. PubMed ID: 24695957
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]