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Yearb Med Inform 2006; 15(01): 105-106
DOI: 10.1055/s-0038-1638511
DOI: 10.1055/s-0038-1638511
Best paper selection
Section 7: Bioinformatics
Weitere Informationen
Publikationsverlauf
Publikationsdatum:
12. März 2018 (online)
- 1 Baumgartner C, Bohm C, Baumgartner D, Marini G, Weinberger K, Olgemoller B. et al. Supervised Machine Learning Techniques for the Classification of Metabolic Disorders in Newborns. Bioinformatics 2004; Nov 22; 20 (17) 2985-96 http://dx.doi.org/10.1093/bioinformatics/bth343.
- 2 Hauser ER, Crossman DC, Granger CB, Haines JL, Jones CJ, Mooser V. et al. A Genomewide Scan for Early-onset Coronary Artery Disease in 438 Families: The GENECARD Study. Am J Hum Genet 2004; Sep; 75 (03) 436-47 http://dx.doi.org/10.1086/423900.
- 3 Hristovski D, Peterlin B, Mitchell JA, Humphrey SM. Using Literature-based Discovery to Identify Disease Candidate Genes. Int J Med Inform 2005; Mar; 74 (2-4): 289-98 http://dx.doi.org/10.1016/j.ijmedinf.2004.04.024.
- 4 Koike A, Niwa Y, Takagi T. Automatic Extraction of Gene/Protein Biological Functions from Biomedical Text. Bioinformatics 2005; Apr 1; 21 (07) 1227-36 http://dx.doi.org/10.1093/bioinformatics/bti084.
- 5 Tiffin N, Kelso JF, Powell AR, Pan H, Bajic VB, Hide WA. Integration of Text- and Data-mining Using Ontologies Successfully Selects Disease Gene Candidates. Nucleic Acids Res 2005; Mar 14; 33 (05) 1544-52 http://dx.doi.org/10.1093/nar/gki296.