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Items: 16

1.

An overview of the BioCreative 2012 Workshop Track III: interactive text mining task.

Arighi CN, Carterette B, Cohen KB, Krallinger M, Wilbur WJ, Fey P, Dodson R, Cooper L, Van Slyke CE, Dahdul W, Mabee P, Li D, Harris B, Gillespie M, Jimenez S, Roberts P, Matthews L, Becker K, Drabkin H, Bello S, Licata L, Chatr-aryamontri A, Schaeffer ML, Park J, Haendel M, Van Auken K, Li Y, Chan J, Muller HM, Cui H, Balhoff JP, Chi-Yang Wu J, Lu Z, Wei CH, Tudor CO, Raja K, Subramani S, Natarajan J, Cejuela JM, Dubey P, Wu C.

Database (Oxford). 2013 Jan 17;2013:bas056. doi: 10.1093/database/bas056. Print 2013.

2.

MeInfoText 2.0: gene methylation and cancer relation extraction from biomedical literature.

Fang YC, Lai PT, Dai HJ, Hsu WL.

BMC Bioinformatics. 2011 Dec 14;12:471. doi: 10.1186/1471-2105-12-471.

3.

Integration of gene normalization stages and co-reference resolution using a Markov logic network.

Dai HJ, Chang YC, Tsai RT, Hsu WL.

Bioinformatics. 2011 Sep 15;27(18):2586-94. doi: 10.1093/bioinformatics/btr358. Epub 2011 Jun 17.

4.

Multistage gene normalization and SVM-based ranking for protein interactor extraction in full-text articles.

Dai HJ, Lai PT, Tsai RT.

IEEE/ACM Trans Comput Biol Bioinform. 2010 Jul-Sep;7(3):412-20. doi: 10.1109/TCBB.2010.45.

PMID:
20479501
5.

HypertenGene: extracting key hypertension genes from biomedical literature with position and automatically-generated template features.

Tsai RT, Lai PT, Dai HJ, Huang CH, Bow YY, Chang YC, Pan WH, Hsu WL.

BMC Bioinformatics. 2009 Dec 3;10 Suppl 15:S9. doi: 10.1186/1471-2105-10-S15-S9.

6.

TCMGeneDIT: a database for associated traditional Chinese medicine, gene and disease information using text mining.

Fang YC, Huang HC, Chen HH, Juan HF.

BMC Complement Altern Med. 2008 Oct 14;8:58. doi: 10.1186/1472-6882-8-58.

7.

Proteomics in diabetes research.

Sundsten T, Ortsäter H.

Mol Cell Endocrinol. 2009 Jan 15;297(1-2):93-103. doi: 10.1016/j.mce.2008.06.018. Epub 2008 Jul 9. Review.

PMID:
18657591
8.

T2D-Db: an integrated platform to study the molecular basis of Type 2 diabetes.

Agrawal S, Dimitrova N, Nathan P, Udayakumar K, Lakshmi SS, Sriram S, Manjusha N, Sengupta U.

BMC Genomics. 2008 Jul 7;9:320. doi: 10.1186/1471-2164-9-320.

9.

Microarray technology and applications in the arena of genome-wide association.

Grant SF, Hakonarson H.

Clin Chem. 2008 Jul;54(7):1116-24. doi: 10.1373/clinchem.2008.105395. Epub 2008 May 22. Review.

10.

PubMeth: a cancer methylation database combining text-mining and expert annotation.

Ongenaert M, Van Neste L, De Meyer T, Menschaert G, Bekaert S, Van Criekinge W.

Nucleic Acids Res. 2008 Jan;36(Database issue):D842-6. Epub 2007 Oct 11.

11.

Text mining: powering the database revolution.

Hahn U, Wermter J, Blasczyk R, Horn PA.

Nature. 2007 Jul 12;448(7150):130. No abstract available.

PMID:
17625544
12.

T1DBase: integration and presentation of complex data for type 1 diabetes research.

Hulbert EM, Smink LJ, Adlem EC, Allen JE, Burdick DB, Burren OS, Cassen VM, Cavnor CC, Dolman GE, Flamez D, Friery KF, Healy BC, Killcoyne SA, Kutlu B, Schuilenburg H, Walker NM, Mychaleckyj J, Eizirik DL, Wicker LS, Todd JA, Goodman N.

Nucleic Acids Res. 2007 Jan;35(Database issue):D742-6. Epub 2006 Dec 14. Erratum in: Nucleic Acids Res. 2007;35(18):6338. Cassen, Victor M [added].

13.

The human obesity gene map: the 2005 update.

Rankinen T, Zuberi A, Chagnon YC, Weisnagel SJ, Argyropoulos G, Walts B, Pérusse L, Bouchard C.

Obesity (Silver Spring). 2006 Apr;14(4):529-644. Review.

14.

SNPs3D: candidate gene and SNP selection for association studies.

Yue P, Melamud E, Moult J.

BMC Bioinformatics. 2006 Mar 22;7:166.

15.

The genetic association database.

Becker KG, Barnes KC, Bright TJ, Wang SA.

Nat Genet. 2004 May;36(5):431-2. No abstract available.

PMID:
15118671
16.
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