Systems literature analysis

Pharmacogenomics

Volumn 5, Issue 7, 2004, Pages 943-947

  Persidis, Andreas ^a   Deftereos, Spyros ^a   Persidis, Aris ^b  

^a Biovista   (Greece)

^b Biovista Inc   (United States)

Author keywords

Database; Literature analysis; Systems biology; Target discovery; Text mining

Indexed keywords

CORTICOTROPIN RELEASING FACTOR; FISH OIL; PHOSPHOLIPASE A2; TRANSCRIPTION FACTOR AP 1;

ARTICLE; ARTIFICIAL NEURAL NETWORK; BIPOLAR DISORDER; CLINICAL GENETICS; CLINICAL RESEARCH; CLINICAL TRIAL; COMPUTER MODEL; COMPUTER PROGRAM; DEPRESSION; EXPERIMENTAL DESIGN; FACTUAL DATABASE; GENE EXPRESSION PROFILING; GENETIC DATABASE; GENETIC LINKAGE; GENETIC PARAMETERS; HUMAN; IMMUNOPATHOGENESIS; MEDICAL INFORMATICS; MEDICAL LITERATURE; ONLINE SYSTEM; PHARMACOGENETICS; PHENOTYPE; RAYNAUD PHENOMENON; RHEUMATOID ARTHRITIS; SCHIZOPHRENIA; SYSTEM ANALYSIS; SYSTEMIC LUPUS ERYTHEMATOSUS; VALIDATION PROCESS;

DATABASES, BIBLIOGRAPHIC; PHARMACOGENETICS; SYSTEMS BIOLOGY;

EID: 6344256948     PISSN: 14622416     EISSN: None     Source Type: Journal    
DOI: 10.1517/14622416.5.7.943     Document Type: Article

References (18)

1. Grivell L: Mining the bibliome: searching for a needle in a haystack? EMBO Rep. 3(31), 200-203 (2002).
2. Kitano H: Systems biology: a brief overview. Science 295, 1662 (2002).
3. Swanson DR: Fish oil, Raynaud's syndrome, and undiscovered public knowledge. Perspect. Biol. Med. 30(1), 7-18 (1986).
4. Srinivasan P, Libbus B: Mining MEDLINE for implicit links between dietary substances and diseases. Bioinformatics 20(Suppl. 1), I290-I296 (2004).
5. Zhang Z, Ng SK: InterWeaver: interaction reports for discovering potential protein interaction partners with online evidence. Nucleic Acids Res. 1, 32 (2004).
6. Crasto CJ, Marenco LN, Migliore M et al.: Text mining neuroscience journal articles to populate neuroscience databases. Neuroinformatics 1(3), 215-237 (2003).
7. Jenssen TK, Laegreid A, Komorowski J, Hovig E: A literature network of human genes for high-throughput analysis of gene expression. Nat. Genet. 28(1), 21-28 (2001).
8. Pittman J, Huang E, Dressman H et al.: Integrated modeling of clinical and gene expression information for personalized prediction of disease outcomes. Proc. Natl. Acad. Sci. USA 101(22 , 8431-8436 (2004).
9. Nevins JR, Huang ES, Dressman H, Pittman J, Huang AT, West M: Towards integrated clinico-genomic models for personalized medicine: combining gene expression signatures and clinical factors in breast cancer outcomes prediction. Hum. Mol. Genet. 12(Spec. No. 2), R153-R157 (2003).
10. Pan H, Zuo L, Choudhary et al.: Dragon TF Association Miner: a system for exploring transcription factor associations through text-mining. Nucleic Acids Res. 32(Web Server issue), W230-W234 (2004).
11. Chen C: Searching for intellectual turning points: progressive knowledge domain visualization. Proc. Natl. Acad. Sci. USA 101(Suppl. 1), 5303-5310 (2004).
12. White HD, Lin X, Buzydlowski JW, Chen C: User-controlled mapping of significant literatures. Proc. Natl. Acad. Sci. USA 101(Suppl. 1), 5297-5302 (2004).
13. Chaussabel D, Sher A: Mining microarray expression data by literature profiling Genome Biol. 3(10), RESEARCH0055 (2002).
14. Hakenberg J, Schmeier S, Kowald A, Klipp E, Leser U: Finding kinetic parameters using text mining. OMICS 8(2), 131-152 (2004).
15. Tanabe L, Scherf U, Smith LH: MedMiner: an Internet text-mining tool for biomedical information, with application to gene expression profiling. Biotechniques 27(6), 1210-1214, 1216-1217 (1999).
16. Karpinets TV, Foy BD, Frazier JM: Tailored gene array databases: applications in mechanistic toxicology. Bioinformatics 20(4), 507-517 (2004).
17. Hewett M, Oliver DE, Rubin DL et al.: PharmGKB: the Pharmacogenetics Knowledge Base. Nucleic Acids Res. 30(1), 163-165 (2002).
18. Frauenfelder M: A smarter web. MIT Technol. Rev. Nov. issue, 52-58 (2001).