Integrating phenotype and gene expression data for predicting gene function

BMC Bioinformatics

Volumn 10, Issue SUPPL. 11, 2009, Pages

  Malone, Brandon M ^a,b   Perkins, Andy D ^a,b   Bridges, Susan M ^a,b  

^a MISSISSIPPI STATE UNIVERSITY   (United States)

^b MISSISSIPPI STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DATA INTEGRATION; FORECASTING; YEAST;

F MEASURE; FUNCTIONAL ANNOTATION; GENE EXPRESSION DATA; GENE FUNCTION; GENE ONTOLOGY; INTEGRATED APPROACH;

GENE EXPRESSION;

ACCURACY; ALGORITHM; ARTICLE; CONTROLLED STUDY; GENE EXPRESSION; GENE FUNCTION; NONHUMAN; NUCLEOTIDE SEQUENCE; PHENOTYPE; PREDICTION; SACCHAROMYCES CEREVISIAE;

SACCHAROMYCES CEREVISIAE;

EID: 70449389289     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-10-S11-S20     Document Type: Article

References (20)

1. Ashburner M. Gene Ontology: Tool for the Unification of Biology. Nature Genetics 2000, 25:25-29.
2. Barrell D. The GOA database in 2009 - an integrated Gene Ontology Annotation resource. Nucleic Acids Res 2009, (37 Database):D396-403. 2686469, 18957448.
3. Huang DW, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc 2009, 4(1):44-57.
4. In-Yee L, Jan-Ming H, Ming-Syan C. CLUGO: a clustering algorithm for automated functional annotations based on gene ontology. Data Mining, Fifth IEEE International Conference on 2005,
5. Daraselia N. Automatic extraction of gene ontology annotation and its correlation with clusters in protein networks. BMC Bioinformatics 2007, 8(1):243. 1940026, 17620146.
6. Groth P. PhenomicDB: a new cross-species genotype/phenotype resource. Nucleic Acids Research 2007, (35 Database):D696-699. 1781118, 16982638.
7. Groth P, Weiss B. Phenotype Data: A Neglected Resource in Biomedical Research?. Current Bioinformatics 2006, 1(3):347-358.
8. Groth P. Mining phenotypes for gene function prediction. BMC Bioinformatics 2008, 9(1):136. 2311305, 18315868.
9. Massjouni N, Rivera CG, Murali TM. VIRGO: computational prediction of gene functions. Nucleic Acids Res 2006, (34 Web Server):W340-4. 1538839, 16845022.
10. Karaoz U. Whole-genome annotation by using evidence integration in functional-linkage networks. Proc Natl Acad Sci USA 2004, 101(9):2888-93. 365715, 14981259.
11. Rodgers J, Nicewander A. Thirteen Ways to Look at the Correlation Coefficient. The American Statistician 1998, 42(1):59-66.
12. Wren JD. A global meta-analysis of microarray expression data to predict unknown gene functions and estimate the literature-data divide. Bioinformatics 2009, 25(13):1694-701.
13. Zhao Y, Karypis G. Data clustering in life sciences. Molecular Biotechnology 2005, 31(1):55-80.
14. Cawley GC, Talbot NLC. Fast exact leave-one-out cross-validation of sparse least-squares support vector machines. Neural Netw 2004, 17(10):1467-1475.
15. NCBI Gene Expression Omnibus. 2009, [cited May 2009];., http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GPL1914
16. Rosetta Biosoftware Rosetta Resolver System. 2009, [cited May 2009]., http://www.rosettabio.com/products/resolver
17. Affymetrix Annotation Server. 2009,
18. Kahraman A. PhenomicDB: a multi-species genotype/phenotype database for comparative phenomics. Bioinformatics 2005, 21(3):418-420.
19. Steinbach M, Karypis G, Kumar V. A Comparison of Document Clustering Techniques. Proceedings of the International KDD Workshop on Text Mining 2000,
20. Ashburner M, Lewis S. On ontologies for biologists: the Gene Ontology - untangling the web. Novartis Found Symp 2002, 247:66-80. discussion 80-3, 84-90, 244-52..