Microarray data classification using inductive logic programming and gene ontology background information

Journal of Chemometrics

Volumn 24, Issue 5, 2010, Pages 231-240

  Ryeng, Einar ^a   Alsberg, Bjørn Kåre ^a  

^a NORWEGIAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Norway)

Author keywords

Bioinformatics; Gene ontology; Inductive logic programming; Microarray

Indexed keywords

COMPUTER CIRCUITS; GENE ONTOLOGY; GENES; INDUCTIVE LOGIC PROGRAMMING (ILP); LEARNING SYSTEMS;

BACKGROUND INFORMATION; CLASSIFICATION RULES; DATA CLASSIFICATION; GENE ONTOLOGY; GENE ONTOLOGY ANNOTATIONS; INDUCTIVE LOGIC; INDUCTIVE LOGIC PROGRAMMING; LOGIC-PROGRAMMING; MACHINE-LEARNING; MICROARRAYS DATA;

CLASSIFICATION (OF INFORMATION);

EID: 77952627785     PISSN: 08869383     EISSN: 1099128X     Source Type: Journal    
DOI: 10.1002/cem.1263     Document Type: Article

References (32)

1. The Gene Ontology Consortium. Gene ontology: tool for the unification of biology. Nat. Genet. 2000; 25: 25-29.
2. Smith B, Williams J, Shulze-Kremer S. The ontology of the gene ontology. In American Medical Informatics Association 2003 Symposium Proceedings, 2003, 609-613.
3. Wroe CJ, Stevens R, Goble CA, Ashburner M. A methodology to migrate the gene ontology to a description logic environment using DAML+OIL. Pac. Symp. Biocomput. 2003; 8: 624-635.
4. Shegogue D, Zhen WJ. Integration of the gene ontology into an object-oriented architecture. BMC Bioinf. 2005; 6: 113.
5. Camon E, Magrane M, Barrell D, Lee V, Dimmer E, Maslen J, Binns D, Harte N, Lopez R, Apweiler R. The gene ontology annotation (GOA) database: sharing knowledge in uniprot with gene ontology. Nucleic Acids Res. 2004; 32: D262-D266.
6. Nienhuys-Cheng SH, de Wolf R. Foundations of Inductive Logic Programming. Springer Verlag, Berlin, 1997.
7. Quinlan JR. C4. 5: Programs for Machine Learning. Morgan Kaufmann, CA, USA, 1993.
8. Buttingsrud B, Ryeng E, King RD, Alsberg BK. Representation of molecular structure using quantum topology with inductive logic programming in structure-activity relationships. J. Comput.-Aided Mol. Des. 2006; 20: 361-373.
9. King RD, Muggleton S, Sternberg MJE. Drug design by machine learning: the use of inductive logic programming to model the structureactivity relationships of trimethoprim analogues binding to dihydro-folate reductase. Proc. Nat. Acad. Sci. 1992; 89(23): 11322-11326.
10. King RD, Srinivasan A, Dehaspe L. Warmr: a data mining tool for chemical data. J. Comp. Aid. Mol. Des 2001; 15(2): 173-181.
11. Ando HY, Dehaspe L, Luyten W, van Craenenbroeck E, Vandecasteele H, van Meervelt L. Discovering H-bonding rules in crystals with inductive logic programming. Mol. Pharm. 2006; 3(6): 665-674.
12. Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, Paulovich A, Pomeroy SL, Golub TR, Lander ES, Mesirov JP. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Nat. Acad. Sci. 2005; 102: 15545-15550.
13. Tran TN, Satou K, Ho TB. Using inductive logic programming for predicting protein-protein interactions from multiple genomic data. 9th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD), Springer LNAI, 2005; 3721: 321-330.
14. King RD. Applying inductive logic programming to predicting gene function. AI Mag. 2004; 25(1): 57-68.
15. Badea L. Functional discrimination of gene expression patterns in terms of the gene ontology. Proc. Pac. Symp. Biocomp. 2003; 8: 565-576.
16. Muggleton S, de Raedt L. Inductive logic programming: theory and methods. J. Logic Program. 1994; 19,20: 629-679.
17. Srinivasan A. Aleph: a learning engine for proposing hypothesis. Available at: http://www.web.comlab.ox.ac.uk/oucl/research/areas/machl
18. Quinlan JR, Cameron-Jones RM. FOIL: Amidterm report. In Proceedings of ECML, 1993; 3-20.
19. Muggleton S. Inverse entailment and progol. New Generat. Comput. 1995; 13: 245-286.
20. Spira A, Beane J, Shah V, Liu G, Schembri F, Yang X, Palma J, Brody JS. The effect of sigarette smoke on the human airway epithelial cell transcriptome. Proc. Nat. Acad. Sci. USA, 2004; 101: 10143-10148.
21. Affymetrix. Data Sheet: Genechip Human Genome U133 Arrays.
22. Tusher VG, Tibshirani R, Chu G. Significance analysis of microarrays applied to the ionizing radiation response. Proc. Natl. Acad. Sci. USA 2004; 98(9): 5116-5121.
23. Helmersson J, Larsson A, Vessby B, Basu S. Active smoking and a history of smoking are associated with enhanced prostaglandin F2 {ogonek}, interleukin-6 and F2-isoprostane formation in elderly men. Atherosclerosis 2005; 181: 201-207.
24. Kitamura S. Effects of cigarette smoking on metabolic events in the lung. Environ. Health Perspect. 1987; 72: 283-296.
25. Willey JC, Coy EL, Frampton MW, Torres A, Apostolakos MJ, Hoehn G, Schuermann WH, Thilly WG, Olson DE, Hammersley JR, Crespi CL, Utell MJ. Quantitative RT-PCR mearurement of cytochromes p450 1A1, 1B1 and 2B7, microsomal epoxide hydrolase and NADPH oxidoreductase expression in lung cells of smokers and nonsmokers. Am. J. Respir. Cell. Mol. Biol. 1997; 17: 114-124.
26. Gidskehaug L, Anderssen E, Flatberg A, Alsberg BK. A framework for significance analysis of gene expression data using dimension reduction methods. BMC Bioinf. 2007; 8: 346.
27. Kuriakose MA, Chen WT, He ZM, Sikora AG, Zhang P, Zhang ZY, Qiu WL, Hsu DF, McMunn-Coffran C, Brown SM, Elango EM, Delacure MD, Chen FA. Selection and validation of differentially expressed genes in head and neck cancer. Cell. Mol. Life Sci. 2004; 61: 1372-1383.
28. Affymetrix. Data Sheet: Genechip Human Genome U95 Set.
29. Hoskuldsson A. PLS regression methods. J. Chemometr. 1988; 2(3): 211-228.
30. Amit I, Citri A, Shay T, Lu Y, Katz M, Zhang F, Tarcic G, Siwak D, Lahad J, Jacob-Hirsch J, Amariglio N, Vaisman N, Segal E, Rechavi G, Alon U, Mills GB, Domany E, Yarden Y. A module of negative feedback regulators defines growth factor signaling. Nat. Genet. 2007; 39(4): 503-512.
31. Kanehisa M, Goto S. KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 2000; 28(1): 27-30.
32. Masys DR, Welsh JB, Fink JL, Gribskov M, Klacansky I, Corbeil J. Use of keyword hierarchies to interpret gene expression patterns. Bioinformatics 2001; 17(4): 319-326.