Gene selection via discretized gene-expression profiles and greedy feature-elimination

Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)

Volumn 3025, Issue , 2004, Pages 256-266

  Potamias, George ^a   Koumakis, Lefteris ^a   Moustakis, Vassilis ^a,b  

^a INSTITUTE OF COMPUTER SCIENCE   (Greece)

^b TECHNICAL UNIVERSITY OF CRETE   (Greece)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; FUNCTIONS; GENES; PROBLEM SOLVING; SAMPLING; SET THEORY; ARTIFICIAL INTELLIGENCE;

FEATURE-ELIMINATION; GENE SELECTION; GENOMICS; RANK-ORDERED GENES; DISCRETIZATIONS; FEATURE ELIMINATION ALGORITHM; GENE EXPRESSION PROFILES; GENE EXPRESSION STUDIES; GENE RANKING; GENETIC BASIS; NUMBER OF SAMPLES;

FEATURE EXTRACTION; GENE EXPRESSION;

EID: 9444245024     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/978-3-540-24674-9_27     Document Type: Conference Paper

References (21)

1. Alizadeh, A.A., et al.: Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature 403:3 (2000) 503-511.
2. Baim, P.W.: A Method for Attribute Selection in Inductive Learning Systems. IEEE PAMI, 10: 6 (1988) 888-896.
3. Bassett, D.E., Eisen, M.B., Boguski, M.S.: Gene expression informatics: it's all in your mine. Nature Genetics 21, Supplement 1 (1999) 51-55.
4. Brazma, A., Parkinson, H., Schlitt, T., Shojatalab, M.: A quick introduction to elements of biology - cells, molecules, genes, functional genomics, microarrays. EMBL- European Bioinformatics Institute (EBI), (October 2001). [http://www.ebi.ac.uk/microarray/biology_intro.html; accessed October 2003]
5. Fayyad, U., Irani, K. Multi-interval discretization of continuous-valued attributes for classification learning. Procs of the 13th Inernational Joint Conference of Artificial Intelligence. Morgan Kaufmann, San Francisco, CA (1993) 1022-1029.
6. Friend, H.F.: How DNA microarrays and expression profiling will affect clinical practice. Br Med J 319 (1999) 1-2.
7. Ginsburg, G.S., McCarthy, J.J.: Personalized medicine: revolutionizing drug discovery and patient care. Trends Biotechnol 19:12 (2001) 491-496.
8. Golub, T.R., Slonim, D.K., Tamayo, P., Huard, C., Gaasenbeek, M., Mesirov, J.P., Coller, H., Loh, M.L., Downing, J.R., Caligiuri, M.A., Bloomfield, C.D., Lander, E.S.: Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science 286 (199) 531-537.
9. Guttmacher, A.E., Collins, F.S.: Genome Medicine. Special issue of N Engl Med 349 (2003).
10. Hall, M.A.: Correlation-based Feature Selection for Machine Learning. PhD thesis, University of Waikato (1999).
11. Hedenfalk, I., et al.: Gene-expression profiles in hereditary breast cancer. N Engl J Med. 344:8 (2001) 539-548.
12. Kinzler, K.W., Vogelstein, B.: Lessons from hereditary colorectal cancer. Cell 87:2 (1996) 159-170.
13. Kohane, I.S.: Bioinformatics and Clinical Informatics: The Imperative to Collaborate. JAMIA 7 (2000) 512-516.
14. Kohavi, R., John, G.: Wrappers for feature subset selection. Artificial Intelligence (special issue on Relevance) 97:1-2 (1996) 273-324.
15. Li, L., Weinberg, C.R., Darden, T.A., Pedersen, L.G.: Gene selection for sample classification based on gene expression data: study of sensitivity to choice of parameters of the GA/KNN method. Bioinformatics 17:12 (2001) 1131-1142.
16. Maojo, V., Iakovidis, I., Martín-Sánchez, F., Crespo, J., Kulikoswki. C.: Medical Informatics and Bioinformatics: European efforts to facilitate synergy. Journal of Biomedical Informatics 34:6 (2001) 423-427.
17. Nadon, R., Shoemaker, J.: Statistical issues with microarrays: Processing and analysis. Trends in Genetics, 15 (2002) 265-271.
18. Pomeroy, S.L., et al.: Prediction of central nervous system embryonal tumour outcome based on gene expression. Nature 415 (2002) 436-442.
19. Potamias, G.: Utilizing Gene Functional Classification in Microarray Data Analysis: a Hybrid Clustering Approach. 9th Panhellenic Conference in Informatics, 21-23 November, Thessaloniki, Greece (2003).
20. Quinlan, J.R.: Induction of decision trees. Machine Learning, 1:81 (1986) 81-106.
21. Su, A.I., et al.: Molecular Classification of Human Carcinomas by Use of Gene Expression Signatures. Cancer Research 61 (2001) 7388-7399.