Adaptive neural network-based clustering of yeast protein-protein interactions

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3356, Issue , 2004, Pages 49-57

  Eom, Jae Hong ^a   Zhang, Byoung Tak ^a  

^a South Korea   (South Korea)

Author keywords

[No Author keywords available]

Indexed keywords

ARTS COMPUTING; CLUSTER ANALYSIS; FEATURE EXTRACTION; GROUP THEORY; INFORMATION THEORY; NEURAL NETWORKS; PROTEINS; YEAST;

ADAPTIVE NEURAL NETWORKS; CLUSTER PROTOTYPE; CLUSTER QUALITIES; CLUSTERING ACCURACY; FEATURE SELECTION FILTERS; K-MEANS CLUSTERING METHOD; PROTEIN INTERACTION; PROTEIN-PROTEIN INTERACTIONS;

K-MEANS CLUSTERING;

EID: 33646262687     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-30561-3_6     Document Type: Article

References (20)

1. Goffeau, A. , Barrell, B. G. ,et al: Life with 6000 genes. Science 274 (1996) 546-67.
2. Eisen, M. B. , Spellman, P. T. ,et al.: Cluster analysis and display of genomewide expression patterns. Proc. Natl. Acad. Sci. USA 95 (1998) 14863-68.
3. Pavlidis, P. andWeston, J.: Gene functional classification from heterogeneous data. In Proceedings of the 5th International Conference on Computational Molecular Biology (RECOMB-2001) (2001) 249-55.
4. Park, J. , Lappe, M. ,et al.: Mapping protein family interactions: intra-molecular and intermolecular protein family interaction repertoires in the PDB and yeast. J. Mol. Biol. 307 (2001) 929-39.
5. Iossifov, I. , Krauthammer, M. ,et al. Probabilistic inference of molecular networks from noisy data sources. Bioinformatics 20(8) (2004) 1205-13.
6. Ng, S. K. , Zhang, Z. ,et al. Integrative approach for computationally inferring protein domain interactions. Bioinfonnatics 19(8) (2003) 923-29.
7. Eom, J. -H. , Chang, J. -H. ,et al.: Prediction of implicit protein-protein interaction by optimal associative feature mining. Proceedings of the 5th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL'04), (2004) 85-91.
8. Carpenter, G. A. and Grossberg, S.: A massively parallel architecture for a self-organizing neural pattern recognition machine. Computer Vision, Graphics and Image Processing 37 (1987)54-115.
9. Barbara, M.: ART1 and pattern clustering. Proceedings of the 1988 connectionist models summer 1988. Morgan Kaufmann (1988) 174-85.
10. Heins, L. G. and Tauritz, D. R.: Adaptive resonance theory (ART): an introduction. Internal Report 95-35, Dept. of Computer Science, Leiden University, Netherlands (1995) 174-85.
11. Mewes, H. W. , Amid, C. ,et al.: MIPS: analysis and annotation of proteins from whole genomes. Nucleic Acids Res. 32(1) (2004) D41-44.
12. Christie, K. R. , Weng, S. ,et al.: Saccharomyces Genome Database (SGD) provides tools to identify and analyze sequences from Saccharomyces cerevisiae and related sequences from other organisms. Nucleic Acids Res. 32(1) (2004) D311-14.
13. Rangarajan, S. K. , Phoha, V. V. ,et al.: Adaptive neural network clustering of web users. IEEE Computer 37(4) (2004) 34-40.
14. Yu, L. and Liu, H.: Feature selection for high dimensional data: a fast correlation-based filter solution. In Proceedings of the 12th International Conference on Machine Learning (ICML'2003), (2003) 856-863.
15. Csank, C. , Costanzo, M. C. ,et al.: Three yeast proteome databases: YPD, PombePD, and CalPD (MycoPathPD). Methods Enzymol. 350 (2002) 347-73.
16. Ito, T. , Chiba, T. ,et al.: A comprehensive two-hybrid analysis to explore the yeast protein interactome. Proc. Natl. Acad. Sci. USA 98 (2001) 4569-4574.
17. Uetz, P. , Giot, L. ,et al.: A comprehensive analysis of protein-protein interactions in Saccharomyces cerevisiae. Nature 403 (2000) 623-627.
18. Quinlan, J.: C4. 5: Programs for machine learning. Morgan Kaufmann. (1993)
19. Press, W. H. , Teukolsky, S. A, et al.: Numerical recipes in C. Cambridge University Press. (1988)
20. Oyama, T. , Kitano, K. ,et al.: Extraction of knowledge on protein-protein interaction by association rule discovery. Bioinfonnatics 18 (2002) 705-14.