Learning kernel matrix from gene ontology and annotation data for protein function prediction

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

Volumn 5553 LNCS, Issue PART 3, 2009, Pages 694-703

  Chen, Yiming ^a   Li, Zhoujun ^b   Liu, Junwan ^a  

^a University of Defence and Technology   (China)

^b BEIHANG UNIVERSITY   (China)

Author keywords

Diffusion kernel; Gene ontology; Protein function prediction

Indexed keywords

BIOLOGICAL DATA; BIOLOGICAL PROCESS; DIFFUSION KERNEL; GENE ONTOLOGY; HAUSDORFF DISTANCE; KERNEL MATRICES; KERNEL METHODS; LEARNING KERNELS; MEASUREMENT METHODS; NOVEL METHODS; PROTEIN FUNCTION PREDICTION; PROTEIN FUNCTIONS; SEMANTIC SIMILARITY; SIMILARITY MATRIX; UNDIRECTED GRAPH;

DIFFUSION; NEURAL NETWORKS; ONTOLOGY; OPTIMIZATION;

MATRIX ALGEBRA;

EID: 69849083710     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-01513-7_76     Document Type: Conference Paper

References (12)

1. Tsuda, K., Noble, W.S.: Learning Kernels from Biological Networks by Maximizing Entropy. Bioinformatics 20, 326-333 (2004)
2. Lanckriet, G., Deng, M., Cristianini, M., Jordan, M., Noble, W.: Kernel-based Data Fusion and Its Application to Protein Function Prediction in Yeast. In: Pac. Symp. Biocomput., vol.9, pp. 300-311 (2004)
3. Cristianini, N., Shawe-Taylor, J.: Kernel Methods for Pattern Analysis. China Machine Press, Beijing (2005)
4. Ashburner, M., Ball, C., Blake, J., Botstein, D.: Gene Ontology: Tool for the Uni-fication of Biology. The Gene Ontology Consortium. Nat. Genet. 25, 25-29 (2000)
5. Resnik, P.: Semantic Similarity in A Taxonomy: An Information-based Measure and Its Application to Problems of Ambiguity in Natural Language. J. Artif. Intell. Res. 11, 95-130 (1999)
6. Lin, D.: An Information-theoretic Definition of Similarity. In: The 15th International Conference on Machine learning, pp. 296-304. Morgan Kaufmann Publishers, San Francisco (1998)
7. Kondor, R.I., Lafferty, J.: Diffusion Kernels on Graphs and other Discrete Input Spaces. In: Proc. Int. Conf. Machine Learning, pp. 315-322. Morgan Kaufmann Publishers, San Francisco (2002)
8. Nello, C., John, S., Elissee, J., Kandola, A.: On Kernel-target Alignment. In: Advances in Neural Information Processing Systems 14, pp. 367-373. MIT Press, Cambridge (2002)
9. Lanckriet, G.R., Cristianini, N., Bartlett, P., Laurent, E., Michael, I.G., Jordan, M.I.: Learning the Kernel Matrix with Semide Nite Programming. Journal of Machine Learning Research 5, 27-72 (2004)
10. Boyd, S., Vandenberghe, L.: Convex Optimization. Cambridge University Press, London (2004)
11. The Mathworks Incorporation: Matlab help, http://www.mathworks.cn/
12. Sonnenburg, S., Raetsch, G., Schaefer, C., Scholkopf, B.: Large scale multiple kernel learning. Journal of Machine Learning Research 7, 1531-1565 (2006)