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Cited In
Searls DB
¡°Data integration: Challenges for drug discovery¡±
NATURE REVIEWS DRUG DISCOVERY 4 (1): 45-58, JAN 2005
Young JA, Winzeler EA
¡°Using expression information to discover new drug and vaccine targets in the malaria parasite Plasmodium falciparum¡±
PHARMACOGENOMICS 6 (1): 17-26, JAN 2005
John Wiley & Sons, Ltd (Current Awareness section)
¡°Current awareness on comparative and functional genomics¡±
Comparative and Functional Genomics 5 (6-7): 555-562, JAN 2005
P.V. Gopalacharyulu, E. Lindfors, C. Bounsaythip et al.
¡°Data integration and visualization system for enabling conceptual biology¡±
Bioinformatics, 21: i177-i185, JUN 2005
H. Yu, L. Gao, K. Tu, Z. Guo
¡°Broadly predicting specific gene functions with expression similarity and taxonomy similarity¡±
Gene, 352: 75-81, JUN 2005
X.Z. Mao, T. Cai et al.
¡°Automated genome annotation and pathway identification using the KEGG Orthology (KO) as a controlled vocabulary¡±
Bioinformatics, 21(19): 3787-3793. OCT 2005
In-Yee Lee, Jan-Ming Ho, Ming-Syan Chen
¡°CLUGO: A clustering algorithm for automated functional annotations based on Gene Ontology¡±
The 5th IEEE International Conference on Data Mining (ICDM ¡¯05) pp.705-708
Nora Speer, Christian Spieth, and Andreas Zell
¡°Spectral clustering gene ontology terms to group genes by function¡±
Lecture notes in Computer Science, 3692:1-12, 2005
In-Yee Lee, Jan-Ming Ho, Ming-Syan Chen
¡°GOMIT: A generic and adaptive annotation algorithm based on Gene Ontology term distributions¡±
The 5th Symposium on Bioinformatics and Bioengineering (BIBE ¡¯05) pp.40-48.
Cliff A. Joslyn, Susan M. Mniszewski, Andy Fulmer, and Gary Heaton
¡°The Gene Ontology Categorizer¡±
Bioinformatics, 20: i169-i177, AUG 2004
Kennedy PJ, Simoff SJ, Skillicorn D, et al.
¡°Extracting and explaining biological knowledge in microarray data¡±
LECTURE NOTES IN ARTIFICIAL INTELLIGENCE 3056: 699-703, 2004
Jinze Liu, Jiong Yang, and Wei Wang
¡°Gene ontology friendly biclustering of expression profiles¡±
Proceedings of the IEEE Computational Systems Bioinformatics Conference (CSB), pp. 436-447, 2004
Nora Speer, Christian Spieth, and Andreas Zell
¡°A Memetic Clustering Algorithm for the Functional Partition of Genes Based on the Gene Ontology¡±
Proceedings of the 2004 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB 2004), San Diego, USA, pp. 252-259, IEEE Press, 2004 4
 
Publication & Presentation
Sung Geun Lee, Jung Uk Hur, and Yang Seok Kim (2004). A Graph-theoretic Modeling on GO Space for Biological Interpretation of Gene Clusters. Bioinformatics, 20(3):381-388.
Sung Geun Lee, Wan Seon Lee, and Yang Seok Kim (2003). GOODIES: GO based Data Mining Tool for Characteristic Attribute Interpretation on a Group of Biological Entities. Genome Informatics, 14:675-676.
Sung Geun Lee & Wan Seon Lee. GOODIES: Gene Ontology-based data-mining tool for biological interpretation and functional classification on a group of biological entities. Participation in the 11th International Conference on Intelligent Systems for Molecular Biology (ISMB 2003).
Jung Hur, Sung Lee, Ji Oh, Tae Chung, Yang Kim. A Mathematical Modeling of GO Hierarchy for Gene Expression Profiling Analysis. Currents in Computational Molecular Biology 2002. pp87-88.
Sung Geun Lee, Jung Uk Hur and Yang Suk Kim. GOODIES: A Mathematical Modeling of GO Hierarchy for Automated Biological Validation and Putative Functional Categorization of Genes. Proceedings of the Annual Meeting of Korean Society for Bioinformatics 2002. pp268.

The Most Excellent Poster Awarded.