IDEAL

Chase Krumpelman

Graduate Student

• Applications of data mining to biological data
• Overlapping/multimembership clustering and generative additive models
• Methods of teaching and communicating data mining and machine learning concepts
• Visualization and effective presentation of data analysis results

• A. Banerjee, C. Krumpelman, S. Basu, R. Mooney, and J. Ghosh, "Model-based Overlapping Clustering", KDD '05. pp. 532-537
• Chase Krumpelman and Joydeep Ghosh, "Matching and Visualization of Multiple Overlapping Clustering of Microarray Data" CIBCB '07
• L Pena-Castillo, M Tasan, CL Myers, H Lee, T Joshi, C Zhang, Y Guan, M Leone, A Pagnani, WK Kim, C Krumpelman, W Tian, G Obozinski, Y Qi, S Mostafavi, GN Lin, G Berriz, F Gibbons, G Lanckriet, J Qiu, C Grant, Z Barutcuoglu, DP Hill, D Warde-Farely, C Grouios, D Ray, JA Blake, M Deng, M Jordan, WS Noble, Q Morris, J Klein-Seetharaman, Z Bar-Joseph, T Chen, F Sun, OG Troyanskaya, EM Marcotte, D Xu, TR Hughes and FP Roth. "A critical assessment of M. musculus gene function prediction using integrated genomic evidence." Genome Biology. In Press
• Wan Kyu Kim, Chase Krumpelman, Edward M. Marcotte, "Inferring mouse gene functions from genomic-scale data using a combined functional network/classification strategy." Genome Biology. In Press
• Chase Krumpelman, Deepu Sudhakar, and Orly Alter, "Interactive Software Environment for DNA Microarray Analysis and Visualization", poster presented at UT SXSVD February 2008.

• krump AT ideal.ece.utexas.edu