BIOKDD, 2001

1st Workshop on Data Mining in Bioinformatics

August 26, 2001
San Francisco, CA, USA

in conjunction with

7th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
(KDD'2001)

Proceedings of the ACM SIGKDD Workshop on Data Mining in Bioinformatics edited by Mohammed J. Zaki, Hannu T.T. Toivonen, and Jason T. L. Wang :

Foreword , Mohammed J. Zaki, Hannu T.T. Toivonen, and Jason T. L. Wang,  pp. i - ii.

Part I (Invited Paper & Gene Expression)

  • Invited Paper: Determination of RNA folding pathway functional intermediates using a massively parallel genetic algorithm , Bruce A. Shapiro, David Bengali, and Wojciech Kasprzak,  National Cancer Institute, USA, pp. 1.

  • Extracting knowledge from gene expression data: A case study of Batten Disease, Simon M. Lin, Sumeer Dhar, and Rose-Mary N. Boustany,  Duke University Medical Center, USA, pp. 2 - 7.

    • Part II (Microarrays)

  • Mining microarray expression data for classifier gene-cores, Goutham Kurra, Wen Niu, and Raj Bhatnagar, University of Cincinnati, USA, pp. 8 - 14.

  • Classification of genes using probabilistic models of microarray expression profiles, Paul Pavlidis, Christopher Tang, and William S. Noble, Columbia University, USA, pp. 15 - 21.

  • Analysis of an associative memory neural network for pattern identification in gene expression data, Silvio Bicciato, Mario Pandin, Giuseppe Didone', and Carlo Di Bello, University of Padova and Cittadella Hospital, Italy, pp. 22 - 30.

    • Part III (Sequence Assembly)

  • A learning algorithm for string assembly, Mark K. Goldberg, Darren T. Lim, and Malik Magdon-Ismail, RPI, USA, pp. 31 - 37.

  • A probabilistic approach to sequence assembly validation, Sun Kim, Li Liao, and Jean-Francois Tomb, Indiana University and DuPont, USA, pp. 38 - 43.

    • Part IV: (Invited Paper & Proteins)

  • Invited Paper: Shared challenges in data mining and computational biology, Charles Elkan, University of California, San Diego, USA, pp. 44.

  • Learning to recognize brain specific proteins based on low-level features from on-line prediction servers, Mikael Huss, Henrik Bostrom, Lars Asker, and Joakim Coster, Vitrual Genetics Laboratory, Sweden, pp. 45 - 49.

  • Investigation of bagging-like effects and decision trees versus neural nets in protein secondary structure prediction, Nitesh Chawla, Thomas E. Moore, Kevin Bowyer, Lawrence O. Hall, Clayton Springer, and Philip Kegelmeyer, University of South Florida and Sandia National Labs., USA, pp. 50 - 59.

    • Part V (Sequence Modeling & Clustering)

  • Maximum entropy methods for biological sequence modeling, Eugen C. Buehler and Lyle H. Ungar, University of Pennsylvania, USA, pp. 60 - 64.

  • Hierarchical cluster analysis of SAGE data for cancer profiling, Raymond T. Ng, Jorg Sander, and Monica C. Sleumer, University of British Columbia, Canada, pp. 65 - 72.

  • A scalable algorithm for clustering protein sequences, Valerie Guralnik and George Karypis, University of Minnesota, USA, pp. 73 - 80.
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    WORKSHOP CO-CHAIRS:
     

  • Mohammed J. Zaki, Rensselaer Polytechnic Institute (zaki@cs.rpi.edu )
  • Hannu T.T. Toivonen, University of Helsinki and Nokia Research Center (Hannu.TT.Toivonen@nokia.com) 
  • Jason T. L. Wang, New Jersey Institute of Technology (jason@cis.njit.edu) 


    • PROGRAM COMMITTEE:

  • Chuck Baldwin, Lawrence Livermore National Laboratory 
  • Chris Bystroff, Rensselaer Polytechnic Institute 
  • Shi-Kuo Chang, University of Pittsburgh 
  • Wesley W. Chu, University of California, Los Angeles 
  • Diane J. Cook, University of Texas at Arlington 
  • Charles Elkan, University of California, San Diego 
  • Janice Glasgow, Queen's University, Canada 
  • Richard Hughey, University of California, Santa Cruz 
  • Hasan Jamil, Mississippi State University 
  • Minoru Kanehisa, Kyoto University 
  • Simon M. Lin, Duke University Medical Center 
  • Jacob V. Maizel, Jr., National Institutes of Health 
  • Sharad Mehrotra, University of California at Irvine 
  • Shinichi Morishita, University of Tokyo 
  • Jane Richardson, Duke University 
  • Isidore Rigoutsos, IBM Thomas J. Watson Research Center 
  • Bruce Shapiro, National Institutes of Health 
  • Vassilis J. Tsotras, University of California, Riverside 
  • Alex Tuzhilin, New York University/Stern School of Business 
  • Jeff Vitter, Duke University 
  • Cathy H. Wu, Georgetown University Medical Center 
  • Michael Zucker, Rensselaer Polytechnic Institute 
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