BIOKDD 2001: San Francisco, CA, USA

@proceedings{DBLP:conf/kdd/2001bio,
  editor    = {Mohammed Javeed Zaki and
               Hannu Toivonen and
               Jason Tsong-Li Wang},
  title     = {Proceedings of the ACM SIGKDD Workshop on Data Mining in Bioinformatics
               (BIOKDD 2001)},
  booktitle = {BIOKDD},
  year      = {2001},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

Invited Paper & Gene Expression

• Bruce A. Shapiro, David Bengali, Wojciech Kasprzak:
  Determination of RNA folding pathway functional intermediates using a massively parallel genetic algorithm (abstract of invited talk). 1
  
• Simon M. Lin, Sumeer Dhar, Rose-Mary N. Boustany:
  Extracting knowledge from gene expression data: A case study of Batten Disease. 2-7
  

Microarrays

• Goutham Kurra, Wen Niu, Raj Bhatnagar:
  Mining microarray expression data for classifier gene-cores. 8-14
  
• Paul Pavlidis, Christopher Tang, William Stafford Noble:
  Classification of genes using probabilistic models of microarray expression profiles. 15-21
  
• Silvio Bicciato, Mario Pandin, Giuseppe Didone, Carlo Di Bello:
  Analysis of an associative memory neural network for pattern identification in gene expression data. 22-30
  

Sequence Assembly

• Mark K. Goldberg, Darren T. Lim, Malik Magdon-Ismail:
  A learning algorithm for string assembly. 31-37
  
• Sun Kim, Li Liao, Jean-Francois Tomb:
  A probabilistic approach to sequence assembly validation. 38-43
  

Invited Paper & Proteins

• Charles Elkan:
  Shared challenges in data mining and computational biology (abstract of invited talk). 44
  
• Mikael Huss, Henrik Boström, Lars Asker, Joakim Cöster:
  Learning to recognize brain specific proteins based on low-level features from on-line prediction servers. 45-49
  
• Nitesh V. Chawla, Thomas E. Moore, Kevin W. Bowyer, Lawrence O. Hall, Clayton Springer, W. Philip Kegelmeyer:
  Investigation of bagging-like effects and decision trees versus neural nets in protein secondary structure prediction. 50-59
  

Sequence Modeling & Clustering

• Eugen C. Buehler, Lyle H. Ungar:
  Maximum entropy methods for biological sequence modeling. 60-64
  
• Raymond T. Ng, Jörg Sander, Monica C. Sleumer:
  Hierarchical cluster analysis of SAGE data for cancer profiling. 65-72
  
• Valerie Guralnik, George Karypis:
  A scalable algorithm for clustering protein sequences. 73-80