Workshop Scope and Objective

Images courtesy of Andrews-Dalkilic Group

Mining biological data is an emerging area of intersection between bioinformatics and data mining. Bioinformaticians have taken a computational approach to understanding biological phenomena.


Because these phenomena are typically characterized by large and increasing amounts of data, divers and unusual data types, and complex relationships, interpreting biological data requires novel approaches that include multiple tools, new algorithms, resources, etc. in an integrated fashion. Data mining has focused on extracting useful information from large database, focusing on scalable, robust algorithms and their implementations. The proposed workshop will respond to both these areas of research by encouraging researchers in the data mining community to bring to bear novel techniques, combinations of tools, and so forth to mine biological data.


The objective of the workshop is to facilitate collaboration between data mining researchers and bioinformaticians by presenting cutting edge research topics and methodologies in the area of data mining for bioinformatics. While such research has an interdisciplinary character, this workshop emphasizes on the area of data mining with particular application to bioinformatics.



Workshop papers will be published in VLDB proceedings (CD version) and selected papers will be published in the Journal of Bioinformatics and Computational Biology.

The workshop will feature invited talks from noted experts in the field and the latest data mining research in bioinformatics. We encourage papers that propose novel data mining techniques for tasks such as:


  • Sequence clustering/classification
  • Protein interaction networks
  • Comparative genomics
  • Microarray analysis
  • RNAi and microRNA analysis
  • Whole, multiple genome comparison
  • Visualization
  • Phylogenetics
  • Text mining and ontologies
  • System biology and pathways

Our workshop, now in its second term, is responding to this need, encouraging researchers in the data mining community to answer this call. Our inaugural VLDB 2006 Data Mining in Bioinformaticswas a success with an excellent diverse programming committee committed to this cause. As more biological data of diverse types become available, research in bioinformatics moves toward systems biology by utilizing multiple tools and data in an integrated fashion.

A related an exciting workshop participants should consider is Probabilistic Methods for Active Learning and Data Integration in Computational Biology that is affiliated with ISMB/ECCB 2007.