Knowledge Discovery in Bioinformatics Special session in BGRS 2008

Objectives: Bioinformatics is the study of how data, information and knowledge about biological systems are collected, analyzed, interpreted and presented in the data rich environment of life sciences. Knowledge Discovery, the key contributor to the success of bioinformatics research, involves a close collaboration between researchers from a number of diverse areas, such as biology, medicine, genomics and proteomics to computer science, mathematics and statistics. It encompasses networking, databases, visualization techniques, search engine design, statistical techniques, modeling and simulation, AI and related pattern recognition methods. This collaboration of disciplines has evolved because of the: (i) advances that have occurred in data production and acquisition facilities, such as the introduction of high-throughput genomics and proteomics microarrays, (ii) enormous amounts of data that is generated every day that cannot be analyzed using ordinary data mining tools and techniques, (iii) the data extracted from more sophisticated simulations of biological processes in genomics and proteomics, and (iv) strong interest from many groups (research institutes, hospitals, academia, life sciences, pharmaceuticals, etc.) who want to benefit from this wealth of data. Many efforts to deal with these issues are being undertaken by researchers working in this field.

The aim of this session that is part of BGRS-2008 is to bring together researchers working on different topics related to knowledge discovery in bioinformatics. In particular we are interested to present and discuss challenges and issues related to the analysis, validation and understanding of various forms of genomics data. The main topics to be addressed during this session are integration of various methodologies for analysis and interpretation of functional genomics data.

The intended audience for this session are reseachers and practitioners who are working in the above fields and in one or more of the following.

Topics:

  • Data pre-processing, data understanding
  • Data management methods
  • Data mining architectures, data bases
  • Machine learning, NN, GA, SVM
  • Statistics
  • Soft computing techniques
  • Gene expression analysis
  • Gene networks and pathways
  • Comparative genomics
  • Post-processing, knowledge/model integration
  • Integration of various forms of genomics and proteomics data
  • Genomics knowledge structure and dissemination
  • Association rules, and knowledge discovery from time series data
  • Data Visualization, Association Graphs
  • Biological Modeling and Artificial Life

Organizing committee:

Important Dates (pending acceptance of this workshop proposal):

  • May 1st 2008 Conference Registration
  • Session is held on June 23rd 2007 (tentative)

Attending the session

This session will consist of one invited talk and four presentations of 30 minutes each,
Time: to be decided later