Machine learning and intelligent optimization
in bioinformatics

Special session at CIBB2008
Computational intelligence methods for bioinformatics and biostatistics

4 October 2008

home call for abstracts CIBB2008

The increasing availability of biological data from sources as diverse as gene expression analysis, mass spectrometry, DNA sequencing and protein structure determination provides an unprecedented opportunity for machine learning approaches to computational molecular biology. Efficient algorithms are demanded in order to deal with such data, as well as techniques capable of learning from heterogeneous information, and jointly addressing related tasks. Transparency is a major concern to be traded-off and explanatory solutions are especially appealing for the domain experts. Intelligent optimization schemes like reactive search can be applied to deal with some of the most challenging problems, like ab initio protein structure prediction. This special session aims at bringing together researches from different fields of machine learning and intelligent optimization working on computational molecular biology, in order to discuss novel approaches to challenging bioinformatics problems and interesting formalizations of new tasks.

To ensure extensive interaction among participants as well as scientific quality and novelty of results, contributions to the special session will be by invitation only, and no formal proceedings will be published in order to allow for the most recent and interesting results to be presented and discussed. Contributions will be limited to a title and abstract, concerning either novel unpublished work, interesting results recently published elsewhere, or work in progress.

Session Chairs:

  • Andrea Passerini, Università degli Studi di Firenze, Italy
  • Roberto Battiti, Università degli Studi di Trento, Italy
  • Mauro Brunato, Università degli Studi di Trento, Italy