Cross Disciplinary Special Session CDCI-17: Computational Intelligence Methods Accelerated on Parallel and Distributed Architectures for Applications in Bioinformatics, Computational Biology and Systems Biology

Aims

Research problems in Bioinformatics, Computational Biology and Systems Biology deal with systems at different scales of complexity and granularity (from the inference of single molecular structure to the emergent behavior of genome-wide networks), each one requiring completely different computational methods. Computational intelligence is frequently exploited to devise efficient heuristics solving problems in these disciplines; however, these approaches can be computationally challenging, limiting their applicability to real-world problems. The scope of this special session is to bring together researchers involved in the development of computational intelligence methods applied to Bioinformatics, Computational Biology and Systems Biology, specifically accelerated either by means of conventional architectures (e.g., computer clusters, GRID computing) or by unconventional technologies (e.g., Graphics Processing Units, Many Integrated Core coprocessors, biomimetic devices).

Scope and Topics

The scope of this session includes accelerated Computational Intelligence methods applied to the fields of Bioinformatics, Computational Biology and Systems Biology. Topics of interest include, but are not limited to:

  • analysis and visualization of large datasets
  • analysis and visualization of genome-wide models
  • biomedical model parameterization
  • development of synthetic biological devices
  • drug design
  • emergent properties in complex biological systems
  • flux balance analysis
  • gene expression array analysis
  • high-throughput data analysis
  • medical image analysis
  • medical imaging and pattern recognition
  • metabolic pathway analysis
  • mining of biomedical data
  • modelling, simulation and optimization of biological systems
  • molecular dynamics and molecular docking
  • molecular evolution and phylogenetics
  • molecular sequence alignment and analysis
  • optimization of biological systems
  • prediction and searching of molecular structure and folding
  • spectral analysis