Topics

The topics of interest include, but are not limited to:

  • Computational proteomics:
    • Analysis of protein-protein interactions.
    • Protein structure modelling.
    • Analysis of protein functionality.
    • Quantitative proteomics and PTMs.
    • Clinical proteomics.
    • Protein annotation.
    • Data mining in proteomics.
  • Next generation sequencing and sequence analysis:
    • De novo sequencing, re-sequencing and assembly.
    • Expression estimation.
    • Alternative splicing discovery.
    • Pathway Analysis.
    • Chip-seq and RNA-Seq analysis.
    • Metagenomics.
    • SNPs prediction.
  • High performance in Bioinformatics:
    • Parallelization for biomedical analysis.
    • Biomedical and biological databases.
    • Data mining and biological text processing.
    • Large scale biomedical data integration.
    • Biological and medical ontologies.
    • Novel architecture and technologies (GPU, P2P, Grid,...) for Bioinformatics.
  • Biomedicine:
    • Biomedical Computing.
    • Personalized medicine.
    • Nanomedicine.
    • Medical education.
    • Collaborative medicine.
    • Biomedical signal analysis.
    • Biomedicine in industry and society.
    • Electrotherapy and radiotherapy.
  • Biomedical Engineering:
    • Computer-assisted surgery.
    • Therapeutic engineering.
    • Interactive 3D modelling.
    • Clinical engineering.
    • Telemedicine.
    • Biosensors and data acquisition.
    • Intelligent instrumentation.
    • Patient Monitoring.
    • Biomedical robotics.
    • Bio-nanotechnology.
    • Genetic engineering.
  • Computational systems for modelling biological processes:
    • Inference of biological networks.
    • Machine learning in Bioinformatics.
    • Classification for biomedical data.
    • Microarray Data Analysis.
    • Simulation and visualization of biological systems.
    • Molecular evolution and phylogenetic modelling.
  • Healthcare and diseases:
    • Computational support for clinical decisions.
    • Image visualization and signal analysis.
    • Disease control and diagnosis.
    • Genome-phenome analysis.
    • Biomarker identification.
    • Drug design.
    • Computational immunology.
  • E-Health:
    • E-Health technology and devices.
    • E-Health information processing.
    • Telemedicine/E-Health application and services.
    • Medical Image Processing.
    • Video techniques for medical images.
    • Integration of classical medicine and E-Health.