With the advent of technologies like DNA sequencing and DNA microarray, an enormous amount of information has been generated that can only be efficiently analyzed with computers. As the information becomes ever larger and more complex, more computational tools are needed to sort through the data. These include:
Development of computational methodologies to perform systematic studies of complex interactions in biological systems to enable discovery of new emergent properties that may arise from the integrated systemic view.
Development of new algorithms and statistics to assess biological information, such as relationships among members of very large data sets.
Development and implementation of tools that enable efficient access and management of different types of information, such as various databases, integrated mapping information.
Visualization of various types of biological data to aid in analysis and interpretation of nucleotide and amino acid sequences, protein domains, and protein structures.
Topics of interest include, but are not limited to:
Modeling and simulation of biological processes, pathways, networks, and so on
Mathematical and quantitative models of cellular and multicellular systems
Synthetic biological systems
Molecular evolution and phylogeny
Metabolomics and other omics
DNA, RNA and protein sequence analysis
Gene expression analysis
Parallel and Grid computing
Image and signal analysis
Qualitative biological model
Biological network reconstruction and analysis
Medical and biomedical informatics
Drug discovery and validation
Discrete/stochastic modeling and language frameworks