The MoBiosD-hub’s portfolio of molecular modeling applications is presented as a workflow involving ligand- and structure-based design strategies. The toolkits employed for these tasks are programming libraries used to create customized applications with object-oriented accessibility to a given set of capabilities. Tools on this website are and will remain free for all interested users. Our aim is to develop information technologies to analyze important bio-molecules in life science (e.g., genes, proteins, compounds, drugs) in order to understand their functions in the biological system. That is, we develop novel statistical/machine learning methods for the prediction of the pharmacokinetics (ADME), pharmacological, biochemical, PhysChem, medical and toxicity endpoints or/and to predict various molecular interaction networks (protein (or compound)-protein interactions, metabolic pathways, etc.) from omics data in genome, transcriptome, proteome, metabolome, and phenome (microarrays). A general trend through our research is to permit scientists to gain access to data, methods, and new technology in Chem-Bio-Med-Informatics and e-Science.
