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Center for Computational Intelligence, Learning, and Discovery
Location :Iowa State University, Ames, Iowa, USA.
The Center for Computational Intelligence, Learning, and Discovery at Iowa State University focuses on a broad range of problems in Data-driven discovery of macromolecular sequence-structure-function-interaction-expression relationships, identification of sequence and structural correlates of protein-protein , protein-RNA, and protein-DNA interactions, protein sub-cellular localization, automated protein structure and function annotation, modeling and inference of protein and gene networks from gene expression (micro-array, proteomics) data, modeling, simulation, analysis, and inference of signal transduction and metabolic pathways.
The center's research in Bioinformatics and Computational Systems Biology is supported by significant breadth and depth of research in Data Mining including analysis, implementation, and evaluation of algorithms and software for data-driven knowledge acquisition, data and knowledge visualization, and collaborative scientific discovery from semantically heterogeneous, distributed data and knowledge sources; Machine Learning including statistical, information theoretic, linguistic and structural approaches to machine learning, Learning and refinement of bayesian networks, causal networks, decision networks, neural networks, support vector machines, kernel classifiers,, multi-relational models, language models (n-grams, grammars, automata), Learning classifiers from attribute value taxonomies and partially specified data; Learning attribute value taxonomies from data; Learning classifiers from sequential and spatial data; Learning relationships from multi-modal data (e.g., text, images); Semantic Web: Ontology-based user and query-centric approaches to information integration and acquisition of sufficient statistics for learning from data under different access and resource constraints from heterogeneous, distributed, autonomous, ubiquitous information sources, sensor networks, peer-to peer networks; description logics, ontology design, ontology tools, ontology-extended information sources, ontology-extended workflow components, ontology-extended agents and services, web service composition.
Additional information about ongoing projects and publications can be found on the Center's web site.
Keywords:Bioinformatics, Information Integration, Ontologies, Systems Biology, Data Mining, Computational Structural Genomics, Genomics, Computational Functional Genomics, Macromolecular Structure-Function, Protein-DNA interactions, Protein-protein interactions, protein-RNA interactions, Protein Function Prediction, Phosphorylation, Glycosylation, MHC-Binding Peptide, Machine Learning, Semantic Web, e-science