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MICHAEL GRIBSKOV
| Professor LILY G-233 494-6933 CV: Link |
The sequence, structure and evolution of proteins are intimately intertwined. This is especially apparent for large protein families such as the protein kinases. Genomics and other high-throughput techniques have made a wealth of information describing proteins, their expression and their interactions available. We try to use this information to understand the function, regulation, and origin of protein families suchs as protein kinases, protein phosphatases, membrane transporters, and participants in the ubiquitin-mediated protein degradation cascade.
More broadly, we develop computational methods for finding patterns in sequences an structures that allow us to make inferences, of the kinds discussed above, about the relationships between sequence, structure and function. These methods include elements datamining, machine learning, modeling, and simulation in the context of biological data. My group is interested in applications to protein motifs, DNA signals (transcription factor binding sites) and modules, and RNA structures.
These studies drive our development of computational tools to find and define protein and nucleic acid sequence and structural patterns, the development of electronic data laboratories, and the development of approaches to interoperation of electronic tools and resources.
Education
B.S. Oregon State University, 1979
Ph.D. University of Wisconsin-Madison, 1985
Professional Faculty Research
(Computational biology; bioinformatics) Relationship between patterns in macromolecular sequences and the evolution, structure and function of corresponding molecules; development of databases and computational tools for functional genomics; development of systems that federate knowledge across multiple electronic resources.
Other Activities
Editorial Boards
- Bioinformatics
- Journal of Computational Biology and Chemistry
- Journal of Molecular Microbiology & Biotechnology
Societies and Advisory Boards
- President, International Society for Computational Biology
- Chair, Protein Information Resource Scientific Oversight and Advisory Board
- Member, Allele Frequency Database (ALFRED) Advisory Board
- Member, Idaho INBRE External Advisoty Committee
Study Section
- 2005 - Biodata Management and Analysis
- 2005 - National Centers for Biomedical Computing
- 2004 - National Centers for Biomedical Computing
- 2002 - NIH Genome Study Section
- 2002 - NCI Basic and Preclinical
Seminars
- 2005 - Purdue University Computational genomics of plant protein families.
- 2005 - Biometrics ENAR Conference Investigation of plant phosphorylation using intergenomic comparison.
- 2005 - DOE, Populus Annotation meeting Global annotation of the plant protein kinase family.
- 2004 - Mid-Central bioinformatics Society The future of Biopinformatics.
- 2004 - Purdue University Computational exploration of the kinome.
- 2004-University of Idaho Finding functionally important sequences using expectation-maximization.
- 2004 - University of Indiana-Bloomington Computational exploration of the kinome.
- 2003 - University of Maryland Exploring the plant kinome.
- 2003 - University of California, Riverside Genomic analysis of plant protein kinases.