Dr. MICHAEL GRIBSKOVProfessor
PROFESSIONAL FACULTY RESEARCH
(Computational Genomics & Systems Biology; Bioinformatics) Computational analysis of biological systems and the macromolecular components that they comprise. My interests range from the evolution, structure and function of macromolecules, to the biological networks that control and integrate the development and function of cells. Active research projects as of 2021 include structure and function of long non-coding RNA, application of machine learning approaches to understanding non-coding RNA structure and function, and genomic/transcriptomic/metagenomics study of diverse systems. Some specific recent projects include g include investigation of Cd resistance in soil fungi and Cacao, gene expression during fruit maturation in Avocado, differential expression of genes and microRNAs in several tumor types, and development of new methods for predicting micropeptide coding frames and internal ribosome entry sites.
Biological systems are controlled by extremely complex networks of interactions between genes, RNAs, proteins, and small molecules. The Computational Genomics & Systems Biology group investigates these complex interactions using computational analysis of genomics and systems biology data.
More broadly, we develop computational methods for finding patterns in sequences and structures that allow us to make inferences about the relationships between sequence, structure, function, and evolution. These methods include elements of datamining, machine learning, modeling, and simulation in the context of biological data. One of our central emphases is using information from homologous molecules in different species to find the conserved structural elements that are associated with biological function. More recently we have extended these approaches to the analysis of biological networks using genome wide expression, protein interaction, genetic interaction and metabolite data.
B.S. Biochemistry & Biophysics (with Honors), Oregon State University, 1979
Ph.D. Molecular Biology, University of Wisconsin-Madison, 1985
Post-doctoral University of California, Los Angeles
- Journal of Computational Biology and Chemistry
- Microbial Physiology
Societies and Advisory Boards
• 2020 Fulbright Scholar
• Past president, International Society for Computational Biology
• 2012 – 2017, NIH/NIAID National Systems Biology Steering Committee
2019 NIH/NIAID special emphasis review panel ZA11-EC-M-J1 Emerging Infectious disease research centers.
2019 NIH/NIAID special emphasis review panel ZA11-EC-M-J21, Emerging Infectious disease coordinating center.
2018 NIH/NIAID special emphasis review panel ZA11-EC-M-J1, Genomics Centers for infectious disease (U19)
2017 Department of Energy, Joint Genome Institute, Triennial review panel
2017 NIH/NIAID special emphasis review panel ZA11-EC-M-S2, Systems biology: the next generation (U19 centers)
2017 NIH/NIAID, Systems biology for Infectious diseases review panel
2021 34 Congreso Latinoamericano de Qúimica /IV Congreso Colombiano de Bioquímica y Biología Molecular, Catagena de las Indias, Colombia . Machine Learning, Artificial Intelligence and RNA
2020 National University of Colombia. Computational Genomics (15 week course)
2017 Colombian Congress on Computational Biology/Iberoamerican Conference on Bioinformatics IV Congreso Colombiano de Bioinformática y Biología Computacional (IVCCBOL) and VIII Conferencia Iberoamericana de Bioinformática, Cali, Colombia. Identifying Functionally Important RNA Structures Using Graph Theoretic Approaches
2017 From Computational Biophysics to Systems Biology. Cincinnati OH Graph Theoretic Approaches to RNA Topology Comparison
2016 National University of Colombia. Principles of Genomic and Metagenomic Data Analysis (Three week international course).
2015 National University of Colombia. Differential gene expression analysis using RNA-Seq (One week workshop).
2014 University of Dundee Bioinformatics Mini-symposium, Finding conserved RNA Motifs, Dundee Scotland.