Isof-Vaisman
Director, School of Systems Biology
Affiliations
- Departments
- Dean’s Administration (Staff)
- School of Systems Biology
Education
- PhD, Russian Academy of Sciences
About
Dr. Vaisman is a Professor of Bioinformatics and Computational Biology and Director of the School of Systems Biology. Current research projects involve different areas of computational biology and bioinformatics, with a specific focus on understanding correlations between protein sequence, structure, and function using machine learning models.
Current Research
Current research projects involve different areas of computational biology and bioinformatics, with a specific focus on understanding correlations between protein sequence, structure, and function using machine learning models.
Teaching Focus
BINF 630, Bioinformatics Methods
BINF 731, Computational Protein Structure Analysis
Selected Publications
D.L. Bostick, M. Shen, I.I. Vaisman, A simple topological representation of protein structure: implications for new, fast, and robust structural classification, Proteins: Structure, Function, and Bioinformatics, 2004, 56 (3), 487-501 (https://onlinelibrary.wiley.com/doi/full/10.1002/prot.20146)
M. Masso, I.I. Vaisman, Accurate prediction of stability changes in protein mutants by combining machine learning with structure based computational mutagenesis, Bioinformatics, 2008, 24 (18), 2002-2009 (https://academic.oup.com/bioinformatics/article/24/18/2002/190733)
T.J. Taylor, I.I. Vaisman, Discrimination of thermophilic and mesophilic proteins, BMC Structural Biology, 2010, 10 (1), S5 (https://bmcstructbiol.biomedcentral.com/articles/10.1186/1472-6807-10-S1-S5)
M. Masso, I.I. Vaisman, Structure-based machine learning models for computational mutagenesis, Introduction to Protein Structure Prediction: Methods and Algorithms, 2010 (https://onlinelibrary.wiley.com/doi/abs/10.1002/9780470882207.ch18)
I.I. Vaisman, Statistical and computational geometry of biomolecular structure, Handbook of Computational Statistics, 2012 (https://link.springer.com/chapter/10.1007/978-3-642-21551-3_36), 2013
