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Igor Tsigelny, Ph.D.

Research Scientist
Computational Biology

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Igor Tsigelny
Igor T Bio


Igor F. Tsigelny is a Research Professor at the Department of Neurosciences and San Diego Supercomputer Center. He is a scientist at CureScience   . He is a world-known expert in structural biology, molecular modeling, bioinformatics, and structure-based drug design. He has a Ph. D. in Physics of Macromolecules from the Academy of Sciences of Ukraine. He has been a postdoctoral fellow in the University of California in the laboratory of Susan S. Taylor in 1992-1995. 

Dr. Tsigelny is the author of over 200 papers in scientific journals including the Nature and Science groups of journals, and Proceedings of National Academy of Sciences of the USA. He wrote and edited 5 scientific books. The book “Protein Structure Prediction: Bioinformatic Approach” that he edited, has been called “The Bible of all current prediction techniques” by BioPlanet Bioinformatics Forums. He is a member of editorial boards of over 10 scientific journals. 

Dr.Tsigelny has approximately 15 existing and pending patents. Two drug-candidates developed by Dr. Tsigelny for treatment of Parkinson’s disease and, brain cancer are licensed by UCSD to pharmaceutical companies and are in various stages of development His computational study of molecular mechanisms of Parkinson’s disease has been included in the US Department of Energy publication “Decade of Discovery” where the best computational studies of the first decade of XXI century were described. He is a cofounder of two companies: Neuropore and CureMatch. Currently he has 7900 citations in scientific publications.


Most Recent Publications

1. Gao, A. K., Chen, T. B., Kouznetsova, V. L., & Tsigelny, I. F. (2023, December 1). Machine-Learning-Based Virtual Screening and Ligand Docking Identify Potent HIV-1 Protease Inhibitors. Artificial Intelligence Chemistry.
2. Tsui, A., Kouznetsova, V. L., Kesari, S., Fiala, M., & Tsigelny, I. F. (2023, November 20). Role of Senataxin in Amyotrophic Lateral Sclerosis. Journal of Molecular Neuroscience.
3. Chen, T. B., Chen, R., You, A. S., Kouznetsova, V. L., & Tsigelny, I. F. (2023, November 1). Search of inhibitors of aldose reductase for treatment of diabetic cataracts using machine learning. Advances in Ophthalmology Practice and Research.
4. Tim, B., Kouznetsova, V. L., Kesari, S., & Tsigelny, I. F. (2023, November 1). Targeting of insulin receptor endocytosis as a treatment to insulin resistance. Journal of Diabetes and Its Complications.
5. Arora, A., Tsigelny, I. F., & Kouznetsova, V. L. (2023, October 31). Laryngeal Cancer Diagnosis via miRNA-based Decision Tree Model.
6. Jin, J., Kouznetsova, V. L., Kesari, S., & Tsigelny, I. F. (2023, November 1). Synergism in actions of HBV with aflatoxin in cancer development. Toxicology.
7. Choudhary, A., Yu, J., Kouznetsova, V. L., Kesari, S., & Tsigelny, I. F. (2023, October 7). Two-Stage Deep-Learning Classifier for Diagnostics of Lung Cancer Using Metabolites. Metabolites.
8. Kulkarni, V., Tsigelny, I. F., & Kouznetsova, V. L. (2023, September 14). Implementation of Machine Learning-Based System for Early Diagnosis of Feline Mammary Carcinomas through Blood Metabolite Profiling.
9. Szu, J. I., Tsigelny, I. F., Wojcinski, A., & Kesari, S. (2023, May 18). Biological functions of the Olig gene family in brain cancer and therapeutic targeting. Frontiers in Neuroscience.
10. Kurzrock, R. (2016, September 8). US20230073255A1 - Optimizing therapeutic options in personalized medicine          - Google Patents.
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