top of page
.jpg)
Biography
Valentina Kouznetsova is a Research Professor at UCSD (San Diego Supercomputer Center). She studies molecular mechanisms of various diseases including cancer, diabetes, and neurological disorders. Her work includes development of metabolic, genetic, and combined biomarkers for early diagnostics and distinction of different types and stages of a disease; development of inhibitors of signaling and metabolic pathways involved in a disease; protein modeling; and molecular simulations.
Dr.Kouznetsova is an expert in computational drug design. She developed drugs for treatment of Parkinson’s disease and glioblastoma that were licensed from UCSD and are in development in industry. She is an author of more than 100 scientific papers including publications in Nature and Science series of journals, edited and wrote 4 books, 8 book chapters, and 13 patents. Her article Locating Blood Vessels in Retinal Images by Piecewise Threshold Probing of a Matched Filter Response exceeded 1000 citations. She is a mentor of UCSD and CureScience programs for high-school students, who participate in scientific conferences and are co-authors of several research papers.
Dr. Kouznetsova obtained her M.S. degree in EE from Lviv Polytechnic National University in Ukraine and the Ph.D. degree in Technical Cybernetics and Information Theory from the Academy of Sciences of Ukraine. Her book “Self-Organization in Technical Systems” published in late twentieth century century was one of the first books devoted to the deep learning concepts.
TM
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. https://doi.org/10.1016/j.aichem.2023.100014
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. https://doi.org/10.1007/s12031-023-02169-0
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. https://doi.org/10.1016/j.aopr.2023.09.002
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. https://doi.org/10.1016/j.jdiacomp.2023.108615
5. Arora, A., Tsigelny, I. F., & Kouznetsova, V. L. (2023, October 31). Laryngeal Cancer Diagnosis via miRNA-based Decision Tree Model. https://doi.org/10.26434/chemrxiv-2023-r6vz1
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. https://doi.org/10.1016/j.tox.2023.153652
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. https://doi.org/10.3390/metabo13101055
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. https://doi.org/10.26434/chemrxiv-2023-g2vbk
9. Gantla, M. R., Tsigelny, I. F., & Kouznetsova, V. L. (2023, February 1). Repurposing of drugs for combined treatment of COVID-19 cytokine storm using machine learning. Medicine in Drug Discovery. https://doi.org/10.1016/j.medidd.2022.100148
10. Kang, W., Kouznetsova, V. L., & Tsigelny, I. F. (2022, February 18). miRNA in Machine-learning-based Diagnostics of Cancers. Cancer Screening and Prevention. https://doi.org/10.14218/csp.2021.00001
bottom of page