headshot photo of Dr. Gennady Verkhivker

Dr. Gennady Verkhivker

School of Pharmacy
Schmid College of Science and Technology; Physics, Computational Science and Engineering
Office Location: Hashinger Science Center 118
Phone: (714) 516-4586
Scholarly Works:
Digital Commons
Lomonosov Moscow State University, Bachelor of Science
Lomonosov Moscow State University, Master of Science


Dr. Verkhivker is currently a Professor of Computational Biology. He is also an Adjunct Professor of Pharmacology at the Department of Pharmacology, UC San Diego. His research activities are in the areas of computational cancer biology, translational bioinformatics, and computational pharmacology. He received his PhD in Physical Chemistry from Moscow University and completed a postdoctoral fellowship in computational biophysics from University of Illinois at Chicago. In 2000-2005, Dr. Verkhivker has held various research and management positions at Pfizer Global Research and Development, San Diego.  Since 2002, he has been Adjunct Professor of Pharmacology at the Skaggs School of Pharmacy and Pharmaceutical Sciences, UC San Diego. In 2006, he joined School of Pharmacy and Center for Bioinformatics, The University of Kansas as a Professor of Pharmaceutical Chemistry and Bioinformatics. Dr. Verkhivker returned to California in 2011 and joined Chapman University in August 2011 as a Full Professor of Computational Biology. Upon arrival to Chapman, Dr. Verkhivker has established a dynamic research group engaged in translational research that attracted a large cohort of undergraduate and graduate students.  He has been involved in various global University initiatives and collaborations. Dr. Verkhivker has served on a number of important committees including Search Committee for new Found Dean of BioPharmacy School. He is also chairing the Doctoral Steering Committee of the newly approved PhD Graduate Program in Computational Sciences.

Recent Creative, Scholarly Work and Publications

Allosteric Mechanisms of Protein Kinase Regulation and Drug Resistance : A Synergistic Perspective from Computational Systems Biology and Biophysical Studies. Stetz G, Tse A, Bouz J,, Agajanian S., Oluyemi O., Verkhivker GM. In Advances in Experimental Medicine and Biology Series. Protein Allostery in Drug Discovery, Springer-Nature, Eds. Jian Zhang and Ruth Nussinov, 2018, Invited Book Chapter, In press
Machine Learning Algorithms for Prediction and Analysis of Cancer Driver Genes and Mutations. Steve Agajanian, Oluyemi Odeyemi, Anna Anne Sonnenschein, Gennady M. Verkhivker. FRONTIERS IN MOLECULAR BIOSCIENCES Section "Biological Modeling and Simulation" Special Issue "Machine Learning in Biomolecular Simulations", 2018. Invited Contributed Article, Submitted
Integration of Protein Structure Network Approaches and Evolutionary Analysis into High-throughput Modeling of Protein Dynamics and Allosteric Regulations: theory, tools and applications. G. Hu, Z. Liang, GM. Verkhivker, Briefings in Bioinformatics, 2018, submitted
Machine Learning Classification and Structure-Functional Analysis of Cancer Mutations Reveal Unique Dynamic and Network Signatures of Driver Sites in Oncogenes and Tumor Suppressor Genes. Steve Agajanian, Oluyemi Odeyemi, Nathaniel Bischoff, Simrath Ratra, Gennady M. Verkhivker. J Chem Inf Model. 2018, In press
Zhou, H., Dong, Z., Verkhivker, G.M., Zoltowski, B.D., Tao, P. Allosteric mechanism of the circadian protein Vivid resolved through Markov state model and machine learning analysis. Plos Comput. Biol. 2018, In press
Biophysical Simulations and Structure-Based Modeling of Residue Interaction Networks in the Tumor Suppressor Proteins Reveal Functional Role of Cancer Mutation Hotspots in Molecular Communication. Verkhivker GM. Biochimica et Biophysica Acta (BBA) - General Subjects. 2018, In press
Data-Driven Computational Modeling of Allosteric Proteins by Exploring Dynamics, Co-evolution, and Residue Interaction Networks. Astl, L,. Verkhivker GM. J. Mol. Biol. 2018, submitted
Allosteric Mechanisms of BRAF Kinases Regulation and Combating Drug Resistance of Kinase Inhibitors: A Synergistic Perspective from Computational Systems Biology and Biophysical Studies. Stetz G, Tse A, Bouz J, Verkhivker G. J. Mol. Biol. 2016, revision submitted
A.Tse, K. Blacklock, GM. Verkhivker. Capturing Differential Sensitivity of Protein Kinases to Drug Binding and Mutations via Modeling of the Residue Interaction Networks and Allosteric Communication Pathways. Plos Computational Biology, 2015 , revision submitted
Computational modeling of Hsp90 molecular chaperone structure, dynamics and function: a synergistic perspective from biophysical simulations and systems biology analysis. N. Lawless, E. Berrigan, K. Blacklock, G. Verkhivker.Molecular Systems Biology, revision submitted