M.Sc., Mathematics, Belarusian State University, 2004
Ph.D., Computer Science, Belarusian State University, 2007
Bioinformatics, computational biology, graph theory, combinatorics
I received my Ph.D. degree in theoretical computer science from Belarusian State University in Minsk (Belarus) in 2007. From 2007 to 2010 I was a lecturer there. In 2010, I joined the National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention of the Centers for Disease Control and Prevention, where I worked as a computational biologist until 2016. My research there was recognized by several CDC awards. In 2016, I joined Georgia State University as an assistant professor.
My research areas are computational biology, bioinformatics, and graph theory. In biology, my research focuses on studying epidemiology and the evolution of highly mutable RNA viruses, such as the human immunodeficiency virus (HIV) and the hepatitis C virus (HCV). Using analysis of molecular data and mathematical modelling, I am trying to understand how viruses escape the immune system, acquire drug resistance, and spread through a population of susceptible individuals. This involves the development of novel algorithms for processing biomedical big data. I am especially interested in studying the roles of complex networks in viral evolution, including epidemiological networks, genetic networks, and cross-immunoreactivity networks. I am also doing research in graph theory and discrete mathematics, where my favorite research topics are graph decompositions and representations of graphs as derived objects of other discrete systems, which make it possible to build bridges between various scientific disciplines, such as computer science, evolutionary biology, epidemiology, combinatorics, topology, and algebra.
A.S. Gargis, et al., Good laboratory practice for clinical next-generation sequencing informatics pipelines, Nature Biotechnology, vol. 33, 2015, pp. 689–693.
P. Skums, L. Bunimovich, and Y. Khudyakov, Antigenic cooperation among intrahost HCV variants organized into a complex network of cross-immunoreactivity, Proceedings of the National Academy of Sciences of the United States of America, vol. 112, no. 21, 2015, pp. 6653–6658.
P. Skums, et al., Computational framework for next-generation sequencing of heterogeneous viral populations using combinatorial pooling, Bioinformatics, vol. 31, no. 5, 2015, pp. 682–690.
D.S. Campo, et al., Drug-resistance of a viral population and its individual intra-host variants during the first 48 hours of therapy, Clinical Pharmacology and Therapeutics, vol. 95, no. 6, 2014, pp. 627–635.
P. Skums, et al., Reconstruction of viral population structure from next-generation sequencing data using multicommodity flows, BMC Bioinformatics, vol. 14 (suppl 9):S2, 2013.
P. Skums, H-product of graphs, H-threshold graphs and threshold-width of graphs, Discrete Mathematics, vol. 313, no. 21, 2013, pp. 2390–2400.
P. Skums, et al., Efficient error correction for next-generation sequencing of viral amplicons, BMC Bioinformatics, vol. 13 (suppl 10):S6, 2012.
P. V. Skums, S. V. Suzdal, and R. I. Tyshkevich, Operator decomposition of graphs and the reconstruction conjecture, Discrete Mathematics, vol. 310, no. 3, 2010, pp. 423–429.