Research Professor, Life Sciences Institute,
Andrei R Skovoroda Collegiate Professor, and Professor of Ecology and Evolutionary Biology, College of Literature, Science, and the Arts
1978 - 1984 Candidate of Biology (PhD) (Evolutionary Genetics) from Research
Computing Center, Pushchino
1973 - 1978 Diploma of Higher Education (MSc) (Zoology and Genetics) from
Lomonosov Moscow Federal University
Alexey Kondrashov is investigating evolutionary differences over long stretches of history through the use of high-powered computing and comparative genomics to increase our understanding of how natural selection works and why many species rely on sexual reproduction.
· Bazykin, G. A. and A. S. Kondrashov (2012). "Major role of positive selection in the evolution of conservative segments of Drosophila proteins." Proc Biol Sci 279(1742): 3409-3417.
· Naumenko, S. A., A. S. Kondrashov, et al. (2012). "Fitness conferred by replaced amino acids declines with time." Biol Lett.
· Assis, R. and A. S. Kondrashov (2012). "Nonallelic gene conversion is not GC-biased in Drosophila or primates." Mol Biol Evol 29(5): 1291-1295.
· Leushkin, E. V., G. A. Bazykin, et al. (2012). "Insertions and deletions trigger adaptive walks in Drosophila proteins." Proc Biol Sci 279(1740): 3075-3082.
· Seplyarskiy, V. B., P. Kharchenko, et al. (2012). "Heterogeneity of the transition/transversion ratio in Drosophila and hominidae genomes." Mol Biol Evol 29(8): 1943-1955.
· Naumenko, S. A. and A. S. Kondrashov (2012). "Rate and breadth of protein evolution are only weakly correlated." Biol Direct 7: 8.
· Assis, R. and A. S. Kondrashov (2012). "A strong deletion bias in nonallelic gene conversion." PLoS Genet 8(2): e1002508.
· Bazykin, G. A. and A. S. Kondrashov (2011). "Detecting past positive selection through ongoing negative selection." Genome Biol Evol 3: 1006-1013.
· Shnol, E. E., E. A. Ermakova, et al. (2011). "On the relationship between the load and the variance of relative fitness." Biol Direct 6: 20.
Kondrashov, A. S. and R. Assis (2010). "Bridges: a tool for identifying local similarities in long sequences." Bioinformatics 26(16): 2055-2056.