Prediction of Evolutionary Dynamics of Pathogens
Evolution of pathogens allows them to evade host immune system, contributing to disease and death caused by them. We are trying to predict such dynamics, notably in Influenza A, hoping to improve vaccine strain selection.
Mutations in Germline and in Cancer
Mutations in human genome arise due to a wide range of processes. Changes in these processes, e.g. exposure to ultraviolet rays or a modification of a protein involved in handling of DNA, may lead to increase in the rate of mutations and/or change their character. We infer changes in mutagenesis from changes in the mutation rates and patterns observed in large-scale sequencing data. Ultimately, such approaches might improve understanding of heritable mutagenesis and cancer diagnosis and treatment.
Inference of Natural Selection and Genetic Interactions from Genomic Data
Mutations may be advantageous or deleterious. Whether a particular mutation harms the cell carrying it, or does it good, may be inferred from its rate of spread, which can in turn be inferred from sequencing data. Moreover, interactions between mutations shape the phenotype. We develop approaches for inference of selection forces and interactions from genetic data.
Supervisor – Georgii Bazykin
|Team:||Olga Vakhrusheva||Elena Nabieva||Maria Andrianova|
|PhD students:||Valentina Burskaya||Aleksandra Bezmenova||Kseniia Safina|
|Anastasia Stolyarova||Evgeniia Alekseeva||Ivan Kuznetsov|
Skoltech Biomedical Initiative