Anton Zhiyanov

Researchers at HSE University and MSU have established a universal law governing the time to extinction of a population in a random environment. Their analysis of the evolution of branching processes—complex probabilistic systems—shows that, regardless of the initial population size, extinction follows strict mathematical laws. The results have been published in the Journal of Applied Probability.

A press release has been released on the HSE website (https://www.hse.ru/news/science/1152167635.html) based on an article about the unique properties of miR-93-5p microRNA (published in the journal PeerJ https://peerj.com/articles/20642/). HSE researchers have discovered an atypical behavior of oncogenic miR-93-5p microRNA in prostate cancer. It turned out that its various isoforms do not change the spectrum of target genes, but rather enhance each other's effects.

On 27 February 2026, Anton P. Zhiyanov, a research fellow at the Laboratory of Molecular Physiology, Faculty of Biology and Biotechnology, HSE University, successfully defended his dissertation “Methods for Evaluating the Quality of Linear Classifiers for microRNA Sequence Analysis” before the HSE University Dissertation Council in Computer Science. The thesis develops an axiomatic framework for comparing classification metrics, proposes new statistical tools for verifying linear classifiers, and applies them to the bioinformatics problem of microRNA isoform prediction. By its decision of 26 March 2026, the Dissertation Council conferred the sought-after degree on Anton.

miR-93-5p microRNA in prostate cancer retains a similar set of targets even with the formation of 5’ isoforms. This indicates the stability of its regulatory function to structural variations.

Research by a collaborative team from HSE University's Faculty of Biology and Biotechnology, Moscow State University, and the Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry of the Russian Academy of Sciences has been officially published in the international journal Stat. The study addresses a critical challenge in biomedicine: determining whether machine learning algorithms identify genuine biological patterns or merely overfit to random noise in data.

In biomedical research, machine learning algorithms are often used to analyse data—for instance, to predict cancer recurrence. However, it is not always clear whether these algorithms are detecting meaningful patterns or merely fitting random noise in the data. Scientists from HSE University, IBCh RAS, and Moscow State University have developed a test that makes it possible to determine this distinction. It could become an important tool for verifying the reliability of algorithms in medicine and biology. The study has been published on arXiv.

The conference was held on 11 July 2024

Leading scientists from HSE University have won the Scientific Category of the 2024 Best Russian-Language Scientific and Popular Science Works Competition by HSE University employees in the "Biology and Medicine" section for their research on predicting the effectiveness of chemotherapy with gemcitabine in patients with bladder cancer.

Scholars from HSE University and the RAS Institute of Bioorganic Chemistry have demonstrated the efficiency of T-cell immune response against the Omicron variant of SARS-CoV-2. In approximately 90% of vaccinated Europeans, T-cell immunity was as effective against Omicron as with other variants. The results of the study were published in PeerJ.