Artificial intelligence in bioinformatics
Project tasks:
Code prediction of functional genomic elements by deep learning methods based on omics-based molecular biology data
- Development of efficient and accurate machine learning models for finding secondary DNA structures and for identifying meaningful associations with epigenetic code elements
- Testing the performance of models based on other deep learning architectures - transformers
Refinement of antibody shape prediction and epitope detection by deep learning methods
- Computer modelling of antibody-antigen interaction for antibody selection for further synthesis
- Development of algorithms that predict not only the unchanging parts of an antibody, but also its variable parts
Machine learning for solving problems of population genetics
- Studying mechanisms of adaptation and natural selection both from a purely scientific point of view and in applied tasks of epidemiology, personalised medicine and others
Project team
![](/pubs/share/thumb/903123862:c2300x2300+710+0:r190x190!.jpg)
Dmitry Glyzin
![](/pubs/share/thumb/444191823:c1125x1125+0+19:r190x190!.jpg)
Elena Pavlovna Zbirovskaya
Vladislav Perelygin
![](/pubs/share/thumb/422566698:c2184x2184+0+148:r190x190!.jpg)
Aleksandr Fedorov