Deep learning in life science

elective monographs

Practical applications of deep learning models in current problems of molecular biology (medical imaging, structural bioinformatics and biological sequence analysis).

We will learn about the current approaches using deep learning methods (convolutional neural networks, recurrent neural networks, transformer-based networks) for classical problems in molecular biology and medicine (microscopy image classification, protein structure prediction and analysis, biological sequence analysis and classification).

The video lectures are available online (https://deeplife4eu.github.io/program) Labs are going to be held in person.

Materials available online: https://deeplife4eu.github.io/program.

Students will gain knowledge of contemporary deep learning methods, be able to implement deep learning models, and evaluate their quality for biological applications. Students will also gain experience and competence in presenting the principles of model operation and the results of computational experiments involving training networks on experimental data and optimizing the parameters of such models.

Individual homework scores (50 %) and a final team project (50%), 60% total points are required for a passing grade.