Bioinformatics and Biocomputing

Students will get acquainted with the advanced algorithms for processing, analysis and presentation of biological data, in particular genomic and proteomic data. In addition to the use of the standard algorithms, students will be able to develop new algorithms in this area. Students will become familiar with the concepts of molecular genetics and with standard biological databases. Students will be able to communicate with biologists. The knowledge acquired by studying biological systems will be used for understanding bio-inspired algorithms and computers. Students will get acquainted with the principles of natural computing, in particular, with evolutionary algorithms, artificial neural networks, DNA computing, and unconventional computing and with the  machine learning principles in general. Students will be able to integrate the bio-inspired principles into existing algorithms and computers in order to improve their efficiency. 

The State Exam in Information Technology and Artificial Intelligence, specializing in Bioinformatics and Biocomputing, consists of the following parts:

• presentation and defense of master's thesis,
• oral exam, which combines the basic themes contained in the courses profiling the basis of Information Technology and Artificial Intelligence (Theoretical Computer Science, Statistics and Probability, Computer Systems Architectures, Artificial Intelligence and Machine Learning, Data Storage and Preparation, Functional and Logic Programming, Parallel and Distributed Algorithms, Modern Trends in Informatics),
• oral exam, which combines the basic themes contained in the courses profiling the fundamentals of Bioinformatics and Biocomputing (Molecular Genetics, Bioninformatics, Advanced Bioinformatics, Biology Inspired Computing, Knowledge Discovery in Databases, Convolutionary Neural Networks, Practical Parallel Programming).

All parts of the state examination are held on the same date before the State Examination Board. The state exam can be taken by a student who has obtained the required number of credits in the prescribed composition necessary for the successful completion of the master's degree and has submitted the master's thesis in due time. The organization and course of the state examination are given by the corresponding internal standard of the faculty and by the relevant instructions of the program guarantor for state examinations.

• Reconstruction of repetitive DNA elements
• Geometric semantic genetic programming
• Principles and applications of neuroevolution
• Search for enzymes in metagenomic data
• Bioinformatic tool for annotation of transposons