Field of Study Details
Bioinformatics and Biocomputing
Length of Study: 2 years
Min. Credits: 120
Degree Programme: Information Technology
Language of Instruction: Czech
Form of Study: full-time
Accredited from: 2008 Accredited till: 2024 Last admissions: 2019
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 and work in multidisciplinary teams. The knowledge acquired by studying the biological systems will be used for understanding bio-inspired computing systems. Students will get acquainted with the principles of natural computing, in particular, with evolutionary design, evolvable systems, DNA computing, fuzzy computing, neural computing and unconventional computing. Students will be able to integrate the bio-inspired principles into existing systems in order to improve their efficiency.
Student of the branch acquire deeper knowledge in the bioinformatics and natural computing. This give him knowledge and skills base to analyse, design and verification of problems of biological databases as well as use, design, implement and accelerate algorithms for analysis of the biological data. He/she is able to apply natural computing algorithms (evolutionary algorithms, artificial neural networks, fuzzy systems etc.) in the complex design and optimization problems.
- A graduate has good insight into bioinformatics and natural computing; he/she is familiar with concepts of molecular genetics. A graduate can utilized biological databases as well as use, design, implement and accelerate algorithms for analysis of the biological data. He/she is able to apply natural computing algorithms (evolutionary algorithms, artificial neural networks, fuzzy systems etc.) in the complex design and optimization problems.
- A graduate has good insight into information technology, particularly into advanced database systems, theoretical computer science, hardware/software codesign and parallel and distributed algorithms.
- A graduate is ready for development, operation and management of bioinformatic computer systems, further for the research and development work in the area of methods, tools and technologies for bio-inspired computing systems. He/she is able to perform an experimental work, analyze and interpret data. He/she is able to work individually or in a team, present the results in written or oral form and further educate him/her-self.
- A carrier is possible in professions such as bioinformatic system developer, system integrator, programmer, and database/information system administrator in biotechnological companies, health service or police. Graduates in this specialization can use their education in development and research divisions of the companies dealing with methods, tools and technologies for bioinformatic system development and further in companies which utilize artificial intelligence principles in their products.
The State Final Examination has two parts: A defense of the Master Thesis, and a discussion based on selected topics from the topic "Bioinformatics and biocomputing which is derived from compulsory courses of the MBI Branch of Study as Bioinformatics, Bio-inspired Computers, Game Theory, Advanced Bioinformatics, Knowledge Discovery in Databases, Biometrics Systems, Soft Computing, Mathematical Structures in Computer Science, Theoretical Computer Science, Hardware/Software Codesign, Molecular Genetics, Advanced Database Systems and Parallel and Distributed Algorithms. The areas of possible questions must be approved by the Study Branch Council, and students will be informed about the selected topics at least 2 months before the state final examination is held in the particular academic year.
- Protein structures prediction
- Microchip data analysis for gene expression detection
- Molecular structures visualization
- Hardware accelerated search in biological databases
- Evolutionary classifier design for biological data
- Hardware acceleration of evolutionary design
- Symbolic regression for biological data analysis
- System modelling using cellular automaton
Choose academic year and curriculum
|MAT||Mathematical Structures in Computer Science *)||5||C||Ex||FME|
|PDB||Advanced Database Systems||5||C||Cr+Ex||FIT|
|TIN||Theoretical Computer Science||7||C||Cr+Ex||FIT|
|PRL||Parallel and Distributed Algorithms||5||C||Cr+Ex||FIT|
|PP1||Project Practice 1||5||E||Cr||FIT|
|ZZN||Knowledge Discovery in Databases||5||C||Cr+Ex||FIT|
|PP2||Project Practice 2||5||E||ClCr||FIT|
Duty: C - compulsory, CEx - compulsory-elective group x, R - recommended, E - elective
|Abbrv||Min. courses||Max. courses||Min.cred||Over as||Courses||Title|
|C||1||9||0||E||HSC, NAV, PCS, PDS, PPP||Hardware and Networks|
|H||1||1||3||E||AEU, FCE, FIK, FIT, HKO, HVR, JA3, PRM, RET||Social Course|
|I||1||9||0||E||AGS, EVO, SIN, SNT||Modern Artificial Intelligence|
|O||1||9||0||E||BIS, KRY, NSB, POS||Operating Systems and Security|
|S||1||9||0||E||KKO, ZPJa, ZRE||Data and Signal Processing|