Without assuming prior knowledge of programming, biology students will learn the basics of programming using the PYTHON language and data science skills based on R. The specialization also includes subjects on bioinformatics algorithms, molecular phylogenetics, structural bioinformatics, systems biology and the bioinformatics aspects of various types of omics data. In collaboration with the Physics Institute, there are specific subjects in the emerging field of data science and machine learning. All courses have a very strong practical focus, encouraging thinking and problem solving instead of passive learning.
During the course, you will learn how to navigate the linux operating system and become familiar with the basics of programming using PYTHON, one of the most commonly used programming languages in bioinformatics. During this practice oriented course, you will write short scripts and encode simple algorithms that are relevant in biology and bioinformatics.
You will become more familiar with the most fundamental bioinformatics algorithms by implementing them, and will get hands-on experience on how these algorithms can be used to solve biological problems. This course also aims to advance your programming skills and algorithmic thinking.
During the course, you will learn the fundamentals of computational analysis of large biological datasets. You will learn about how to process, analyze and visualize data generated by various omics approaches, including genomics, transcriptomics, metabolomics, and proteomics. You will learn how to interpret the results in a biological context, and identify and apply follow-up analyses based on this.
Macromolecular structures are fundamental to our understanding of biochemical processes, as well as to our ability to manipulate them through various drug molecules. This course mostly focuses on proteins and covers structure determination methods, classification of protein structures, various structure prediction approaches and fundamental methods to characterize the dynamic properties of proteins.
This course gives a succinct introduction to modern phylogenetics methods with an emphasis on probabilistic methods. Starting with the conceptual foundations, the course proceeds by introducing substitution models in an accessible manner, starting with the simplest two state models, and proceeding to DNA models and arriving at state-of-the-art models of sequence evolution.
In addition to these courses, we encourage students to choose additional topics related to their main topic of interest.
You can find the final exam topics here. (2023)
| Code | Subject | Semester | Subject Type | Credit | Subject coordinator |
| pytbioib19lm | PYTHON programming for biologists | 1 | Bioinformatics mandatory (32cr) | 8 | Kozsik Tamás |
| kutmodub17gm | Research methods PR | 1 | Professional subjects (17cr) | 6 | Miklósi Ádám |
| biometub17vm | "Biometry and advanced biostatistics L+PR" | 1 | Science subjects (11cr) | 5 | Podani János |
| bioinfub17gm | Bioinformatics PR | 1 | Science subjects (11cr) | 4 | Vellai Tibor |
| szabiohb17em | Regulatory biology L | 1 | Mandatory elective(24cr) | 4 | Világi Ildikó |
| bioinfub17em | Bioinformatics L | 1 | Science subjects (11cr) | 2 | Vellai Tibor |
| gentecub17em | Genetechnology L | 1 | Professional subjects (17cr) | 2 | Málnási-Csizmadia András |
| evojatsb17em | Evolutionary game theory L | 1 | Mandatory elective(24cr) | 2 | Scheuring István |
| immunomb17em | Immunology L | 1 | Mandatory elective(24cr) | 2 | Kacskovics Imre |
| progengb17em | Regulation of prokaryotic gene expression L | 1 | Mandatory elective(24cr) | 2 | Varga Máté |
| bioetiub17em | Bioethics and Philosophy of Science L | 1 | Professional subjects (17cr) | 1 | Lőw Péter |
| evojatsb17em | Computational Biology Algorithms | 2 | Bioinformatics mandatory (32cr) | 8 | Dosztányi Zsuzsanna |
| immunomb17em | Analysis of Omics Data | 2 | Bioinformatics mandatory (32cr) | 8 | Vellai Tibor |
| szammosb17gm | Computer modelling in biology PR | 2 | Mandatory elective(24cr) | 6 | Müller Viktor |
| gentecmb17lm | Gene technology PR | 2 | Mandatory elective(24cr) | 6 | Nyitray László |
| baktaxmb17lm | Bacterial taxonomy and virus diagnostic PR | 2 | Mandatory elective(24cr) | 6 | Tóth Erika |
| mamgy1ub17gm | Advanced Methodology I. PR | 2 | Professional subjects (17cr) | 4 | Nyitray László |
| dsexplorf17vm | Data Exploration and Visualization | 2 | Mandatory elective(24cr) | 4 | Visontai Dávid |
| pubangnb17gm | Writing Scientific Papers in English PR | 2 | Mandatory elective(24cr) | 3 | Böddi Béla |
| rendb1ub17em | Systems and omics biology I. L | 2 | Professional subjects (17cr) | 2 | Dobolyi Árpád |
| fehtudmb17em | Protein Science L | 2 | Mandatory elective(24cr) | 2 | Kovács Mihály |
| novionnb17em | Plant ionomics L | 2 | Mandatory elective(24cr) | 2 | Fodor Ferenc |
| baktaxmb17em | Classical and molecular bacterial taxonomy L | 2 | Mandatory elective(24cr) | 2 | Tóth Erika |
| diplm1ub17dm | Thesis Research Work I. PR | 3 | Thesis work (30 cr) | 5 | Nyitray László |
| progengb17em | Structural bioinformatics | 3 | Bioinformatics mandatory (32cr) | 4 | Gáspári Zoltán |
| szabiohb17em | Advanced Methodology II. PR | 3 | Bioinformatics mandatory (32cr) | 4 | Dosztányi Zsuzsanna |
| phygenib19vm | Phylogenetics | 3 | Mandatory elective(24cr) | 4 | Szöllősi Gergely |
| sembioib19gm | Seminars in bioinformatics | 3 | Mandatory elective(24cr) | 4 | Dosztányi Zsuzsanna |
| dsminingf17vm | Data Mining and Machine Learning | 3 | Mandatory elective(24cr) | 4 | Csabai István |
| dsmodelsf17vm | Data Models and Databases in Science | 3 | Mandatory elective(24cr) | 4 | Kiss Attila Elemér |
| genpopgb17em | Genetics and population genetics L | 3 | Mandatory elective(24cr) | 3 | Vellai Tibor |
| novionnb17lm | Plant ionomics PR | 3 | Mandatory elective(24cr) | 3 | Fodor Ferenc |
| terembub17em | Nature and humankind L | 3 | Professional subjects (17cr) | 2 | Oborny Beáta |
| genomigb17em | Genomics L | 3 | Mandatory elective(24cr) | 2 | Egyed Balázs |
| diplm2ub17dm | Thesis Research Work II. PR | 4 | Thesis work (30 cr) | 25 | Nyitray László |
| advrprib19gm | Advanced R programming for biologists | 4 | Mandatory elective(24cr) | 4 | Kaposi Ambrus |
| evotorsb17em | Reconstructing evolutionary history from molecular sequences L | 4 | Mandatory elective(24cr) | 2 | Szöllősi Gergely |
| Code | Subject | Semester | Subject Type | Credit | Subject coordinator |