MSc seminars for Bioinformatics (course group defined by Faculty of Mathematics, Informatics, and Mechanics)
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2023 - Academic year 2023/24 2024 - Academic year 2024/25 (there could be semester, trimester or one-year classes) |
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| 2023 | 2024 | |||||||
| 1000-5D22ADB |
 
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Classes
Academic year 2023/24
Groups
Brief description
The seminar topics include computational biology and machine learning in application to biomedical data analysis. We are interested in the problems of human diseases such as cancer or infectious diseases. From the area of computational biology we focus on analysis of modern molecular profiling data, analysis of single cell sequencing data, medical imaging, or protein structure. From methods, we focus on probabilistic graph models, statistical data analysis, machine learning, including deep learning, and generative models. |
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| 1000-5D22ADP |
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Classes
Academic year 2023/24
Groups
Brief description
The subject of the seminar covers the basic branch of computational biology which is proteomics, i.e. the analysis of proteins in living organisms. We focus on algorithms and mathematical models that allow for the interpretation of data obtained by the spectrometric technology. |
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| 1000-5D22BGO |
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Classes
Academic year 2023/24
Groups
Brief description
The subject of the seminar covers the basic sections of bioinformatics and computational genomics, with particular emphasis on the applied mathematical models and algorithmic methods. We are interested in molecular sequence analysis, comparative genomics, evolution and organization of genomes, phylogenetics and molecular evolution, as well as analysis of data from high-throughput sequencing and other large-scale experimental techniques of modern genomics. |
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| 1000-1D10MBS |
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Classes
Academic year 2023/24
Groups
Brief description
We will discuss mathematical models and methods used in natural and social sciences. We will analyze complex processes in Physics, Biology, Medicine and Social Sciences that can be described by discrete and continuous dynamical systems both deterministic and stochastic. |
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