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Genomic methods are used to study various biological phenomena across a broad range of research fields, and they will likely soon become part of a basic toolbox of each biologist. Unlike "classical" approaches, which typically study just one or a few selected genes/transcripts etc., genome-wide approaches are used to analyze whole genomes/transcriptomes, and allow us to get a global overview of the studied topic and capture the broader context. The course introduces a range of basic genomic methods and approaches, with emphasis on understanding the principles and specifics of "-omic" research. Examples of genomic experiment design and evaluation will also be presented. Introduction of methods during lectures will be complemented with computational data analyses during practical sessions. The course is primarily intended for MSc/BSc students of experimental biology. Basic knowledge of cell and molecular biology, genetics and (at least a bit of) statistics is required. This is a highly interactive course and questions & discussions are more than welcome.
IMPORTANT: Bioinformatics students - do not take this course. Instead, take the "Genomics - Approaches and Algorithms (MB151P130)" course, which is mandatory for your MSc program. The course is taught with the support of the project ESF pro VŠ II na UK, Reg. num.: CZ.02.2.69/0.0/0.0/18_056/0013322 Last update: Převorovský Martin, RNDr., Ph.D. (07.02.2022)
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Course materials from lectures and practical sessions (including recommended reading items) are available via Moodle. Last update: Převorovský Martin, RNDr., Ph.D. (29.05.2020)
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credit (zápočet) - active participation at practical sessions exam - ability to apply information from lectures and practicals will be determined using a written test and a practical assignment Last update: Převorovský Martin, RNDr., Ph.D. (29.05.2020)
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Topics covered: - microarrays, next generation sequencing - how they work, technologies, applications, advantages, limitations - analyses of genome, transcriptome (RNA-seq), translatome..., single-cell analyses - epigenomics - chromatin modifications, transcription factor binding sites (ChIP-seq) - analysis of 3D nuclear architecture - chromosome conformation capture methods (HiC) - metagenomics - analysis of environmental samples, composition of microbial communities - genetic interactions - mutant libraries, synthetic genetic array, siRNA screens, mapping the functional architecture of a cell - chemical genetics - identification of novel targets for therapy - tools for genomic data processing and analysis - Galaxy framework, genome browsers... - visualizing genomic data - integrating data from various methods - databases for "omics" data
Practical sessions will be based on online tools and resources (eg. Galaxy). No programming skill are needed. Last update: Převorovský Martin, RNDr., Ph.D. (29.05.2020)
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General knowledge of cell and molecular biology, genetics, and basic knowledge of statistics are required for understanding the course materials. You must be able to log into CAS (https://ldap1.cuni.cz/) for the practical sessions. No programming skills are required. Last update: Převorovský Martin, RNDr., Ph.D. (29.05.2020)
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