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The course aims to provide a view and practical knowledge of data downloading, handling, processing, and visualization methods of various high-throughput experiments. The most important topics of the practical: (1) Introduction to the computer environment and to bash, (2) Introduction to next-generation sequencing, (3) Genomics, (4) Chip-seq, (5) Transcriptomics (RNA-seq), (6) Functional enrichment analysis, (7) Marker gene amplification metagenomics (16S rRNA), and (8) Proteomics.
The most up-to-date schedule, detailed description and requirements can be found here: https://docs.google.com/document/d/1okHYnyxcyyCyohYHSyNDFSWE4sEnllHoQKyvVrJ2-Z0/edit?usp=sharing
At the end of the course, the learner will have this knowledge:
Knows how to process high-throughput genetics and proteomics data.
Understands the next-generation sequencing methods, data, and how to process the “reads” in the case of genomic, Chip-seq, RNA-seq, and 16S rRNA metagenomics sequencing.
Knows the fields of application of modern biological research methods, understands the importance of the development of these methods, and contributes to it as much as possible.
Has systematic scientific knowledge.
Knows the connections between the knowledge acquired in different subjects, and understands the importance of an interdisciplinary approach.
At the end of the course, the learner will be able to:
Able to express oneself professionally, both in oral and written form in the field of bioinformatics, high-throughput genetics and proteomics.
Able to systematize data and knowledge, and analyse and evaluate them according to scientific aspects.
Can recognize and integrate connections between the knowledge of different scientific fields.
Attitude:
Adheres to and makes others follow the rules of research ethics.
Actively disseminates the results of the field of science, confidently publishes knowledge even in the media, and defends his/her professional position against representatives of other approaches and pseudoscience, if necessary.
Open to new biological and other scientific research results and scientific cooperation. Seeks to further develop existing results and actively promotes the development of new research directions.
Committed to quality work, sets a high standard for the scientific knowledge and advancement of himself and fellow researchers.
Autonomy and responsibility:
Expresses views on biological, bioinformatics and high-throughput method issues responsibly in professional and non-professional circles.
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Weekly grades: You will receive a grade for your work weekly. If you could finish your work during the practical you will receive the weekly grade there. If you were not able to finish your work during the practical you can send the solutions and the log file by e-mail to the lecturer before the end of the actual week(!). After a week has passed since the practical, each additional week will result in a minus one grade. (For example: if you send a fully solved practical 10 days after the practical you will get grade 4 for that work.)
If you didn’t miss any practicals, you can have a maximum of 11 weekly grades.
The mean of the weekly grades will make up half of your final grade.
Missing a practical: MSc students can miss a maximum of 3 practicals. This means that you won’t receive a grade for that week, nor will it count towards your final grade.
The exam: Each of you has to choose a data set to analyse using the methods you’ve learned in the course. So you can do proteomics, SNP analysis, RNA-seq, ChIP-seq analysis, etc. It is up to you to decide what kind of analysis you will perform. Do not hesitate to contact us if you need assistance choosing a topic or data set(s). If you decide what dataset to use and what analyses to conduct, please write 3-4 sentences by (date: TBA) here: (link to the document). By (date: TBA), the lecturers will determine whether the promoted topic and dataset are appropriate for the exam.
Following that, you perform the analysis on your own. Ensure that every step is reproducible by creating a log file or a report. Prepare a 10-minute presentation with slides that describe the data set, the analysis, and the results. Send us the log file or report of the analysis by email by (date: TBA).
Present your work to the lecturers and peers on (date: TBA) during the practical. The lecturers and peers may ask questions about the analysis you presented.
The final practical grade is based on your work throughout the semester (50%) and your presenta
Recommended literature, papers, and websites will be provided at the end of each lecture.
Individual and group works during the practicals on computers.
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Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Education and Culture Executive Agency (EACEA). Neither the European Union nor EACEA can be held responsible for them.
