| Titel |
Computational analysis of transcriptomes and proteomes
|
| Title |
Computational analysis of transcriptomes and proteomes |
| Schwerpunkt/Focus |
|
| Sprache/Language |
englisch |
| VV-Nr./Course No. |
136123 |
| Modulverantwortlich/Responsible |
Dr. Carsten Kemena |
| Vertreter/Co-responsible |
|
| Anbieter/Teachers |
Prof. Dr. E. Bornberg-Bauer; Dr. M. Harrison; Dr. A. Lange |
| Typ/Type |
Seminar und Praktikum |
| SWS/Semerster periods per week |
|
| Arbeitslast(h)/Work load |
150 |
| KP/Credit points |
5 |
| Zuordnung/Classification |
Fortgeschrittenen-Modul |
| Semester/Semester |
SoSe |
| Studierende/Students |
MSc Biowissenschaften
MSc Biotechnologie
MSc Molekulare Biomedizin |
| Corona-Informationen/Corona-Information |
|
| Zeit/Date |
Block 3: 24.06.24-19.07.2024 |
| Ort/Location |
Hüfferstr. 1 |
| Beginn/Start |
24.06.2024 - 10.00 |
| Vorbesprechung/Obligatory pre-meeting |
|
| Voraussetzung/Prerequisite |
keine |
| Anmeldung/Registration |
Online-Anmeldung |
| Leistungskontrollen/Performance assessments |
To be determined |
| Termine f. Leistungskontrollen/Date for performance assessments |
|
| max. NP/Max. grade points |
200 |
| Ziele/Aims |
The goal of this course is to teach theoretical and practical knowledge about transcriptomic and proteomic analyses |
| Inhalte/Content |
I got my sequencing data and now what? I know there are genomes online, but how can I analyse them? How can I organise my data effectively? ... If you are keen to learn the basics of transcriptomics and proteomics, this course will help you along.
In this course we will go through the entire pipeline from genome assembly and annotation to current methods of proteomics and transcriptomics
1. Part: Linux Command Line & Research Data Management
Here, we introduce the Linux command line, which provides a lot of useful text manipulation tools that can be used to get a first impression of your data and prepare it for further analyses. We‘ll use the HPC cluster for these analyses.
Futhermore, we will have a look at good research data management: How to store your data, keeping records of your analysis steps and an overview of your results.
2. Part: Assembly & Annotation
We will assess the quality of the sequencing data and assemble the genomes. Further steps like purging, scaffolding and polishing are going to be introduced.
In a next step, we will annotate genomes and analyse genome and proteome quality.
3. Part: Transcriptomics & Proteomics
During the transcriptomics part, we mainly focus on differential expression analyses.
For the proteomics part we will discuss and apply different analyses like orthology prediction, domain based analyses.
4. Part: Analysing data
Here, you will do an analysis of data using the methods taught in the previous parts.
|
| Methoden/Methods |
- Linux Command Line
- Orthology prediction using OrthoFinder
- Domain based analyses (e.g. DOGMA, DomRates)
- Differential expression analyses
|
| Berufsrelevante und interdisziplinäre Komponenten/Occupational and interdisciplinary skills |
|
| Voraussetzung für/Prerequisite for |
|
| Präsenzpflicht/Compulsory presence |
|
| Plätze/Number of participants |
12 |
| Gruppengröße/Group size |
|
| Materialien/Materials |
|
| Literatur/Literature |
|
| Links |
|
| Sonstiges/Further information |
|
= Modul gehört zum SPP Imoplant / Module is part of the SSP Imoplant
= Modul gehört zum SPP Evolution /Module is part of the SSP Evolution
= Modul gehört zum SPP Bioanalytics and Biochemistry /Module is part of the SSP Bioanalytics and Biochemistry
= Modul gehört zum SPP Neuroscience and Behaviour /Module is part of the SSP Neuroscience and Behaviour
= Modul gehört zum SPP Quantitative Cell Biology /Module is part of the SSP Quantitative Cell Biology