EMBL Course: Analysis and integration of transcriptome and proteome data

EMBL

06 March 2022

EMBL Advanced Training Centre

Registration Deadline

23 January 2022

Course Overview

Systems biology is a still expanding field of research aiming to understand at the molecular level how cells, tissues and organism operate in their biological context. Among the key technologies driving this forward are next-generation sequencing and proteomics, as they provide powerful means to determine global expression levels of genes and proteins. Both fields have matured to a degree that they have now become accessible to researchers in many areas of biology. During this course participants will gain theoretical insight in the structure of sequencing and proteomic data, and will receive training in data analysis using various computational tools.


Audience

This course is targeted at biologists and biochemists who are (starting to be) involved in both next-generation sequencing and mass spectrometry-based proteomics, but who are not experts in these fields.


Modules/Resources

Principles of mRNA quantification

Principles of protein identification and quantification

Principles and application of bioinformatic tools for mining of transcriptome and proteome data

Data integration by Cytoscape


Learning Outcomes

The aim of this practical course is to provide insight in techniques that are frequently used for transcriptome and proteome analysis, and to provide hands-on experience turning primary data into information that can be used for further biological interpretation. To achieve these goals, participants will gain insight in the basic principles of gene expression analysis (RNAseq data quantification and differential expression analysis), protein identification and quantification, and they will be trained in the use of software tools to analyse sequencing and proteomic data (SearchGUI, PeptideShaker, MaxQuant). In addition, the course will provide insight in the complementarity of transcriptome and proteome data by their integrative analysis via Cytoscape.