This training course is aimed at researchers who are not experts in proteomics and want to integrate quantitative proteomics results into wider biomedical experiments. We will focus on quality control from an end-user perspective, link to the underlying genomic context, multivariate analysis, protein complexes investigation, and compare different platforms for biological interpretation.
This 3 day course will introduce participants to the machine learning taxonomy and the applications of common machine learning algorithms to omics data. The course will cover the common methods being used to analyse different omics data sets by providing a practical context through the use of basic but widely used R libraries.
This course will give a comprehensive introduction to the research field of metagenomics. It will cover the basic concepts of microbiome analysis of shotgun metagenomic data using state of the art bioinformatics.
The aim of the course is to present a complete computational pipeline for the analysis and interpretation of Next-Generation Sequencing (NGS) data such as exome sequencing or targeted panels that are commonly used in the clinic.
3C-based methods, such as Hi-C, produce a huge amount of raw data as pairs of DNA reads that are in close spatial proximity in the cell nucleus. In this course, participants will learn to use TADbit, a software designed and developed to manage all dimensionalities of the Hi-C data.