Systems Biology of Human Metabolism and Gut Microbiome
(3 ECTS)

April 08-12, 2024

Lecturers: Adil Mardinoglu, Fredrik Edfors, Cheng Zhang, Ozlem Altay, Linqi Meng
Keynote Speakers: TBD

Aim

The aim of the course is to give students a fundamental understanding of

1. how high-throughput omics data including proteomics, bulk and single-cell transcriptomics, and metagenomics data can be analysed
2. how mathematical modelling of biological systems can be used to gain novel biological insight through integration of multi-omics data.

A number of examples from analysis of data from different studies of mouse, rat and human tissues in different physiological conditions will be introduced. Students will further get hands-on experience with analysis of raw data from both bulk and single-cell transcriptome, metagenome data and will be introduced to how such data can be analysed using different statistical techniques. Methods for reconstruction of metabolic network models, analysis and use of these for simulation of biological functions in different cells/tissues will be presented. Finally, the students will learn about integrated data analysis through a number of different examples. The overall objective is that each PhD student attending this course should be able to work independently in the field of systems biology.

Intended learning outcomes:

• Analyze raw omics data (e.g. Proteomics, Transcriptomics, Metabolomics, Metagenomics)
• Select the right statistical method for the right omics analysis and compare the results using different methods
• Generate biological networks using biochemical information and omics data
• Integrate multiple omics data using biological networks
• Analyze multiple omics data from different disease or environmental conditions.

Course Contents

The course will have a focus on omics analysis and how these data are analysed using different methods. Concepts of proteomics, transcriptomics, and metagenomics will be presented and how biological networks can be used for integration of high-throughput omics data. The course will further give insight into how metabolic networks can be reconstructed from biochemical and genomic information. Topological analysis of large genome-scale metabolic models (GEM) as well as Integrated Networks (INs) will be performed. Simulation of GEMs and INs will be performed. Throughout the course there will be examples from studies of human and gut microbiome in different clinical and environmental conditions

• Proteomics analysis
  • Describe the concepts of proteome analysis
  • Perform analysis of raw proteomics data, perform differential expression analysis using different methods, principal component analysis, clustering of data, functional GO and KEGG pathway analysis
  • Describe the concepts of integrated data analysis using protein-protein interaction networks
• Transcriptomics analysis
  • Describe the concepts of transcriptome (RNA-seq) analysis
  • Perform analysis of Raw RNA-seq data, and perform differential expression analysis using different methods, principal component analysis, clustering of data, functional GO and KEGG pathway analysis
• Single-cell transcriptomics analysis
  • Describe the concepts of single cell transcriptomics (scRNA-seq) analysis
  • Perform analysis of single cell count data, and perform quality control, cell clustering, marker gene identification, cell type annotation, differential expression analysis, and single cell data visualisation
• Metagenomics analysis
  • Describe the concepts of metagenomics analysis
  • Primary processing of metagenomics data for quantitative metagenomics applications, quality controls (cleaning and filtering), mapping the reads and counting the genes in very large reference catalogues, functionals analysis and clustering of data.
• Biological network analysis for integration of data
  • Genome-scale metabolic network reconstruction based on biochemical, genomic, transcriptomics and proteomics information
  • Integrated Networks based on transcriptomics, proteomics and DNA-seq information
  • Perform simulation based on linear programming of network metabolic models
  • Perform metabolic control analysis of simple reaction network models
  • Perform multi-omics analysis for a disease or environmental conditions

Course organization

Guest lecturers will also attend the course. It will be a 5 days PhD course with lectures and workshops. There will be a mini symposium on one day where leaders in the field will have keynote lectures. On the last day, students are expected to do short presentation in groups about the state-of-the-art usage of Systems Biology.

Course Requirement

PhD students and researchers who use omics data in their research project.

Course Fee

The course free is 2000 SEK for student and academic researcher (for others, please contact the course organizer directly). In case of no-show or cancellation after 9 February 2020, the full fee will be charged to the institution. Please note that we cannot invoice individuals (only institutional invoice is accepted).