schedule.md

layout	title
default	Schedule - Omics integration and systems biology - 2024

Before the course

Prepare Pre-course materials. In order to be able to access the lab notebooks for this course you need to have access to SciLifeLab Serve. For lunching practicals please follow the instructions [here](./session_intro/Instructions for course OMICSINT_H24.pdf).

Course schedule

- lecture

- hands-on workshop

- invited seminar

- break

Day 1

09.00 - 09.15 Introduction and contextualization (Rasool)

Resources

• Slides

09.15 - 09.55 Machine Learning view of Omics integration (Nikolay)

Resources

• Slides

09.55 - 10.05 Break

10.05 - 10.55 Feature Selection and Supervised Omics integration (Nikolay)

Resources

• Slides

10.55 - 11.00 Break

11.00 - 12.00 Feature Selection and Supervised Omics integration (Nikolay)

Resources

• Launch Lab feature selection on Scilifelab Serve, use Rstudio app.
• Feature Selection lab Notebook
• Docker image: docker pull rasoolsnbis/omicsint_h24:session_ml_feature_selection_amd_v.h24.9879876


• Launch Lab supervised omics integration on Scilifelab Serve, use Rstudio app.
• Supervised Integration lab Notebook
• Docker image: docker pull rasoolsnbis/omicsint_h24:session_ml_supervised_omics_integration_amd_v.h24.38310b0

12.00 - 13.00 Lunch

13.00 - 13.10 Lab recap (Nikolay)

13.10 - 14.00 Unsupervised Omics integration (Nikolay)

Resources

• Slides

14.00 - 14.05 Break

14.05 - 15.20 Unsupervised Omics integration (Nikolay)

Resources

• Launch Lab unsupervised omics integration on Scilifelab Serve, use Rstudio app.
• Unsupervised Integration lab Notebook
• Docker image: docker pull rasoolsnbis/omicsint_h24:session_ml_unsupervised_omics_integration_amd_v.h24.6d635ce

15.20 - 15.30 Lab recap (Nikolay)

15.30 - 17.00 Assisted exercises

🌟 18:00 Course Dinner at Valvet Steakhouse 🌟

Day 2

09.00 - 09.20 Review (Nikolay)

09.20 - 09.50 Single Cell Omics integration (Nikolay)

Resources

• Slides

09.50 - 10.00 Break

10.00 - 11.00 Daniel Muthas - “Deriving actionable insight from omics data – an industry perspective”

11.00 - 11.15 Break

11.15 - 12.00 Single cell omics integration (Nikolay)

Resources

• Launch Lab single cell on Scilifelab Serve, use Rstudio app.
• Single cell omics integration lab notebook
• Docker image: docker pull rasoolsnbis/omicsint_h24:session_ml_single_cell_amd_v.h24.7054451


• Launch Lab UMAP on Scilifelab Serve, use Jupyter app.
• UMAP lab notebook
• Docker image: docker pull rasoolsnbis/omicsint_h24:session_ml_umap_data_integration_amd_v.h24.6d635ce

12.00 - 13.00 Lunch

13.00 - 13.45 Single cell omics integration (Nikolay)

Resources

• Launch Lab single cell on Scilifelab Serve, use Rstudio app.
• Single cell omics integration lab notebook
• Docker image: docker pull rasoolsnbis/omicsint_h24:session_ml_single_cell_amd_v.h24.7054451


• Launch Lab UMAP on Scilifelab Serve, use Jupyter app.
• UMAP lab notebook
• Docker image: docker pull rasoolsnbis/omicsint_h24:session_ml_umap_data_integration_amd_v.h24.6d635ce

13.45 - 13.55 Lab recap (Nikolay)

13.55 - 14.05 Break

14.05 - 14.45 Deep Learning for Omics integration (Nikolay)

Resources

• Slides

14.45 - 15.00 Break

15.00 - 16.15 Deep Learning for Omics integration (Nikolay)

Resources

• Launch Lab deep learning integration on Scilifelab Serve, use Jupyter app.
• Deep Learning for data integration lab html
• Docker image: docker pull rasoolsnbis/omicsint_h24:session_ml_deep_learning_integration_amd_v.h24.6d635ce

16.15 - 16.30 Lab recap (Nikolay)

16.30 - 17.00 Assisted exercises

Day 3

09.00 - 10.00 Introduction to biological network analysis (Sergiu)

Resources

• Introduction
• Network inference
• Community analysis

10.00 - 10.15 Break

10.15 - 11.00 Introduction to biological network analysis (Sergiu)

Resources

• Launch Lab topology on Scilifelab Serve, use Jupyter app.
• Topology lab Notebook part 1
• Topology lab Notebook part 2
• Topology lab Notebook part 3
• Docker image: docker pull rasoolsnbis/omicsint_h24:session_topology_amd_v.h24.a2b336c

11.00 - 11.30 Review (Sergiu)

12.00 - 13.00 Lunch

13.00 - 14.00 Introduction to biological network analysis (continued) (Sergiu)

Resources

• Launch Lab topology on Scilifelab Serve, use Jupyter app.
• Topology lab Notebook part 1
• Topology lab Notebook part 2
• Topology lab Notebook part 3
• Docker image: docker pull rasoolsnbis/omicsint_h24:session_topology_amd_v.h24.a2b336c

14.00 - 14.15 Break

14.15 - 16.15 Machine learning on Graphs (Sergiu)

Resources

• Graph neural networks (html)
• Graph neural networks (notebook file)
• Graph neural networks lab (html)
• Graph neural networks lab (notebook file)

16.15 - 16.30 Lab recap (Sergiu)

Resources

• Data engineering tutorial

16.30 - 17.00 Assisted exercises

Day 4

09.00 - 10.00 Genome-scale metabolic models for integration (Rasool)

Resources

• Introduction – Constraint-based modeling concepts

10.00 - 10.15 Break

10.15 - 11.30 Genome-scale metabolic models for integration (Rasool)

Resources

• Launch Lab GEMs on Scilifelab Serve, use Jupyter app.
• Docker image: docker pull rasoolsnbis/omicsint_h24:session_gems_amd_v.h24.a2b336c

11.30 - 11.45 Lab recap (Rasool)

12.00 - 13.00 Lunch

13.00 - 14.00 Johan Gustafsson - “Generation of context-specific genome-scale metabolic models using single-cell RNA-Seq data”

14.00 - 14.15 Break

14.15 - 14.45 Non-negative matrix factorization (Sergiu)

Resources

• Non-negative Matrix Factorization

14.45 - 15.15 Non-negative matrix factorization (Sergiu)

Resources

• Launch Lab NMF & SNF on Scilifelab Serve, use Jupyter app.
• NMF lab Notebook
• Docker image: docker pull rasoolsnbis/omicsint_h24:session_nmf_amd_v.h24.1b36f11

15.15 - 15.30 Break

15.30 - 16.00 Similarity network fusion (Sergiu)

Resources

• Similarity network fusion

16.00 - 16.30 Similarity network fusion (Sergiu)

Resources

• Launch Lab NMF & SNF on Scilifelab Serve, use Jupyter app.
• SNF lab Notebook
• Docker image: docker pull rasoolsnbis/omicsint_h24:session_nmf_amd_v.h24.1b36f11

16.30 - 16.45 Lab recap (Sergiu)

Day 5

09.00 - 09.45 Gene set analysis and reporter features (Rasool)

Resources

• Gene set analysis via GEMs

09.55 - 10.00 Break

10.00 - 11.00 Mats Nilsson - “Targeted in situ sequencing for characterization of the genetic, molecular and cellular diversity of healthy and disease tissues”

11.00 - 11.45 Gene set analysis and reporter features (Rasool)

Resources

• Launch Lab GEM GSA on Scilifelab Serve, use Jupyter app.
• Gene set analysis lab Notebook
• Docker image: docker pull rasoolsnbis/omicsint_h24:session_gsa_amd_v.h24.a1ae0fc

11.45 - 12.00 Lab recap (Rasool)

12.00 - 13.10 Lunch

13.00 - 14.00 Discussions and course end (Rasool)

Resources

• Closing remarks!
• Course Evaluation

Teachers:

• Nikolay Oskolkov
• Rasool Saghaleyni
• Sergiu Netotea

Teaching assistants:

• Yuan Li
• Jennifer Fransson
• Stefan Ebmeyer

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