Course schedule
This page is under update.
- lecture;
- hands-on workshop;
- invited seminar;
- break
Before the course
Prepare Pre-course materials and pre-processing introduction (notebook, html).
Day 1
09.00 - 09.20 Introduction and contextualization (Rui, slides)
09.20 - 09.55 Machine Learning view of Omics integration (Nikolay, slides)
09.55 - 10.05 Break
10.05 - 10.55 Feature Selection and Supervised Omics integration (Nikolay, slides)
10.55 - 11.00 Break
11.00 - 12.00 Feature Selection and Supervised Omics integration (Nikolay,feature selection notebook, supervised integration notebook)
12.00 - 13.00 Lunch
13.00 - 13.10 Lab recap (Nikolay)
13.10 - 14.00 Unsupervised Omics integration (Nikolay, slides)
14.00 - 14.05 Break
14.05 - 15.20 Unsupervised Omics integration (Nikolay, notebook)
15.20 - 15.30 Lab recap (Nikolay)
15.30 - 17.00 Assisted exercises
Day 2
09.00 - 09.20 Review (Nikolay)
09.20 - 10.00 Dimensionality reduction and clustering (Nikolay, slides)
10.00 - 10.10 Break
10.10 - 11.10 Dimensionaliry reduction and clustering (Nikolay, notebook)
11.10 - 11.20 Break
11.20 - 12.00 Deep Learning for Omics integration (Nikolay, slides)
12.00 - 13.00 Lunch
13.00 - 13.55 Deep Learning for Omics integration (Nikolay, DL notebook, DL in single cell)
13.55 - 14.05 Break
14.05 - 15.00 Single cell and UMAP for integration (Nikolay, slides)
15.00 - 15.30 Single cell and UMAP for integration (Nikolay, single cell notebook, UMAP notebook)
15.30 - 17.00 Assisted exercises
Day 3
09.00 - 09.30 Introduction to biological network analysis (Rui, slides)
09.30 - 10.00 Network inference (Rui)
10.00 - 10.05 Break
10.05 - 11.00 Network inference (Rui, notebook)
11.00 - 11.10 Review (Rui)
11.10 - 11.20 Break
11.20 - 11.30 Community analysis (Rui, slides)
11.30 - 12.15 Community analysis (Rui, notebook)
12.15 - 13.15 Lunch
13.15 - 14.15 Evangelia Petsalaki - “Data-driven approaches towards studying context-specific cell signalling”
14.15 - 14.20 Break
14.20 - 14.45 Network meta-analysis (Ashfaq, lecture, pdf)
14.45 - 14.50 Break
14.50 - 15.45 Network meta-analysis (Ashfaq, notebook, pdf)
15.45 - 17.00 Assisted exercises
Day 4
09.00 - 09.40 Similarity network fusion (Sergiu, slides)
09.40 - 09.45 Break
09.45 - 10.40 Similarity network fusion (Sergiu, notebook)
10.40 - 10.45 Break
10.45 - 11.20 Matrix factorization (Sergiu, slides)
11.20 - 11.25 Break
11.25 - 12.00 Matrix factorization (Sergiu, notebook)
12.00 - 13.00 Lunch
13.00 - 13.10 Review (Sergiu)
13.10 - 13.50 Genome-scale metabolic models for integration (Rui, slides)
13.50 - 14.00 Break
14.00 - 14.50 Genome-scale metabolic models for integration (Rui, notebook)
14.50 - 15.00 Review (Rui)
15.00 - 16.00 Jonathan Robinson - “The evolution of human Genome Scale Metabolic models”
16.00 - 17.00 Assisted exercises
Day 5
09.00 - 09.55 Gene set analysis and reporter features (Ashfaq, lecture)
09.55 - 10.00 Break
10.00 - 10.45 Gene set analysis and reporter features (Ashfaq, GSA notebook, RCytoscape notebook, Circos notebook)
10.45 - 10.55 Review (Ashfaq)
10.55 - 11.00 Break
11.00 - 12.00 Francesco Gatto - “Systems biology approaches for translational cancer research”
12.00 - 13.10 Lunch
13.10 - 14.10 Mihail Anton - “The open source ecosystem for genome-scale metabolic models”
14.10 - 14.20 Break
14.20 - 15.20 Discussions and course end
Teachers:
Teaching assistants: