Course modules: ELIXIR Omics Integration and Systems Biology

Preparation

Preparation Preparation

Overview Page

Overview Overview 1

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Pre-course Page

Pre-course Pre-course 3

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Data pre-processing Page

Data pre-processing Data pre-processing 4

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Day 1: Introduction, ML view of omics integration, introduction to Unsupervised Integration

Day 1: Introduction, ML view of omics integration, introduction to Unsupervised Integration Day 1: Introduction, ML view of omics integration, introduction to Unsupervised Integration

Introduction Page

Introduction Introduction 1

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Machine Learning view of Integration Page

Machine Learning view of Integration Machine Learning view of Integration 2

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Unsupervised Integration Page

Unsupervised Integration Unsupervised Integration 3

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Lab: Unsupervised Integration through MOFA2 Page

Lab: Unsupervised Integration through MOFA2 Lab: Unsupervised Integration through MOFA2 4

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Day 1: Unsupervised Integration through MOFA

Day 1: Unsupervised Integration through MOFA Day 1: Unsupervised Integration through MOFA

Multi-Omics Factor Analysis - MOFA Page

Multi-Omics Factor Analysis - MOFA Multi-Omics Factor Analysis - MOFA 1

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Lab: MOFA for personalized medicine Page

Lab: MOFA for personalized medicine Lab: MOFA for personalized medicine 2

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Bonus materials: mofa Page

Bonus materials: mofa Bonus materials: mofa 3

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Day 2: Supervised Integration through Mixomics

Day 2: Supervised Integration through Mixomics Day 2: Supervised Integration through Mixomics

Your instructor Page

Your instructor Your instructor 1

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Preliminary background on PCA Page

Preliminary background on PCA Preliminary background on PCA 2

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Lecture Page

Lecture Lecture 3

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Lab: Application to a microarray data set Page

Lab: Application to a microarray data set Lab: Application to a microarray data set 4

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Bonus materials: mixomics Page

Bonus materials: mixomics Bonus materials: mixomics 6

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Day 2: Deep Learning and UMAP integration

Day 2: Deep Learning and UMAP integration Day 2: Deep Learning and UMAP integration

Deep Learning for Omics integration Page

Deep Learning for Omics integration Deep Learning for Omics integration 1

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Lab: Deep learning Page

Lab: Deep learning Lab: Deep learning 2

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UMAP for data integration Page

UMAP for data integration UMAP for data integration 3

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Lab: UMAP for data integration Page

Lab: UMAP for data integration Lab: UMAP for data integration 4

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Bonus lab: dimensionality reduction Page

Bonus lab: dimensionality reduction Bonus lab: dimensionality reduction 5

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Bonus lab: integration at single-cell level Page

Bonus lab: integration at single-cell level Bonus lab: integration at single-cell level 6

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Bonus materials: deep learning Page

Bonus materials: deep learning Bonus materials: deep learning 7

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Day 3: Network Analysis

Day 3: Network Analysis Day 3: Network Analysis

Introduction to network analysis Page

Introduction to network analysis Introduction to network analysis 1

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Network inference and properties Page

Network inference and properties Network inference and properties 2

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Community analysis Page

Community analysis Community analysis 3

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Lab: Network construction and analysis of a transcriptomic and metabolomic dataset Page

Lab: Network construction and analysis of a transcriptomic and metabolomic dataset Lab: Network construction and analysis of a transcriptomic and metabolomic dataset 4

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Bonus lab: Feature selection Page

Bonus lab: Feature selection Bonus lab: Feature selection 5

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Bonus lab: data pre-processing in python Page

Bonus lab: data pre-processing in python Bonus lab: data pre-processing in python 6

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Day 4: Similarity Network Fusion and Non-negative Matrix Factorization

Day 4: Similarity Network Fusion and Non-negative Matrix Factorization Day 4: Similarity Network Fusion and Non-negative Matrix Factorization

Non-negative Matrix Factorization Page

Non-negative Matrix Factorization Non-negative Matrix Factorization 1

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Similarity Network Fusion Page

Similarity Network Fusion Similarity Network Fusion 2

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Lab: Non-negative Matrix Factorization Page

Lab: Non-negative Matrix Factorization Lab: Non-negative Matrix Factorization 3

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Lab: Similarity Network Fusion Page

Lab: Similarity Network Fusion Lab: Similarity Network Fusion 4

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Bonus material: NMF and SNF Page

Bonus material: NMF and SNF Bonus material: NMF and SNF 5

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Day 4: Genome-scale metabolic modeling

Day 4: Genome-scale metabolic modeling Day 4: Genome-scale metabolic modeling

Constraint-based modeling of metabolism Page

Constraint-based modeling of metabolism Constraint-based modeling of metabolism 1

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Lab: constraint-based modeling of metabolism (in Python with cobrapy) Page

Lab: constraint-based modeling of metabolism (in Python with cobrapy) Lab: constraint-based modeling of metabolism (in Python with cobrapy) 2

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Day 5: Gene set analysis, reporter features and network-meta analysis

Day 5: Gene set analysis, reporter features and network-meta analysis Day 5: Gene set analysis, reporter features and network-meta analysis

Network meta-analysis - Lecture Page

Network meta-analysis - Lecture Network meta-analysis - Lecture 1

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Network meta-analysis - lab Page

Network meta-analysis - lab Network meta-analysis - lab 2

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Gene set analyses - Lecture Page

Gene set analyses - Lecture Gene set analyses - Lecture 3

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Gene set analysis and reporter features - lab Page

Gene set analysis and reporter features - lab Gene set analysis and reporter features - lab 4

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Bonus material

Bonus material Bonus material

Multi Omics Data Management Page

Multi Omics Data Management Multi Omics Data Management 2

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Visualization with Cytoscape Page

Visualization with Cytoscape Visualization with Cytoscape 3

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Circos & Hive visualization Page

Circos & Hive visualization Circos & Hive visualization 4

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Additional Materials

Additional Materials Additional Materials

Additional reading Page

Additional reading Additional reading 3

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Open seminars Page

Open seminars Open seminars 4

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FAQs Page

FAQs FAQs 5

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