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Data Science for Biotechnology students

Supervised Machine Learning

1. Introduction to Machine Learning
2. Regression
3. Regularization
4. Multiple Regression Example
5. Multiple Regression Analysis of KPNA2 Gene Expression
6. Classification
7. Validation
8. Support Vector Machines
9. Example of classification
10. Multi-Layer Perceptrons (MLPs)

Statistics

11. Hypothesis Testing
12. Differential expression anlaysis of the TCGA breast cancer set
13. Multiple Hypothesis Corrections
14. \(q\) Value calculations in breast cancer set

Unsupervised Machine Learning

15. Unsupervised Machine Learning
16. Cluster analysis of TCGA breast cancer sets
17. Principal Component Analysis (PCA)
18. PCA analysis of two lung cancer sets
19. Autoencoders
20. VAE analysis of two lung cancer sets

Network Analysis

21. Pathway Analysis
22. Example of ORA and GSEA

Appendix

23. Appendix: Some Maths

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By Lukas Käll

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