The course will include exercises on python applications and packages dedicated to processing data often used in biology and medical applications. The preliminary plan is to cover the following subjects:

1. Using data tables, importing transforming, exporting data.

2. Use statistics (scipy, numpy). Scipy is a big library of all kinds of statistical functions and distributions (numpy)

3. Graphic tools (Matplotlib) . All kinds of scientific illustrations, like scatter, line, barchart, boxplot, heatmaps etc.

4. Basics with images, pixels analysis, image analysis (PIL Image). Useful for some cytological elements of analysis, like colocalization of red, green dots on the image, count cells from microscopic image.

5. DNA strings, motifs, codes (Biopython). Basic manipulation with different DNA files, finding motifs, generating random DNA, encoding/decoding algorithms.

6. Data clustering, multi-dimensional scaling (sklearn). How to make PCA, MDS, t-SNE and other plots of this kind using python. Brief check of clustering options. 

Applying students should be interested in programming and be ready to learn a programming language. Prior skills of programming are not required. Post-docs are also welcome to apply. Students should be willing to learn. The course will start on March 6th, and you can register online.