COURSE:
Python in biology for beginners and advanced

 
1x per year
March

 

COURSE:
Python in biology for beginners and advanced

1x per year
March

 

 

 

 

 

 

 

 

 

 

 

 

Python in biology for beginners and advanced

The course will include exercises on python applications and packages dedicated to processing data often used in biology and medical applications. The following subjects will be covered:

  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.
Eligibility

PhD students in biology, medical biology, medicine or farmacy- those who professionally connected to biology. Students should understand a concept of programming and be ready to learn the programming language. Prior skills of programming are not required. 

Assumed pre-knowledge

Beginners level, no prior knowledge of programming required, although elementary understanding of the script writing will be an advantage.

Equipment / Litrature

Students should have personal laptop with administrative rights (able to install software and packages) with 8 GM RAM, preferably Mac or Linux. Windows can be used, but with limitations. R (with R-studio) and Python3 (with Pycharm) can be preinstalled, or will be installed during the course.?

Books are optional. Students will be referred to online documentation of each package

Schedule

This course consist of 6 meetings: 12 hours lectures and 6 hours practicals.

Exam / Assesment

Expect weekly homework on discussed subjects. This will also form the basis to pass the course.
100% participation and final assignment required. 

Without exam:
2 ECTS
 
Course coordinator:
Dr. Leonid Bystrykh
 
Language:
ENGLISH
 
 
Target groups
 
 
 
PhD Students
  
 
 
 
 
Point of contact
 
 
 
Maaike Bansema
m.h.bansema@umcg.nl 
 

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