Python for Biologists
The course comprises lectures and hands-on sessions devoted to programming in Python, specifically designed for biologists who are new to programming. It focuses on Python to address applied problems in statistics and bioinformatics. We start with fundamental programming concepts, scripting, and file manipulation before moving on to the use of specialized packages for handling biological data.
All classes will be given in Ukrainian.
Programming languages and their applications. Advantages and disadvantages of Python. Setting up your first project. Fundamentals of writing programs and code formatting in Python.
Numeric Types and Boolean: Understanding integers, floats and the usage of Boolean values. Collections: Exploring sequences like Strings, Lists, Tuples, Dictionaries and Sets. Testing code.
Defining and invoking functions, parameters, and return values. Control Structures. Loops: Using “for” and “while” loops for repeated execution. Logical Expressions: Implementing “if”, “else”, and “elif” statements for decision making.
String formatting. Finding substrings. Comparing strings and checking string properties. Regular expressions.
Reading and Writing Text Files. Handling CSV Files. File Manipulation.
Descriptive statistics of data series. Testing sample for normal distribution.
(Seaborn and Matplotlib). Creating plots for biological data: scatter plots, bar plots, box plots, heatmaps, volcano plots. Adding error bars and statistical annotations. Plot customization with proper labels and legends. Export of high-resolution images.
FASTA file reading/writing. Sequence object manipulation, DNA/RNA transcription and translation. Sequence statistics calculation.
DataFrame operations for biological data - reading CSV/TSV files, filtering, sorting, merging datasets. Handling of missing values. Basic data cleaning. Expression data normalization.
