Python programming in Life Science, Msc

• Independently gain deeper insight into using python language constructs and data types in higher level programming based on existing python knowledge.
• Adhere to basic principles in good programming practice, like evaluating the appropriateness of variable/object names and avoiding obfuscating code.
• Develop pseudocode and commenting skills for enhancing code readability and maintainability through effective commenting.
• Understand and utilize the file path for interoperable (mac/win/unix) file reading thereby expanding the file reading concept.
• Apply exception handling to manage errors and alternative execution.
• Perform string manipulation to process biological data formats such as BLAST output and FASTA files.
• Parse biological data files like SwissProt with stateful parsing techniques to extract data.
• Apply sorting, searching, and deduplication algorithms to biological datasets using list manipulation techniques.
• Utilize pattern matching techniques – hereunder regular expressions – to identify and extract relevant data from Genbank files or other biological data files.
• Utilize set and dict techniques for efficient data handling and analysis in biological contexts.

The course has a strong focus on acquiring programmatic thinking through lectures and hands-on exercises in a life science context. Students will engage in in-depth programming by creating smaller but complete programs in the exercises, utilizing the breadth of Python data types and language constructs. The emphasis will be on readability, maintainability, and good programming practices, using pure Python to highlight the programmatic aspect. Through the use of simple algorithms, students will parse and manipulate various biological data file types. An important part of the course involves peer-evaluation of exercises, allowing students to gain exposure to diverse ideas and solutions from their peers.

• 36 – 49 (Mon 13-17)

02002, Basic programming experience is required, preferably in Python. This includes knowledge of variables, assignments, operators, conditional and looping language constructs, and files.

Lectures med weekly mandatory exercises.