COMPUTER LAB 3
Academic Year 2025/2026 - Teacher: ROBERTO PATANE'Expected Learning Outcomes
Acquire the fundamental concepts of computer science and a comprehensive understanding of programming systems and the reasoning process. Understand the concept of an algorithm and the ability to identify the fundamental principles associated with it. Learn about computational methods applied to the modeling of biological systems.
Course Structure
The course consists of 30 hours of face-to-face instruction, delivered through laboratory-style lessons, adopting a theoretical and practical approach. Each explanatory session will be followed by a practical exercise phase, during which solutions will be analyzed, corrected, and explained. If the course is conducted in a hybrid or remote format, lessons will be delivered via the Microsoft Teams platform, with exercises carried out online.
Required Prerequisites
It is recommended to have attended the course on Principles of Computer Science and Applied Mathematics for Biotechnology, as well as the modules on Principles of Bioinformatics and Principles of Computer Science.
Attendance of Lessons
Mandatory
Detailed Course Content
- Algorithms, flowcharts and programming languages
- Python language
- Elements of bioinformatics
- Biopython modules
Textbook Information
Teaching materials, notes, handouts and slides provided by the professor
Course Planning
| Subjects | Text References | |
|---|---|---|
| 1 | Introduction to the course. | |
| 2 | Algorithms, flowcharts, structured programming, variables and constants, input/output instructions, assignment, seqeunce, selection. Boolean algebra in programming. Multiple selection. Iterative loops, pre- and post-condition loops, enumerative loops. Programming languages, low-level and high-level languages, compiler and interpreter. | |
| 3 | Python language, syntax, variables and data types, operators selection constructs (if … else, elif), multiple selection (match case). Iterative loops (while, for). Functions and modules. Strings, lists, sets, tuples, dictionaries and text files. | |
| 4 | Elements of bioinformatics, sequences, central dogma of molecular biology, genetic code, comparison, similarity and distance between sequences, sequence alignments, BLAST, CLUSTALW/O, FASTA/FASTQ formats, GenBank, NCBI and primary biological databases. | |
| 5 | Biopython, Seq and MutableSeq objects, complement, transcription, translation, pairwise alignment, FASTA/FASTQ files. Entrez. |
Learning Assessment
Learning Assessment Procedures
Analysis of the exercises completed during the course, questions on the Python programming language and the Biopython modules. Practical programming exercises.
Examples of frequently asked questions and / or exercises
- .replace() method in Python
- Dictionaries in Python
- Difference between FASTA and FASTQ formats
- Seq object in Biopython
- DNA to RNA transcription exercise with Biopython
- Protein translation exercise with Biopython
- Pairwise alignment exercise with Biopython
- Exercise on accessing the NCBI databases via Entrez with Biopython