Bioinformatics

General

• Code: TΑBO-45-Δ5
• Semester: 4th
• Study Level: Undergraduate
• Course type: Special Background
• Teaching and exams language: Greek
• Teaching Methods (Hours/Week): Lectures (3)
• ECTS Units: 5
• Course homepage: https://eclass.emt.ihu.gr/courses/FD335/
• Instructors: Lampakis Dimitrios

Course Contents

• Chapter 1. The Fasta algorithm.
• Chapter 2 The Blast algorithm.
• Chapter 3. Multiple alignment of nucleic acid and protein sequences.
• Chapter 4. Protein motifs.
• Chapter 5. Phylogenetic trees.
• Chapter 6. Prediction of protein secondary structures.
• Chapter 7. Promoter finding.
• Chapter 8. The Needleman algorithm.
• Chapter 9. Position-specific scoring matrices.
• Chapter 10. PAM and Blosum Tables.
• Chapter 11. Predicting protein 3D structures.
• Chapter 12. Predicting RNA secondary structures.
• Chapter 13. Finding enzyme active site animoacids and hydrophobic regions.

Educational Goals

The course aims to teach students the applications and methods of extracting information related to genetic material and proteins from large databases.

General Skills

• Working independently.
• Production of new research ideas.
• Search for, analysis and synthesis of data and information, with the use of the necessary technology.

Teaching Methods

• In the classroom, face to face.

Use of ICT means

• Basic software (windows, word, power point, the web, etc.).
• Support of learning process through the electronic platform / e-class.

Teaching Organization

Students Evaluation

The evaluation of the students is conducted in the Greek language.

The assessment methods are:

• short answer questions,
• open ended questions,
• problem solving,
• written work.

The course aims to master the basic knowledge of Bioinformatics, as well as software skills

Evaluation criteria:

• Study and understanding of special topics of Bioinformatics, which are relevant to the scientific field of Agricultural Biotechnology and Oenology.
• Manipulation of data on computer and understanding of the algorithms that underlie the analysis tools.

The evaluation criteria are explicitly stated and can be accessed by the students through the e-class platform, in the “course description”.

Recommended Bibliography

1. [86054818]: Bioinformatics & Functional Genomics, Jonathan Pevsner.
2. [94702956]: Introduction to Bioinformatics, ARTHUR M. LESK.
3. [59380291]: Introduction to Genomics, Arthur M. Lesk.
4. [13256855]: Bioinformatics-Computer Applications in Health Care and Biomedicine, Cimino J., Shortlife.
5. Book: Bioinformatics. ISBN: 978-1-119-33558-0 Andreas D. Baxevanis (Editor), Gary D. Bader (Editor), David S. Wishart (Editor), 2020. Willey.