2023/24
27123 - Bioinformatics
Compulsory
1. General information
The objective of this subject is to introduce students to the use of basic bioinformatics tools and computational biology used in various fields of biotechnology. The course is taught in the second quarter of the third year , when students already have methodological and theoretical knowledge that makes them aware of the enormous amount of information to process when working with biological systems . The subject allows them to know and use the main databases of biomolecules and genomes, and to deepen in the search for information and its analysis. To take this subject, it is recommended to have taken Biochemistry, Molecular Biology and Structure of Macromolecules, as well as to have taken or to be taking Genetic Engineering at the same time.
These approaches are aligned with the following SDGs of the United Nations 2030 Agenda ( https://www.un.org/sustainabledevelopment/es/), such that the acquisition of the subject's learning results provides training and competence to contribute to some extent to their achievement; Goal 3: Health and wellness; Goal 5: Gender equality; Goal 7: Affordable and non-polluting energy; Goal 9: Industry, Innovation and infrastructure; Goal 14: Underwater life; Goal 15: Life of terrestrial ecosystems.
3. Syllabus
MASTER CLASSES
1. Introduction.
2. Gene and protein sequence databases. Data entry and retrieval.
3. Sequence alignment.
4.Genome analysis and comparison. Metagenomes. Transcriptomics databases.
5. Metabolic pathway databases
6. Phylogenetic trees. CP1. Construction of distance matrices and cladograms.
7. Protein and nucleic acid structure databases. Data entry and applications of visualization.
8. Molecular simulation methods.
9. Molecular Dynamics and Monte Carlo.
10. Protein and nucleic acid structure prediction methods.
11. Molecular docking prediction methods (docking).
12. Simulation of biological reactions. Hybrid Quantum Mechanics/Molecular Mechanics (QM/MM) methods.
13. Chemoinformatic: databases of organic molecules.
14. Tools for drug design. QSAR, ADMET.
15. Databases for proteomics and interactomics.
16. Databases and thematic servers (of diseases, etc.).
CASE STUDY CLASSES
Case 1: Sequence recovery, sequence alignment and construction of a phylogenetic tree.
Case 2: In silico gene amplification and cloning.
Case 3: Structural analysis: structure-function relationship of an enzyme.
Case 4: Molecular docking for drug design.
Case 5. Preparation of an analysis script. Analysis of a molecular dynamics trajectory.
PROJECT
Development of an individual tutored project on a real case and presentation of the results, discussion and conclusions in a report
4. Academic activities
MASTER CLASSES
Face-to-face. 2 ECTS. They present the basic theoretical knowledge of the subject. The basic material will be provided to students through UNIZAR's MOODLE blended learning platform.
CASE STUDIES
Face-to-face and mandatory. 2 ECTS. 5 sessions of 4 hours in a computer classroom. The student will be instructed on how to design their searches and simulations and interpret the results. The student will independently design searches, data analysis and simulations and critically evaluate the results obtained.
LEARNING THROUGH THE DEVELOPMENT OF AN INDIVIDUAL PROJECT
Face-to-face and mandatory. 2 ECTS. 5 sessions of 4 hours in a computer classroom for the preparation of a supervised project . Students will develop a specific tutored project and then generate a structured report including Results, Discussion, Conclusions, and Bibliography.