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Bioinformatics

Code: 101909
Credits: 6
2026/2027
Degree programme Type Course
Biomedical Sciences OB 3

Contact lecturer

Name :
Angel Gonzalez Wong
Email :
angel.gonzalez@uab.cat

Teaching staff

Leonardo Pardo Carrasco
Carolina Soriano Tarraga
Angel Gonzalez Wong
Berta Carrasco Martinez
Marc Ciruela Jardí

Group languages

You can consult this information at the end of the document.

Prerequisites

There are no prerequisites.

Objectives

This course introduces the student to the field of Bioinformatics, an area of research that uses computer databases to store, retrieve and assist in the understanding of biological information. The large genome sequencing projects as well as significant progresses in the determination of three-dimensional protein structures have led to an explosion of genetic sequences and structural data available for automated analysis. The student will learn how genomic analysis and protein structures can lead to a better understanding of the biological processes. Students will be introduced to basic tools of Boinformatics and Computational Biology. The practical sessions will complement this knowledge, allowing students to become familiar with the details and the use of the most used tools and online resources of the field.

Objectives:

  • General introduction to the field of Bioinformatics.
  • Introduction to the types of data analyzed in Bioinformatics and their databases.
  • Introduction to the use of tools and algorithms commonly used in the field.
  • Develop skills in the research, retrieval, and analysis of protein sequences and structures.
  • Understand the most relevant aspects of Chemoinformatics, with special emphasis on drug discovery.
  • Understand the concepts of Medical Informatics and the integration of genetic and clinical databases.

Learning outcomes

  1. Work as part of a group with members of other professions, understanding their viewpoint and establishing a constructive collaboration.
  2. Use procedures for analysing the structure, properties and function of cellular molecules and organelles.
  3. Identify and apply suitable functional study methodologies for the development of research projects.

Contents

1. Introduction. Databases in Bioinformatics

  • NCBI - Entrez. EMBL - EBI
  • Bibliographic data bases. PubMed
  • Protein sequences. UniProt
  • Nucleotide sequences. GenBank

2. Genomics

  • Genome annotations
  • Search for genes
  • Genome project
  • Genomic browsers
  • Encode project
  • HapMap project
  • Catalog of human genes and genetic disorders: OMIM
  • Databases of SNPs
  • Genome association studies (GWAS)

3. Sequence Comparisson and Phylogenetic Analysis

  • Sequence comparison methods
  • Substitution matrices
  • Dynamic programming
  • Local and global alignment
  • Search by similarity (BLAST)
  • Multiple sequence alignment
  • Representation of LOGOS of Sequences
  • Progressive alignment. ClustalW
  • Phylogenetic analysis

4. Structural Bioinformatics

  • Protein secondary structure
  • Protein tertiary structure. Molecular interactions
  • Experimental methods for the determination of the tertiary structure of proteins: X-ray and NMR
  • The PDB format
  • Protein quaternary structure
  • Structural alignment of proteins, molecular cavities, molecular electrostatic potential
  • Cell membrane, membrane proteins, prediction of secondary structure of transmembrane segments
  • Structural classification of proteins: motifs, domains
  • Homology modeling and AlphaFold

5. Modes of Drug Action and Chemoinformatics

  • G protein-coupled receptors
  • Kinases
  • Growth factors
  • Representation of chemical entities. SMILES and Tanimoto coefficient
  • Structure-Activity Relationships. Pharmacophore models
  • Protein-ligand molecular docking
  • ADME / Tox

Learning activities and methodology

Title Hours ECTS Learning outcomes
Consolidation practices and tutorials 10 0.4
Research project 10 0.4
Research project presentation 5.5 0.22
Study 71 2.84
Practical classes 24 0.96
Theoretical classes 24 0.96

The course has a strongly practical orientation, centered on the use of bioinformatics software.

Lectures

The theoretical classes will be delivered through face-to-face lectures. However, student interaction and participation will be encouraged and promoted as much as possible. Classes will be supported by audiovisual materials.

All teaching materials used by the instructor will be made available through the course's Virtual Campus. Students are encouraged to bring these materials to class to facilitate note-taking and learning.

Students will also be encouraged to deepen their understanding of the topics covered in class through the use of the recommended bibliography and simulation software.

Practical Sessions

Given the nature and orientation of the course, practical sessions will play a key role in both course development and student learning, and they are essential for achieving the learning objectives.

In addition to the wide range of bioinformatics web resources available, the selected software tools will be installed in the computer laboratory.

During these sessions, students will be required to solve previously selected practical case studies. Training will include both data input and manipulation, as well as the use of the main functionalities provided by the selected software packages.

Practical activities will be carried out individually or in pairs.

Research Project

The aim of the research project is for students to develop skills in addressing a biological hypothesis through the application of the bioinformatics tools and resources presented throughout the course.

In this course, the use of Artificial Intelligence (AI) technologies is permitted as an integral part of coursework development, provided that the final outcome reflects a significant contribution from the student in terms of analysis and personal reflection. Students must clearly identify which parts have been generated using AI technologies, specify the tools employed, and include a critical reflection on how these technologies have influenced both the process and the final outcome of the activity. Failure to disclose the use of AI will be considered a breach of academic integrity and may result in a penalty in the activity grade or, in more serious cases, additional disciplinary sanctions.

Annotation: within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.

Assessment

Continuous assessment activities

Title Weight Hours ECTS Learning outcomes
Practical and theoretical exams 65% 0.5 0.02 1, 2, 3
Drafting and presentation of a project 20% 1 0.04 1, 2, 3
Attendance to practices and presentation of the corresponding reports 15% 4 0.16 2, 3

The competencies of the course will be assessed according to the following criteria:

Theoretical-Practical

  • Two midterm examinations covering theoretical-practical knowledge and conceptual questions [exams T1 (32.5%) i T2 (32.5%)]

Practical

  • Attendance at practical sessions and submission of the corresponding reports [AI] (15%)
  • Preparation and presentation of a project [PJ] (20%)
Theoretical-Practical Examinations T 65%
Midterm Exam 1 T1 32.5%
Midterm Exam 2 T2 32.5%
Attendance at Practical Sessions and Submission of Reports AI 15%
Project Preparation and Presentation PJ 20%
  • A minimum overall grade of 5.0 is required to pass the course.
  • Participation in the practical component is mandatory in order to be assessed, although no minimum grade is required for this component.
  • A student will be considered “Not Assessable” (NA) if the grades obtained in the completed assessment activities do not allow the student to achieve an overall grade of 5.0, even if the maximum possible marks were obtained in all remaining assessment activities.
  • A final examination will be available either: As a resit examination for students who do not pass the course, or for students wishing to improve their final grade (with the possibility that the new grade may be lower than the original one).
  • This examination will account for 65% of the final grade, while the practical component will account for the remaining 35%.
  • Students repeating the course may choose whether or not to attend the practical sessions. If they decide not to do so, the assessment will be distributed as follows: T1 40%, T2 40% i PJ 20%.
  • Any irregularity in an assessment activity (academic fraud, plagiarism, or improper use of AI, unless such use is expressly authorized in the course guide) that may lead to a significant alteration of the assessment result will result in a grade of 0 for that activity. If the course guide establishes a minimum grade requirement for that assessment activity in order to pass the course, or if multiple irregularities occur in assessment activities within the same course, the final grade for the course will be 0. In addition, disciplinary proceedings may be initiated against the student.

This course does not offer a single-assessment option.

Bibliography

Specific Bibliography.

  • Attwood, T.K., Parry-Smith, D.J., Introducción a la Bioinformática, Pearson Education, 2002.

Recommended Bibliography

  • Baldi, P., Brunak, S., Bioinformatics, MITPress, 1998.
  • Baxebanis, A.D., Oullette, F., Bioinformatics, John Wiley & Sons, 1998.
  • Lesk, A. Introduction to Bioinformatics. Oxford University Press, 2005.
  • Waterman, M.S., Introduction to computational biology maps, sequences and genomes,Chapman & Hall/CRC, 2000.

Internet-Based Resources

http://www.nih.gov/

http://www.ncbi.nlm.nih.gov/

http://www.pdb.org/

http://www.ebi.ac.uk

http://www.uniprot.org/

http://www.rcsb.org/

http://www.genomesonline.org/index

http://www.ncbi.nlm.nih.gov/projects/mapview/

http://genome.ucsc.edu/ENCODE/

http://www.genome.gov/Encode/

http://www.nature.com/encode/#/threads

http://hapmap.ncbi.nlm.nih.gov

http://www.ncbi.nlm.nih.gov/snp

http://www.ncbi.nlm.nih.gov/SNP/

http://omim.org

http://www.1000genomes.org/home

http://www.genome.gov/

http://www.genome.gov/GWAStudies/

http://www.embl.de/

http://genes.mit.edu/GENSCAN.html

http://expasy.org/prosite/

http://prodom.prabi.fr/

http://pfam.sanger.ac.uk/

http://www.cbs.dtu.dk/services/TMHMM/

http://scop.mrc-lmb.cam.ac.uk/scop/

http://www.cathdb.info/

http://ekhidna.biocenter.helsinki.fi/dali_server/

http://www.vcclab.org/lab/edragon/

http://matisse.ucsd.edu/itp-bioinfo/links.html

http://sites.univ-provence.fr/~wabim/english/logligne.html

Software

https://www.jalview.org/

https://pymol.com/

https://www.inteligand.com/ligandscout/

https://openmolecules.org/datawarrior/

Course groups and languages

The information provided is provisional until November 30. After this date, you will be able to consult the language of each group through this link. To access the information, you will need to enter the course CODE

Type of teaching Group Language Semester Shift
(TE) Theory 53 Catalan second semester morning-mixed
(PLAB) Practical laboratories 531 Catalan second semester afternoon
(SEM) Seminars 531 Catalan second semester morning-mixed
(PLAB) Practical laboratories 532 Catalan second semester afternoon
(SEM) Seminars 532 Catalan second semester morning-mixed
(PLAB) Practical laboratories 533 Catalan second semester afternoon