Universitat Internacional de Catalunya
Biological Databases
Other languages of instruction: Catalan, Spanish
Teaching staff
Introduction
The course is aimed at knowing the different types of databases available in the area of health sciences to solve problems in the field of biomedicine. Throughout the subject, the aspects that are introduced in the subject "Introduction to bioinformatics" will be expanded and its application for access to information will be deepened.
Pre-course requirements
It is recommended to have completed and passed:
- Introduction to bioinformatics
Objectives
- To know the main biomedical databases and their web sites to access and exploit this type of data.
- To know how to search, collect, process and interpret biomedical data to solve problems in this field.
- To develop critical thinking based on scientific results.
Competences/Learning outcomes of the degree programme
- CB01 - Students must demonstrate that they have and understand knowledge in an area of study that is based on general secondary education, and it tends to be found at a level that, although it is based on advanced textbooks, also includes some aspects that involve knowledge from the cutting-edge of their field of study.
- CB03 - Students must have the ability to bring together and interpret significant data (normally within their area of study) to issue judgements that include a reflection on significant issues of a social, scientific and ethical nature.
- CB04 - That students can transmit information, ideas, problems and solutions to specialist and non-specialist audiences.
- CB05 - That students have developed the necessary learning skills to undertake subsequent studies with a high degree of autonomy.
- CE07 - To apply statistical tools to Health Science studies.
- CE19 - To be aware of the principles of biomedical science related to health and learn how to work in any field of Biomedical Sciences (biomedical companies, bioinformatics laboratories, research laboratories, clinical analysis companies, etc.).
- CG07 - To incorporate basic concepts related to the field of biomedicine both at a theoretical and an experimental level.
- CG10 - To design, write up and execute projects connected to the field of Biomedical Sciences.
- CG11 - To be aware of basic concepts from different fields connected to biomedical sciences.
- CT01 - To develop the organisational and planning skills that are suitable in each moment.
- CT02 - To develop the ability to resolve problems.
- CT03 - To develop analytical and summarising skills.
- CT04 - To interpret experimental results and identify consistent and inconsistent elements.
- CT05 - To use the internet as a means of communication and a source of information.
- CT06 - To know how to communicate, give presentations and write up scientific reports.
- CT07 - To be capable of working in a team.
- CT08 - To reason and evaluate situations and results from a critical and constructive point of view.
- CT09 - To have the ability to develop interpersonal skills.
- CT10 - To be capable of autonomous learning.
- CT11 - To apply theoretical knowledge to practice.
- CT12 - To apply scientific method.
- CT13 - To be aware of the general and specific aspects related to the field of nutrition and ageing.
- CT14 - To respect the fundamental rights of equality between men and women, and the promotion of human rights and the values that are specific to a culture of peace and democratic values.
Learning outcomes of the subject
The specific learning outcome of this mention are:
- Analyze biomedical problems and identify the aspects that require the use of databases. Obtain information of interest from the main massive databases (Big Data) in the field of Biomedical Sciences.
In addition, other learning outcomes will be that the student:
- Learn about the different types of databases available in the area of health sciences to solve the main problems in the field of biomedicine.
- Learn the basics of collecting, processing and analyzing large volumes of data from biomedical research.
- Learn about the main tools in the field of bioinformatics and the bases of programming languages that allow the extraction of information from databases.
- Knows and adequately uses the scientific, technical or specific vocabulary of the field in which the activity will be carried out.
Syllabus
1) Introduction to biological databases. Use of biomedical data in the field of life sciences. Types of data available in biomedicine. Main databases. Search for information in a database.
2) Bibliographic databases. MEDLINE bibliographic database. MeSH biomedical vocabulary. PubMed search engine. PubMed Central bibliographic repository. Mendeley bibliographic manager.
3) Nucleotide databases: genomes, genes and transcripts. INSDC: NCBI, EMBL-EBI and DDBJ. Genomes, Genes, and Transcripts at NCBI: Entrez, Nucleotide, GenBank, RefSeq; and in EMBL-EBI: ENA and Ensembl. Visualization of genomes at UCSC. Gene nomenclature in HGNC. Description of genes in Gene Cards. Coding sequence in CCDS.
4) Gene expression and regulation databases. Gene expression in GEO, Expression Atlas, Single Cell Expression Atlas and Single Cell Portal. Gene regulation in GTEx and ENCODE.
5) Protein databases. Protein sequence in UniProt, RefSeq and Ensembl. Protein domains in InterPro, PROSITE and Pfam. Protein structures in PDBe, RCSB PDB and AlphaFold. Protein interaction in IntAct, STRING and BioGRID.
6) Network databases. Gene function in Gene Ontology. Metabolic pathways in Reactome and KEGG.
7) Databases of diseases, genetic variability and drugs. Diseases in OMIM and Orphanet. Genetic variability in ClinVar, UniProt, gnomAD and dbSNP. Drugs in DrugBank, PubChem and PHARMGKB.
Teaching and learning activities
In person
Master classes: presentation for 50 minutes of a theoretical topic by the teacher.
Case methods Approach of a real or imaginary situation. The students work on the questions formulated in active interaction with the teacher and the answers are discussed. The teacher actively intervenes and, if necessary, contributes with new knowledge.
Laboratory practices: Students work individually on the problems raised by the teacher that will have to be solved using different bioinformatics tools.
Evaluation systems and criteria
In person
First call students:
- Case methods: 15%
- Internship reports: 15%
- Partial exam: 30%
- Final exam: 40%
1) In order to make an average, a minimum grade of 5 must be obtained in the final exam.
2) Attendance at case methods and practices is mandatory. The continuous nature of this assessment means that it is not possible to aprove the subject if a minimum of 75% of the hours have not been participated in.
3) The improper use of electronic devices (such as the recording and dissemination of both students and teachers during the different lessons, as well as the use of these devices for recreational and non-educational purposes) may lead to expulsion from class.
4) The expulsion of a student from the classroom may lead to the failure of the subject.
Students in second or subsequent call: the note of the methods of the case and the note of practices will be saved; and the final exam will represent 70% of the final grade. Repeating students who wish to repeat the partial in 3 or 5 calls, may do so by previously communicating it to the head teacher.
Bibliography and resources
https://www.ncbi.nlm.nih.gov/home/tutorials/
https://www.ensembl.org/info/index.html
https://www.ebi.ac.uk/training/online/
Andreas D. Baxevanis (Editor) , B. F. Francis Ouellette (Editor) (2004). Bioinformatics: A Practical Guide to the Analysis of Genes and Proteins (3 ed.). Wiley.
Model, Mitchell L. (2010). Bioinformatics programming using Python (1 ed.). O’Reilly .
Evaluation period
- E1 18/01/2024 I2 14:00h
- R1 25/01/2024 A10 18:00h
- E2 18/06/2024 I1 18:00h