Molecular bioinformatics: from molecules to clinical practice

Code:

OPT159

Acronym:

BIOMOL

Keywords
Classification	Keyword
OFICIAL	Medicine

Instance: 2020/2021 - 2S (of 08-02-2021 to 31-07-2021)

Active?	Yes
Responsible unit:	Departamento de Biomedicina
Course/CS Responsible:	Integrated Master in Medicine

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
MIMED	20	Mestrado Integrado em Medicina- Plano oficial 2013 (Reforma Curricular)	2	-	3	28	81
			3

Teaching language

Suitable for English-speaking students

Objectives

This curricular unit has the following learning objectives:

- Understanding the purpose of molecular biology techniques used in the molecular diagnosis;

- Acquisition of theoretical concepts about several bioinformatic tools commonly used and how to apply them in the interpretation of data from molecular diagnostics;

- Execution hands-on, using a computer, of multiple software tools freely available for the molecular analysis of sequences and query of clinical information and experimental data in databases;

- Development of critical thinking about the data of molecular diagnostics, genetic counselling and therapeutic choices.

Learning outcomes and competences

By the end of the course the participants must be able to:

- Master essential knowledge of bioinformatics analysis in the scope of molecular genetics;

- Autonomously use the bioinformatics tools presented, understanding its capabilities and limitations, and interpret the results in a self-confident manner;

- Know the multistep process of molecular diagnosis: request, techniques of molecular analysis used in laboratory, interpretation and analysis of the results, prediction of the degree of pathogenicity, generation of the report, prognostic, genetic advice and selection of the appropriate therapy.

 

Relevance of this optional UC for MIMED:

Bioinformatics is a science that comprises concepts of biology, mathematics, statistics and computer science, and aims to solve biological questions through the analysis of molecular data. This area of knowledge is constantly being developed and updated to cope with the exponential growth of experimental data, especially after the advent of Next Generation Sequencing (NGS). Bioinformatic tools are essential because they allow storage, through repositories or databases, data analysis and interpretation. The technological innovation of molecular biology methods and the development of new bioinformatic tools have had a very positive impact on clinical practice, facilitating the diagnosis, prognosis, genetic advice and choice of the most appropriate therapies to each clinical case. Thus, this optional UC is relevant for future physicians interested in expanding their knowledge related to bioinformatics, clinical genetics and/or investigation of pathologies originating from variations of the DNA sequence.

Working method

À distância

Pre-requirements (prior knowledge) and co-requirements (common knowledge)

Knowing how to work with a computer in the user's perspective.

Program

This curricular unit is organized in theoretical-practical (TP) sessions of 2h each in which the following syllabus are taught:

- Molecular biology techniques: Sanger versus NGS sequencing. Nomenclature and report production.

- Sequences Databases. Introduction, examples, comparison, and data retrieval. Practical exercises I.

- Sequences comparison. Sequences alignment, search for similarity, homology, motifs and protein domains. Practical exercises II.

- Sequences analysis. Infer biological functions from nucleotide and protein sequences. Primer design for gene expression analysis. Design of siRNAs. Enzymatic restriction maps. Practical exercises III.

- Gene ontology. Prediction of enriched biological processes from high throughput screenings. Databases of gene expression data. Sequence variation and mutations associated to diseases. Practical exercises IV.

- Integration of biological data. Comparison of gene lists and query of multiple databases at once for nucleic acid and protein sequence analysis. Practical exercises V.

- Sequence variations: human population databases. Practical exercises VI.

- Sequence variations: databases for functional analyses of genetic alterations. Practical exercises VII.

- Nomenclature and molecular diagnostic report. Practical exercises VIII.

- Interpretation of sequence variations and genetic counselling.

- Therapeutic approaches based on molecular diagnostics results.

Mandatory literature

Matthijs, G., Souche, E., Alders, M., Corveleyn, A., Eck, S., Feenstra, I., Race, V., Sistermans, E., Sturm, M., Weiss, M., Yntema, H., Bakker, E., Scheffer, H., & Bauer, P; Guidelines for diagnostic next-generation sequencing, Eur J Hum Genet, 2016. ISBN: doi:10.1038/ejhg.2016.63
Cordido, A., Besada-Cerecedo, L., & Garcia-Gonzalez, M. A.; The Genetic and Cellular Basis of Autosomal Dominant Polycystic Kidney Disease-A Primer for Clinicians, Front Pediatr, 2017. ISBN: doi:10.3389/fped.2017.00279
Carlon, M. S., Vidovic, D., & Birket, S; Roadmap for an early gene therapy for cystic fibrosis airway disease, Prenat Diagn, 2017. ISBN: doi:10.1002/pd.5164
Jin Xiong; Essential Bioinformatics, Cambridge University Press, 2006. ISBN: 113945062X
Cook, C. E., Bergman, M. T., Cochrane, G., Apweiler, R., & Birney, E; The European Bioinformatics Institute in 2017: data coordination and integration, Nucleic Acids Res, 2018. ISBN: doi:10.1093/nar/gkx1154
Coordinators, N. R; Database resources of the National Center for Biotechnology Information, Nucleic Acids Res, 2018. ISBN: doi:10.1093/nar/gkx1095

Complementary Bibliography

Mashima, J., Kodama, Y., Fujisawa, T., Katayama, T., Okuda, Y., Kaminuma, E., Takagi, T; DNA Data Bank of Japan, Nucleic Acids Res, 2017. ISBN: doi:10.1093/nar/gkw1001
Ion Tutorials #1; https://www.youtube.com/watch?v=R8rEEUkfC9I
Ion Tutorials #2; https://www.youtube.com/watch?v=WYBzbxIfuKs
Ion Tutorials #3; https://www.youtube.com/watch?v=okAWh_mLsno
Ion Tutorials #4; https://www.youtube.com/watch?v=ZL7DXFPz8rU

Teaching methods and learning activities

The teaching, using TP sessions, will combine (i) the exposition, for each topic, of the theoretical concepts and bioinformatics tools available, (ii) the practical demonstration of these tools and (iii) their application by the students, solving the proposed exercises (usually the time provided during the class is suficient). The learning will be done by direct contact with the bioinformatics programs, of open access, and through the resolution of the proposed exercises. In the sessions, each students will have one computer with internet access.

keywords

Natural sciences > Biological sciences > Biology > Molecular biology
Natural sciences > Biological sciences > Biology > Genetics
Health sciences > Medical sciences > Medicine > Diagnostics

Evaluation Type

Distributed evaluation without final exam

Assessment Components

Designation	Weight (%)
Participação presencial	10,00
Trabalho escrito	90,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Estudo autónomo	38,00
Frequência das aulas	28,00
Trabalho escrito	15,00
Total:	81,00

Eligibility for exams

Attendance: at least 75% of contact hours.

Calculation formula of final grade

The evaluation will take into account the following elements: (i) individual written work based on solving the proposed problems (PP) in practically all TP sessions, and (ii) continuous assessment (AC) considering oral participation in a relevante/critical point of view. The assessment will be expressed on a scale of 0 to 20 and calculated according to the following formula:

 

Final classification = (0.90xPP) + (0.10xAC)

Classification improvement

It is possible to improve the final grade by frequency of the curricular unit in the next year.