This version of the course guide is provisional until the period for editing the new course guides ends.

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Medical Genomics and Bioinformatics

Code: 44344 ECTS Credits: 6
2025/2026
Degree Type Year
Advanced Genetics OT 0

Contact

Name:
Jordi Surralles Calonge
Email:
jordi.surralles@uab.cat

Teachers

Massimo Bogliolo
Lidia Gonzalez Quereda
Benjamin Rodriguez Santiago
Ivon Cusco Marti
Susana Boronat Guerrero
(External) Clara Serra

Teaching groups languages

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


Prerequisites

A degree in the field of biosciences


Objectives and Contextualisation

Introduction to the applications of genomic medicine to the diagnosis, understanding and treatment of genetic diseases.

Introduction to the bioinformatic analysis of genetic variants, data bases, filtering of variants

Genetic councelling

Genetically based advanced therapies for the treatment of genetic disorders 

Medical genetics and dysmorphology


Competences

  • Demonstrate a mastery of genetic analysis as a transversal tool applicable to any field of genetics.
  • Demonstrate responsibility in management of information and knowledge.
  • Design and apply scientific methodology in resolving problems.
  • Identify and propose scientific solution for problems related to genetic research at both molecular and organism levels and demonstrate an understanding of the complexity of living beings.
  • Possess and understand knowledge that provides a basis or opportunity for originality in the development and/or application of ideas, often in a research context.
  • Student should possess an ability to learn that enables them to continue studying in a manner which is largely self-supervised or independent.
  • Students should know how to apply the knowledge they acquire and be capable of solving problems in new or little-known areas within broader contexts (or multidisciplinary contexts) related to their area of study.
  • Use and manage bibliographical information and other resources related to genetics and related fields.
  • Use scientific terminology to argue the results of the research and show how to communicate in spoken and written English in an international setting.

Learning Outcomes

  1. Apply bibliographical information about rules and legislation in risk assessment.
  2. Demonstrate responsibility in the management of information and knowledge and in the direction of groups and/or projects in multidisciplinary teams.
  3. Display knowledge of genetic analysis applied to the genomics of clinical cases.
  4. Identify and compare the different methodologies of molecular analysis of genetic variability and medical genomics.
  5. Identify suitable bioinformatic methodologies for genomic analysis applied to personalised medicine.
  6. Preparation and presentation of seminars.
  7. Solve practical problems in medical genomics by applying knowledge of bioinformatic analysis of the genoma.
  8. Student should possess an ability to learn that enables them to continue studying in a manner which is largely self-supervised or independent.
  9. Use scientific terminology to argue the results of the research and show how to communicate in spoken and written English in an international setting.
  10. Write a report that considers the use of the methodology used in the module to resolve a specific problem.
  11. Write critical summaries about the taught seminars.

Content

Introduction to the applications of genomic medicine to the diagnosis, understanding and treatment of genetic diseases. Introduction to the bioinformatic analysis of genetic variants, data bases, filtering of variants . Introcution to genetic councelling. Genetically based advanced therapies for the treatment of genetic  diseases. Medical genetics and dysmorphology


Activities and Methodology

Title Hours ECTS Learning Outcomes
Type: Directed      
Bioinformatics in informatics classroom 25 1 1, 7, 2, 3, 11, 10, 4, 5, 6, 8, 9
Theoretica teaching 25 1 1, 7, 2, 3, 11, 10, 4, 5, 6, 8, 9
Type: Supervised      
Bioinformatic analysis 50 2 7, 5
Type: Autonomous      
Written report 40 1.6 7, 3, 11, 4

 
 
theoretical classes
										
											
										
											
										
											Teaching based on problem solving
										
											
										
											
										
											Classes in the bioinformatics classroom

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

Continous Assessment Activities

Title Weighting Hours ECTS Learning Outcomes
Exam of the Bioinformatics Part 40% 3 0.12 7, 3, 4, 5
exam theory 40% 4 0.16 1, 7, 2, 3, 11, 10, 4, 5, 6, 8, 9
Written report 20% 3 0.12 3, 11, 10, 5, 9

Exam of the theorethical teaching, problem solving at the bioinformatica classroom and written report

For the written work part of this subject, the use of Artificial Intelligence (AI) technologies is permitted exclusively in support tasks, such as bibliographic or information searches, text correction or translations. The student must clearly identify which parts have been generated with this technology, specify the tools used and include a critical reflection on how these have influenced the process and the final result of the activity. The lack of transparency in the use of AI in this assessable activity will be considered a lack of academic honesty and may lead to a partial or total penalty in the grade of the activity, or greater sanctions in serious cases.


Bibliography

to be showns during the teaching sessions


Software

Will be given in the PC classroom


Groups and Languages

Please note that this information is provisional until 30 November 2025. You can check it through this link. To consult the language you will need to enter the CODE of the subject.

Name Group Language Semester Turn
(PLABm) Practical laboratories (master) 1 English first semester afternoon
(TEm) Theory (master) 1 English first semester morning-mixed