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Introduction to Bioinformatics for Medical doctors and other Healthcare professionals

Enrollment is Closed

About This Course

The BioS course integrates the latest advancements in the field of Computational Biology/Bioinformatics, that can be immediately applied in clinical environment.

The main aim of the course is to provide learners with skills which will enable understanding and utilization of large biomedical data sets, especially genomic sequence data, to enhance patient care through improved diagnostic sensitivity and more precise therapeutic targeting.


Specific admission requirements: A completed degree in health care professional training programme at the minimum of EQF level 6, such as medical doctor degree or B.Sc. in Health and Safety.

Occupational competences of trainees with examples: Medical doctor; Veterinary doctor; Clinical geneticist.

What you will learn

  1. Better understanding of and more confidence in data from modern-day high-throughput sequencing;
  2. Making more use of such data in clinical decision-making;
  3. Quicker and more relevant diagnoses of diseases with an assumed genetic component.

Mode of study

Recommended: part-time, asynchronous e-learning sessions;

ECVET credits

The BioS curriculum is modular, based on the learning outcomes approach, and is in line with the European transparency instruments: EQF/ECVET/EQAVET.

  • Module 1: Introduction to Bioinformatics, 4 credits
  • Module 2: Computational Statistics for clinical doctors, 4 credits
  • Module 3: Commercial personalised genomics services in patient care, 4 credits
  • Module 4: Quality improvement in Healthcare, 2 credits

EQF level

The BioS course is leading to EQF level 5, considering the complexity, range and level of learning expected to be achieved by the learners:

EQF level Knowledge Skills Competences
Level 5, Relevant learning outcomes Comprehensive, specialised, factual and theoretical knowledge within a field of work or study and an awareness of the boundaries of that knowledge. A comprehensive range of cognitive and practical skills required to develop creative solutions to abstract problems. Exercise management and supervision in contexts of work or study activities where there is unpredictable change; review and develop performance of self and others.

View Course syllabus

Module 1: Introduction to Bioinformatics

This module provides basic knowledge of how molecular data connects to modern biomedicine in order to give an understanding of background of genomic/personalized medicine. The course introduces the student to genomic data, DNA and protein sequence data and protein structures, major biological databases and teaches basic methods for their analyses.

Module 2: Computational Statistics for clinical doctors

This module will provide a practical introduction to analysis of biological and biomedical Big data, in order to develop a critical understanding of the reliability of analysis results. Clinical doctors will learn to appreciate how the R statistical environment can be applied to biological data analysis in a cost-efficient manner.

Module 3: Commercial personalised genomics services in patient care

The purpose of this module is to provide medical doctors the necessary knowledge and skills to interpret results from commercial personalized genomics services, like 23andMe, deCODE, Gene by Gene, etc. This module facilitates integrating these services into their patient care activities.

Module 4: Quality Improvement in Healthcare

This module programme will aim to equip trainees with a range of knowledge and skills, which are relevant and applicable in communications within healthcare contexts. Participants will learn how to build high-performing and engaged healthcare teams, establish and sustain effective clinical relationships, as well as implement strategies and tools to support patient-centered care. Additionally, with patient safety initiatives at the forefront of care, a major goal of this module will be to help health care professionals to develop the background knowledge and skills necessary for the specialty of risk management. This module is focused especially to the communication, ethics and risks associated with genetic testing and disease risk assessment.

Career Prospects

It is commonly agreed that personalized medicine, driven by genomic sequencing of individuals, will transform medicine. There is great potential for genome sequencing to enhance patient care through improved diagnostic sensitivity and more precise therapeutic targeting [Ashley, EA. Towards precision medicine, Nature Reviews Genetics, 17, 507–522 (2016)].

This specialization enables the learner to get started with the use of genomic sequence data to enhance patient care through improved diagnostic sensitivity and more precise therapeutic targeting. These skills allow the learner to take up tasks related to analyses and interpretation of genomic sequence data, either as a doctor treating the patient or as a consulting professional.

Course Staff

Course Staff Image #1

Ferran Casals

Head of Genomics Core Facility

Universitat Pompeu Fabra (UPF)

Course Staff Image #2

Ivon Cusco

Research Scientist

Clinical and Molecular Genetics unit, Hospital Vall d’Hebron

Course Staff Image #2

Oscar Lao

PI of Population genomics

CRG-CNAG, Barcelona

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Gerard Muntané

Postdoctoral scientist

Universitat Rovira I Virgilli (URV)

Course Staff Image #2

Cedric Notredame


Notredame Lab, Comparative Bioinformatics Centre for Genomic Regulation (CRG)

Course Staff Image #1

Clara Serra

Genetic counselor

Vall d’Hebron University Hospital


The course materials of this course are licensed under a Creative Commons Attribution-NonCommercial-ShareAlike (CC-BY-NC-SA) 4.0 International License.


Feedback received from the students of the BioS course.

“The short problems and learning activities were really helpful. I enjoyed my time. The teachers were brilliant and exceptional. They handled their topics with professionalism that is unparalleled.”

“Inspiring. They open a window to innovation. Thank you.”

  • Maria Psilopoulou