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Integrated Learning in Medicine V and Bioinformatics

Code: 106918
Credits: 5
2026/2027
Degree programme Type Course
Medicine OB 6

Contact lecturer

Name :
Raul Martinez Fernandez
Email :
raul.martinez.fernandez@uab.cat

Teaching staff

Jesus Pérez Pérez
Javier Pagonabarraga Mora
Carlos Rodrigo Gonzalo De Liria
Gianluigi Caltabiano
Oriol Gasch Blasi
Angel Gonzalez Wong
Oscar Manuel Len Abad

Teaching staff (external to UAB)

Maria Borrell Pichot

Group languages

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

Prerequisites

Students are expected to have acquired a basic understanding of clinical pathophysiology and semiology, structural pathology, complementary diagnostic techniques, medical imaging, clinical microbiology and laboratory medicine, as well as the principles of pharmacology and therapeutics across the different human organ systems.

Students should also possess sufficient knowledge of the physiological and psychological bases of health and disease, together with fundamental interpersonal communication skills.

In addition, a basic background in molecular biology, genetics, biostatistics, and digital competencies is recommended. A good command of scientific English is advisable, as a substantial proportion of the scientific literature and learning resources are available in this language. Familiarity with basic data analysis tools and biomedical databases is also considered beneficial.

Objectives

Course overview

This is a year-long course taught during the sixth year of the Medicine Degree.

Like the other Integrated Multidisciplinary Courses (AIM), it is a cross-disciplinary course designed to develop the core competencies required for medical practice and scientific thinking. Its overall aim is to provide an integrated approach to medical knowledge, enabling students to understand the biological and pathophysiological foundations of medicine and the clinical disciplines as closely interconnected areas that ensure continuity throughout the healthcare process.

Throughout the course, students develop cross-cutting competencies including clinical and scientific reasoning, evidence-based argumentation, hypothesis generation, the ability to formulate relevant questions, and the critical interpretation of scientific information. The course also promotes the ability to search, select and critically appraise the scientific literature and biomedical databases, together with the use of information technologies, bioinformatics tools and basic data analysis techniques applied to clinical problem solving.

The course also contributes to the development of professional skills such as teamwork, oral and written communication, discussion and critical appraisal of ideas among peers, evidence-based decision making, adherence to the ethical principles of medical practice, and critical reflection on one’s own learning process, fostering lifelong learning and professional development.

Teaching is based on the resolution of clinical cases, which are updated every academic year. Students work in small groups under the supervision of a tutor responsible for each case, together with faculty members from the different disciplines involved. The course follows a Problem-Based Learning (PBL) methodology, combining tutorial sessions with independent student work. During the introductory session, the objectives and methodology of each case are presented. Students are then expected to attend the scheduled tutorials, consult relevant information sources, critically appraise the available evidence, and prepare a proposed solution that is presented and discussed during the final group session.

The Bioinformatics module follows a blended teaching approach. It includes an introduction to the most widely used bioinformatics tools in biomedicine, guided and independent case-based activities, and a final group project presented in the format of a scientific congress during the final session.

General Learning Objectives

  • Acquire the fundamental skills required for medical practice by integrating scientific and clinical knowledge into the management of health problems.
  • Consolidate the scientific foundations of the basic procedures of clinical medicine and apply them to clinical reasoning and evidence-based diagnostic and therapeutic decision-making.
  • Integrate knowledge acquired throughout the Medicine Degree and apply it to simulated clinical scenarios using a Problem-Based Learning approach.
  • Develop skills in syndromic diagnosis, critical interpretation of complementary investigations, and assessment of the benefits, risks and limitations of different diagnostic and therapeutic strategies.
  • Develop competencies in searching, selecting and critically appraising scientific information using bibliographic resources, biomedical databases, bioinformatics tools and information technologies applied to biomedical research.
  • Foster critical thinking, hypothesis generation, scientific reasoning, and the ability to communicate scientific findings clearly and accurately, both orally and in writing.
  • Promote self-directed learning, teamwork, organizational skills, reflection on the learning process, and a commitment to lifelong learning and good professional practice.
  • Develop competencies in the critical, ethical and responsible use of artificial intelligence tools to support clinical decision-making, biomedical research and lifelong professional learning.

Specific and Transversal Competencies

  • Communicate clearly and effectively, both orally and in writing, with patients, relatives, healthcare professionals and society, adapting communication to the context and audience.
  • Integrate biomedical and clinical knowledge to understand disease mechanisms and apply this knowledge to clinical reasoning, diagnosis and therapeutic decision-making.
  • Apply scientific thinking, the scientific method and evidence-based medicine to formulate hypotheses, critically analyse information and solve clinical problems.
  • Efficiently use statistical methodologies, information technologies, bioinformatics tools and biomedical databases in clinical practice and biomedical research.
  • Develop self-directed learning skills, organizational abilities, teamwork and interdisciplinary collaboration while recognising personal limitations and valuing the contributions of other professionals.
  • Obtain, synthesise and accurately document relevant clinical information, producing clear and well-structured clinical records and reports.
  • Select, interpret and critically evaluate the most appropriate diagnostic and therapeutic procedures, considering their indications, limitations, risks, benefits and cost-effectiveness.
  • Practise medicine according to ethical, legal and professional standards while promoting the responsible management of healthcare resources.
  • Integrate a gender perspective into healthcare by recognising the impact of sex, gender and gender-related determinants on disease presentation, clinical communication and medical decision-making, thereby promoting equitable, patient-centred care.


  • BIOINFORMATICS
  • Objectives
  • General Objectives:
  • Equip students with basic and advanced skills for the use of Bioinformatics tools, which are essential in current medical research and modern clinical practice.
  • Promote a critical understanding of the application of Bioinformatics in disease diagnosis, prognosis, and treatment, as well as in the personalization of medicine through the use of genomic data and other digital biomedical resources.
  • Specific Objectives:
  • Effectively use major Bioinformatics electronic resources that provide access to databases and tools for Biomedical, Genomic, and Proteomic research—such as NCBI, EMBL-EBI, and others—to obtain relevant information in the field of Medicine.
  • Recognize the utility and potential of Bioinformatics information technologies in various areas of medical knowledge, such as Oncology, Genetics, and Pharmacogenomics, and apply them effectively to draw clinical conclusions.
  • Interpret and analyze biological data using Bioinformatics tools and artificial intelligence for the analysis of omics data and the prediction of clinical phenotypes, highlighting practical applications.
  • Develop the ability to integrate Bioinformatics knowledge into scientific research, thereby contributing to interdisciplinary projects that connect computational biology with clinical practice.

Learning outcomes

  1. Describe the person as a multidimensional being in which the interplay of biological, psychological, social, environmental and ethical factors determines and alters the states of health and disease and their manifestations.
  2. Identify the basic principles of legislation on health and the right to health.
  3. Describe the organisation, characteristics and performance of the Spanish health system.
  4. Explain ethical, legal and technical features and those of confidentiality related to patient documentation.
  5. Be self-critical and reflect on one's own learning.
  6. Accept other viewpoints (lecturers, colleagues, etc.) regarding the problem or topic at hand.
  7. Adopt values of solidarity and service to others, both when dealing with patients and with the general public.
  8. Acquire the principles and values of good medical practice, both in health and in illness.
  9. Compare one's own opinions with those of colleagues and other healthcare professionals as a basis for teamwork.
  10. Apply analytic tests in accordance with their cost efficiency.
  11. Correctly apply statistical techniques to obtain benchmark values and compare them to the results of analytic tests on patients.
  12. Use appropriate statistical techniques to study the semiological value of analytic tests.
  13. Explain the mechanisms by which illness affects the different systems of the human body at different stages in life and in both sexes.
  14. Assess the importance of every sign and symptom in the current illness.
  15. Assess the semiological value of laboratory tests used in the most common human pathologies.
  16. Identify the physical, chemical, environmental, psychological, social and occupational and carcinogenic factors, and the factors associated with food habits and drug use, that determine the development of the disease.
  17. Assess the relationship between efficacy and risk in the main therapeutic interventions.
  18. Assess the efficiency of the main therapeutic interventions.
  19. Interpret population parameters of individual risks appropriately.
  20. Conduct the interview correctly to obtain significant clinical data.
  21. Gather, choose and record important information patient supplied by patients and accompanying persons.
  22. Gather meaningful psychosocial data.
  23. Identify serious clinical situations.
  24. Distinguish normality from pathological alterations on performing a physical examination.
  25. Identify symptoms of anxiety, depression, psychosis, toxics consumption, delirium and cognitive deterioration.
  26. Establish a method for complementary examinations, in accordance with the standard process and the diagnostic expectations.
  27. Assess the need, indications, contraindications, chronology, risk, benefits and costs of each examination.
  28. Indicate and interpret the basic techniques and procedures for laboratory diagnosis, diagnostic imaging and others.
  29. Obtain, in an appropriate way, clinical samples needed for laboratory tests.
  30. Identify the most efficient analytic tests for prevention, diagnosis and control of treatment for the most common human pathologies.
  31. Calculate the cost efficiency of analytic tests.
  32. Critically assess the results of complementary examinations, taking their limitations into account.
  33. Order signs and symptoms to perform a differential syndromic diagnosis.
  34. Establish a therapeutic action plan considering the needs of patients and their family and social environment, and involving all members of the healthcare team.
  35. Distinguish situations that require hospitalisation and those that require intensive care.
  36. Identify type, evolution and limitations in chronic diseases, their possible treatments and prevention of complications.
  37. Indicate suitable therapeutic interventions for the main health problems.
  38. Appraise patients' expectations in order to respect them and act appropriately.
  39. Summarise and order information on the problems of the sick.
  40. Identify patients' social and health needs.
  41. Involve the family in patient healthcare.
  42. Correctly record the information obtained in interviews with patients.
  43. Inform on the results of analytic tests.
  44. Describe the elements that should be considered when determining the reasons for a consultation and those of the patient's therapeutic itinerary.
  45. Use biomedical databases.
  46. Identify sources of information on analytic tests for patients and professionals and critically evaluate their content.
  47. Maintain and sharpen one's professional competence, in particular by independently learning new material and techniques and by focusing on quality.
  48. Organise and plan time and workload in professional activity.
  49. Convey knowledge and techniques to professionals working in other fields.
  50. Demonstrate, in professional activity, a perspective that is critical, creative and research-oriented.
  51. Formulate hypotheses and compile and critically assess information for problem-solving, using the scientific method.
  52. Demonstrate basic research skills.
  53. Communicate clearly, orally and in writing, with other professionals and the media.
  54. Use information and communication technologies in professional practice.

Contents

Depending on the number of student groups, different clinical cases (at least one case per group) are developed based on the contents of the subjects included in Module 3 (Human Clinical Training). These cases are addressed using the Problem-Based Learning (PBL) methodology.

The clinical cases may primarily integrate content from the following disciplines:

  • Neurology
  • Endocrinology
  • Infectious Diseases
  • Paediatrics
  • Psychiatry
  • Clinical Dermatology

Whenever required by the nature of the case, content from Modules 2 and 4 is also incorporated, promoting a multidisciplinary approach to the diagnostic, therapeutic and research processes.

Module 4. Diagnostic and Therapeutic Procedures

  • Medical Microbiology and Parasitology
  • Clinical Radiology
  • Structural and Molecular Pathology
  • General Pharmacology
  • Clinical Pharmacology
  • Medical Immunology

Module 2

  • Social Medicine, Communication Skills and Introduction to Research
  • Preventive Medicine and Public Health
  • Forensic Medicine and Toxicology

The resolution of clinical cases enables students to integrate basic and clinical knowledge, develop diagnostic and therapeutic reasoning, critically interpret complementary investigations, apply the principles of evidence-based medicine, use biomedical information resources and digital tools, work effectively in multidisciplinary teams, and communicate their conclusions clearly and rigorously in accordance with the ethical principles of medical practice.


Bioinformatics Module.


Practical sessions in Bioinformatics applied to Medicine




DISTRIBUTIVE BLOCKS


Presentation and solution of various clinical pathology cases, to be defined for each group




Bioinformatics Module:


The Bioinformatics module consists of 5 face-to-face sessions of 2 hours each, which combine theoretical classes and supervised practices, as well as autonomous activities. The teaching will be of a mixed type, with an initial introductory part to the most used tools, followed by the resolution of practical cases, both in a tutored and autonomous manner. At the end of the module, students will work in groups to prepare and present a complex clinical case, using the Bioinformatics tools studied.


Session 1 (2h) - Introduction to basic Bioinformatics tools and resources (ABP):


Students will be introduced to the most used tools and resources in Bioinformatics, including genomic databases (NCBI, EMBL-EBI) and genome browsers. Practical exercises will be carried out in the use of Genome Data Viewer, Ensembl and other platforms.


Session 2 (2h) - Genetic Variations and Mendelian Diseases (ABP):


Genetic variations and their relationship with Mendelian diseases will be studied, using databases such as dbSNP, ClinVar and OMIM. Case studies related to mutations and clinical variants will be analyzed.


Session 3 (2h) - Tutored Case Resolution (ABP):


AI-based clinical prediction tools will be introduced to support genetic diagnosis, trained to detect pathogenic variants. A clinical case will be presented that students will have to resolve using bioinformatics tools.


Session 4 (2h) - Group Resolution of a Selected Case (ABP):


Students, divided into groups, will work autonomously on the resolution of a selected clinical case. Each group will use the most appropriate Bioinformatics tools to reach diagnostic and therapeutic conclusions. This session will be guided by teachers, allowing students to apply the knowledge acquired in previous sessions.


Session 5 (2h) - Congress: Evaluated Oral Case Presentations (ABP):


The groups will present the results of their work to their peers and teachers, in a scientific congress format. Both the scientific quality of the work and the ability to communicate orally will be assessed.

Learning activities and methodology

Title Hours ECTS Learning outcomes
PERSONAL STUDY / READING ARTICLES / REPORTS OF INTEREST 94.25 3.77
PROBLEM-BASED LEARNING (PBL) 25 1

Teaching Methodology

This guide outlines the framework, contents, teaching methodology, and general regulations of the course in accordance with the current curriculum. The final organization of the course, including the clinical cases, number and size of student groups, timetable, examination dates, specific assessment criteria, and examination review procedures, will be determined by each Hospital Teaching Unit (HTU). These details will be made available through the corresponding HTU websites and communicated on the first day of class by the faculty members responsible for the course.

Course Coordinators

Responsible Department

Multidisciplinary

Faculty Coordinator

Raúl Martínez Fernández (rmartinezf@santpau.cat)

Hospital Teaching Unit (HTU) Coordinators

  • Vall d’Hebron HTU: Oscar Len (oscarmanuel.len@vallhebron.cat)
  • Germans Trias i Pujol HTU: Carlos Rodrigo Gonzalo de Liria (crodrigo.germanstrias@gencat.cat)
  • Sant Pau HTU: Raúl Martínez Fernández (rmartinezf@santpau.cat)
  • Parc Taulí HTU: Oriol Gasch Blasi (ogasch@tauli.cat)

Bioinformatics Module Coordinator

Ángel González Wong (Angel.Gonzalez@uab.cat)

Tutors and Teaching Sessions

Each clinical case will be supervised by a tutor from one of the Module 3 subjects involved in the case. The tutor will coordinate the case presentation, tutorials, follow-up activities, and the final discussion session.

Module 3. Human Clinical Training

  • Internal Medicine IV (Neurology, Endocrinology and Infectious Diseases)
  • Paediatrics
  • Psychiatry
  • Clinical Dermatology

Whenever required by the nature of the clinical case, faculty members from Modules 2 and 4 will also participate.

Module 4. Diagnostic and Therapeutic Procedures

  • Medical Microbiology and Parasitology
  • Clinical Radiology
  • Structural and Molecular Pathology
  • General and Clinical Pharmacology
  • Medical Immunology

Module 2

  • Social Medicine, Communication Skills and Introduction to Research
  • Preventive Medicine and Public Health
  • Forensic Medicine and Toxicology

Course Organization

AIM Course

  • Total workload: 3 ECTS (75 hours)
  • Independent learning: 55% (41.25 hours)
  • Guided learning activities: 40% (30 hours)
  • Assessment: 5% (3.75 hours)

Bioinformatics Module

  • Total workload: 2 ECTS (50 hours)
  • Independent learning: 52% (26 hours)
  • Guided learning activities: 44% (22 hours)
  • Assessment: 4% (2 hours)

Clinical Case Development

Clinical cases are developed using a Problem-Based Learning (PBL) approach.

Throughout the case-solving process, students identify clinical problems, formulate diagnostic and therapeutic hypotheses, search for and select relevant scientific information, critically appraise the available evidence, use biomedical databases, digital technologies and bioinformatics tools, and discuss alternative diagnostic and therapeutic strategies in a structured and evidence-based manner. This process promotes clinical and scientific reasoning, teamwork, and evidence-based decision-making.

Whenever appropriate, students will apply basic concepts of data analysis and statistical interpretation to evaluate the performance of diagnostic tests and the quality of scientific evidence.

All students are expected to become familiar with and actively participate in the resolution of every clinical case, as both participation and engagement throughout the process constitute essential components of continuous assessment.

Suggested Timeline

Week 1: Presentation of clinical cases (5 × 1 hour)

Week 2: Literature search, documentation and problem solving (5 × 2 hours)

Week 3: Case discussion, supervision and preparation of the final presentation (5 × 2 hours)

Week 4: Case presentation, discussion and closing session (5 × 1 hour)

Assessment

Assessment will be continuous and based on the following components:

1. Attendance and Active Participation (30%)

Attendance is mandatory. Assessment will consider active participation, teamwork, quality of contributions during discussions, clinical and scientific reasoning, evidence-based argumentation, and each student’s individual contribution to solving the clinical cases.

2. Questionnaires and Practical Exercises (40%)

Students will complete questionnaires and practical activities using bioinformatics resources, biomedical databases and other scientific information sources. Assessment will focus on their ability to identify, interpret and critically evaluate the quality of scientific evidence and apply it appropriately to clinical problem-solving.

3. Final Congress-Style Presentation (30%)

Students will present, as a group, the results of one clinical case using the most appropriate bioinformatics tools. Assessment will include scientific rigor, integration of knowledge, quality of critical analysis, oral and written communication skills, discussion of results, and the ability to answer questions from the audience.

Following each presentation, students will receive formative feedback aimed at promoting reflection on their learning process, improving clinical and scientific reasoning, and fostering the development of professional competencies.

Use of Artificial Intelligence Tools

The use of artificial intelligence (AI) tools is permitted to support literature searches, knowledge synthesis, language editing and the critical appraisal of scientific literature. These tools must not replace students’ own scientific reasoning, clinical judgment or intellectual work. Students remain fully responsible for the accuracy, quality and academic integrity of all submitted work and may be required to disclose any substantial use of AI tools.

Fifteen minutes of one teaching session will be allocated for students to complete the institutional course and faculty evaluation surveys.

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
Attendance and active participation (AIMV) 12% of the final mark 0 0 4, 8, 14, 15, 17, 20, 30, 37, 38, 40, 41, 45
Written evaluations through objectives tests (AIMV) 30% of the final mark 1.75 0.07 11, 12, 13, 17, 19, 20, 22, 23, 24, 25, 33, 38, 44, 48, 49, 51, 52, 53
Congress / Presentation of works (Bioinformatics) 12% of the final mark 2 0.08 1, 2, 3, 7, 16, 20, 21, 23, 24, 35, 36, 44, 45, 47
Attendance and active participation (Bioinformatics) 12% of the final mark 0 0 4, 7, 8, 9, 20, 21
Assessments trough practical cases and problem resolution (AIMV) 18% of the final mark 2 0.08 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 15, 16, 17, 18, 20, 21, 23, 24, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54
Resolution of questionnaires (Bioinformatics) 16% of the final mark 0 0 9, 10, 21, 45, 47

Assessment Activities

Each student will participate in the presentation and resolution of one clinical case. The main assessment strategy for this course is continuous assessment of the work carried out by each group throughout the four sessions devoted to each case. This approach is intended to enable students, regardless of the specific content of each case, to integrate knowledge from different disciplines, formulate diagnostic and therapeutic hypotheses, apply clinical and scientific reasoning, work collaboratively, communicate effectively, and justify their decisions on the basis of the best available scientific evidence.

Throughout the process, students will also be assessed on their ability to search for, select and critically appraise the scientific literature, biomedical databases and other digital resources, as well as on their ability to integrate the acquired knowledge into the resolution of clinical cases.

Case Presentation and Discussion

The presentation will be shared equally among all members of the group responsible for the case, with equivalent presentation time allocated to each student. The case will be presented to the entire class following a common structure and within an overall presentation time of approximately 40 minutes.

Assessment will consider the scientific rigor of the presentation, the integration of knowledge, the quality of clinical reasoning, evidence-based argumentation, oral communication skills, the ability to answer questions, and active participation in the scientific discussion.

Continuous Assessment

Attendance at all case presentation sessions, final discussion sessions and scheduled meetings with the tutor is mandatory. These meetings may be held either face-to-face or online (Microsoft Teams). Failure to attend these activities will prevent the student from being assessed.

Particular emphasis will be placed on the assessment of:

  • Active participation in tutorials and discussions.
  • Teamwork and collaboration with other group members.
  • Formulation of diagnostic and therapeutic hypotheses.
  • The ability to identify, select and critically interpret the scientific literature and biomedical databases.
  • The application of evidence-based medicine principles to the resolution of clinical cases.
  • Critical interpretation of complementary investigations and justification of diagnostic and therapeutic decisions.
  • Organisation of work, self-directed learning and the quality of individual contributions.
  • Oral and written communication of results and scientific argumentation.

At the end of each case, each group will prepare a written report that will be shared with all students enrolled in the course. This report will also form part of the assessment and should demonstrate the ability to synthesise information, scientific rigor, quality of critical analysis and appropriate justification of the conclusions.

As a guideline, the final report should include:

  • Case summary.
  • Differential diagnosis.
  • Diagnostic hypothesis and proposed management plan.
  • Complementary investigations.
  • Recommended diagnostic tests and assessment of their risk-benefit balance.
  • Final diagnosis.
  • Treatment.
  • Prognosis.

Following each case presentation, students will receive formative feedback aimed at promoting critical reflection on their own learning process, improving clinical and scientific reasoning, and fostering the development of professional competencies.


Bioinformatics Module

Assessment

Assessment will be continuous and based on:

1. Attendance and active participation in sessions (30%):

Attendance is mandatory in all sessions. Active participation in classes and student contributions to solving cases and exercises will be assessed.

2. Completion of questionnaires and practical exercises (40%):

Quizzes will be given in each session, which students will be required to complete using the bioinformatics resources studied. These questionnaires will aim to consolidate the knowledge acquired and ensure its practical application.

3. Final presentation at the Conference (30%):

Students will present the results of solving a clinical case in a group, using the most appropriate bioinformatics tools. The presentation will be delivered in PowerPoint format, and both scientific quality and presentation skills will be assessed.

Students who wish to obtain a First Class Honors will be required to take a multiple-choice test consisting of 3 to 5 questions for each of the cases worked on during the course by all groups, including 3 to 5 questions related to the Bioinformatics Module and the tools used. This test will be based on the documents prepared by each group. The highest grades will be eligible for a First Class Honors.

Students who do not pass the course through continuous assessment will be graded as \"NOT EVALUABLE.\" The assessment, while following a similar pattern, may be adapted to the characteristics of each Hospital Teaching Unit. A make-up exam will be scheduled based on cases presented by students who have not passed the course content, in a format to be determined.

This course does not include a single assessment system.

Bibliography

Consult the specific bibliography of the teaching guides for the different fifth year subjects.

Bioinformatics Module

Bioinformatics

Recommended Bibliography

* Introduction to Bioinformatics / Teresa K. Attwood, David J. Parry-Smith; translation: Fernando González Candelas. Madrid: Prentice Hall, 2002.

* Translational Bioinformatics in Healthcare and Medicine. 1st Edition - May 13, 2021.

* Next generation sequencing and the future of genetic diagnosis. Neurotherapeutics. 11: 699-707. 2014.

* Topol, E. (2019). Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again. Basic Books.

* Diagnostic Clinical Genome and Exome Sequencing. New England Journal of Medicine. 370: 2418-2425. 2014

Programs

At the beginning of the module, the specific program needed to complete the practical activities will be provided to the virtual campus for the course, including access to databases and online resources.

Internet Resources

* National Institutes of Health (NIH)

* National Center for Biotechnology Information (NCBI)

* European Bioinformatics Institute (EMBL-EBI)

* Online Mendelian Inheritance in Man (OMIM)

* National Human Genome Research Institute

* MedlinePlus in Spanish

* Pharmacogenomics Knowledgebase (PharmGKB)

* The Genetic and Rare Diseases (GARD) Information Center

Software

Specific software is not required for the part of clinical cases.  

 

Bioinformatics Programs

At the beginning of the module, the specific program needed to complete the practical activities will be provided to the virtual campus for the course, including access to databases and online resources.

Internet Resources

* National Institutes of Health (NIH)

* National Center for Biotechnology Information (NCBI)

* European Bioinformatics Institute (EMBL-EBI)

* Online Mendelian Inheritance in Man (OMIM)

* National Human Genome Research Institute

* MedlinePlus in Spanish

* Pharmacogenomics Knowledgebase (PharmGKB)

* The Genetic and Rare Diseases (GARD) Information Center

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