Máster en Bioinformática

Program Overview

The Master's Degree in Bioinformatics at Universidad Europea is an online program that provides training in the management and analysis of health data for personalized medicine. It emphasizes health data science, drug design, and clinical trials, and offers practical experience with industry-leading tools and technologies. Graduates will be prepared for careers in industry, healthcare settings, and research.

Program Outline

Degree Overview:

The Master's Degree in Bioinformatics is an official degree designed to train professionals transversally for data management in the health area and the transfer of results to clinical practice. It is the only official degree on the market with a program applied to health, contextualized with a specific storyline towards personalized and precision medicine. This marks a clear difference from other purely technical programs, which have been designed as an accumulation of tool learning. The faculty is made up of active professionals, leaders in the sector, with extensive professional experience in companies such as Kyowa Kirin International plc., Repsol-Química and REDCap, among others, with whom you will work hand in hand on real projects.

Objectives:

• To train professionals in the field of bioinformatics, with a focus on health data science and precision medicine.
• To provide students with the skills and knowledge necessary to analyze and interpret biological data, develop new diagnostic and therapeutic tools, and contribute to the advancement of personalized medicine.
• To prepare students for careers in research, industry, and healthcare.

Outline:

Structure of the curriculum:

• Module 1 - Fundamentals of Biomedicine and Translational Medicine (6 ECTS)
• Description of the fundamental aspects of the structure and function of the human body and main aspects of translational research processes.
• Structure and Function.
• Experimental models in Biomedicine.
• From bench to bedside.
• Introduction to therapy and translational research.
• Communication, Transfer and Scientific Management.
• Biobanking, Ethics, and Relevant.
• Module 2 - Bioinformatics Applied to Molecular Diagnosis (6 ECTS)
• Exploitation of biological databases.
• Molecular diagnosis.
• Molecular diagnosis in cancer and infectious diseases.
• Genetic tests.
• Gene panels.
• Massive sequencing technologies.
• Biological databases.
• Relational databases.
• Data mining.
• Data repositories and knowledge discovery in databases.
• Module 3 - Biomedical Informatics (6 ECTS)
• Data integration in a clinical setting.
• Big Data and Precision Medicine.
• Fundamentals of electronic health.
• Large amounts of data in Clinical Medicine.
• Quality parameters in large medical and biomedical data repositories.
• Precision medicine.
• Module 4 - Research Methodology I (6 ECTS)
• Mathematical and statistical models in Bioinformatics and Computational Biology.
• Statistics and Probability.
• Inferential analysis.
• Introduction to genomics.
• Computational tools to exploit omics data of different natures.
• Statistical and machine learning methods.
• Networks in systems biology.
• Module 5 - Research Methodology II (6 ECTS)
• Introduction to Data Science in Health: Machine learning and Deep learning for the optimization of diagnosis, adaptation of treatments and personalization of therapies.
• Natural language processing.
• Machine learning applied to medicine.
• AI (artificial intelligence).
• Preventive and Predictive Medicine.
• Module 6 - Applied Bioinformatics I (6 ECTS)
• Design of innovative therapies and drugs.
• Historical introduction to drug design and development.
• Drug research and development.
• Phases of new drug development.
• Toxicity studies and drug optimization.
• Patents in the pharmaceutical industry.
• Module 7 - Applied Bioinformatics II (6 ECTS)
• Molecular modeling, docking, virtual screening and other techniques commonly used in computer-aided drug design.
• Childhood and health.
• Fundamentals of molecular structure.
• Macromolecular movements.
• Interactions between molecules.
• Ligand-receptor docking.
• Module 8 - Applied Bioinformatics III (6 ECTS)
• Personalized or precision medicine.
• Planning and design of translational studies.
• Biomarkers for personalized or precision medicine.
• Ethical and legal aspects of the exploitation and management of Big Data in Medicine.
• AI and genomics for Precision medicine.
• Clinical reports with precision medicine data.
• Module 9 - Applied Bioinformatics IV (6 ECTS)
• Clinical Trials.
• The MSL figure.
• Clinical trial protocols.
• Statistical analysis and validation of data resulting from CT.
• Master Protocols.
• Pharmacovigilance mechanisms in CT.
• Module 10 - Master's Thesis (6 ECTS)
• Consists of the development of a research project in the fields of bioinformatics, data science and translational medicine.
• Phases of research.
• Choice and justification of the topic.
• Construction of the theoretical framework.
• Research objectives.
• Material and method.
• Collection and analysis of preliminary results.

Teaching:

• Online with live classes: The program is delivered online with live classes that are recorded and accessible on the Virtual Campus.
• Faculty: The faculty is made up of active professionals, leaders in the sector, with extensive professional experience in companies such as Kyowa Kirin International plc., Repsol-Química and REDCap, among others.
• Unique approaches: The program includes a focus on health data science and precision medicine, which is a unique feature that sets it apart from other bioinformatics programs.

Careers:

• Industry: Biotechnology and healthcare product development industry (MSL)
• Hospital setting: Electronic medical records and precision medicine
• Research and development (R&D): Preclinical and clinical research
• Academic setting: Access to doctorate and teaching and research career
• Core Facilities: Sequencing platforms and institutes, genomic, proteomic and metabolomic data analysis
• Pharmaceutical industry: Development of new drugs and repositioning of old drugs for emerging diseases
• Data analysis: Use of IT tools and management of health data (Data Science, Business Analytics in Healthcare)
• Database maintenance
• Consulting: Healthcare AI Consultant, Healthcare Project Manager

Other:

• The program includes access to the "Python Fundamentals" course from CISCO, which will allow students to familiarize themselves with the campus, refresh programming concepts if they are a technical profile or start in this field if they come from the health or biomedical areas.
• The program is integrated with the University's own research lines, which gives students direct access to doctoral programs.
• The program offers training in clinical trials, which is a unique feature that sets it apart from other bioinformatics programs.
• The program includes a focus on legal aspects, such as the laws governing the handling of data in pre-clinical and clinical research.
• The program includes a focus on Health Data Science, which involves working with R and R Studio, Python and BioPython, and related libraries focused on the health field, Big Data, intelligent data analysis using artificial intelligence (AI), natural language processing, database creation and data mining.
• The program includes 4 modules of applied bioinformatics, oriented to the new job profiles that work with data in health, a differentiating point in your curriculum.
• The program includes access to the latest technologies, such as REDCap, Dr. Larrasa Laboratories, Dreamgenics, 24 Genetics, and Sycai Medical.
• The program includes the opportunity to earn two digital recognition badges that accredit your knowledge and training in Health Data Science and in the management of research data in a clinical setting through the specific use of the REDCap tool.
• The program is offered by the Universidad Europea, which is a leading institution in innovation and quality education.
• The program is flexible and can be adapted to the student's needs.
• The program is experiential and includes practical exercises and real-world cases in simulated environments.
• The program includes constant communication with the university, professors, and classmates.
• The program includes continuous support from professors and tutors.
• The program is based on a learning model that prepares students for the needs of the professional world.
• The program includes experiential learning, significant learning, collaborative learning, professional learning, constructive and discovery learning, autonomous learning, individualized learning, and creative learning.
• The program is open to graduates in Medicine, Nursing, Human Nutrition and Dietetics, Pharmacy, Psychology, Biology, Chemistry, Biomedicine, Biotechnology, Biochemistry, and other related fields.
• The program is also open to mathematicians, physicists, statisticians, computer scientists, and engineers from different branches with professional experience, research activity, or previous postgraduate training in the biomedical field.
• The program is offered online and can be accessed throughout the year.
• The program includes a scholarship and aid program.
• The program has a leading faculty, including Dr. Rocío González Soltero, Dr. Ana Fernández Santander, Laura Núñez Bárez, Dr. María Peña Chilet, Javier Escalera Orobón, Carlos Rodríguez Abellán, Dr. Javier Pérez Florido, Dr. Pablo Ryan Murua, Dr. Juan José Beunza Nuín, Rocío Queipo Matas, Dr. Ana Isabel Rodríguez Learte, Dr. Verónica Moral Dardé, Dr. Jon Del Arco, and Dr. Antonio Morreale.
• The program has a quality assurance system that includes an internal quality plan, external recognition and accreditation, measurement and analysis of results, simplification of management, and relationship with the external regulator.
• The program has a high graduation rate and student satisfaction.
• The program includes student services such as academic management services, career services, and a suggestion, complaint, and claim mailbox.