If you are looking for a program with which to obtain a Postgraduate diploma in Bioinformatics and Big Data applicable to the healthcare field, this program is perfect for you. What are you waiting for? Enroll now!"

The improvement in the management of biological data that the specialties related to the health sciences have experienced with the development of bioinformatics is incalculable. Thanks to the evolution of Big Data strategies, web 3.0 and digital technology, it is now possible to carry out a massive analysis of clinical information in a very short time, optimizing the interpretation and application processes and facilitating the professional's decision-making when dealing with a patient.

Areas such as Physiotherapy have implemented the most innovative techniques related to specialized computing in their daily work, which has helped them to establish more effective and specialized therapeutic guidelines, which corresponds to one of the main objectives of Bionformatics. And in order to bring the physiotherapist closer to the latest developments in this sector, TECH has decided to release this Postgraduate diploma, a 100% online program designed by and for those versed in the area.

It is an innovative and intensive educational experience through which the specialist will be able to get up to date with the latest advances in the creation and management of different databases, the use of the most sophisticated and complex search engines or the management of the most effective statistical techniques applicable to computing. It will also delve into the massive processing of information through techniques such as structural genomics, functional genomics and transcriptomics, among others.

For this purpose, 450 hours of the best theoretical, practical and additional material will be available, the latter presented in different formats: detailed videos, research articles, complementary readings, dynamic summaries and much more. Everything will be available from the beginning of the educational activity and can be downloaded to any device with an Internet connection. In this way, graduates will have the opportunity to organize this experience in a totally personalized way and adapted to their absolute availability.

Would you like to delve into the latest developments in bioinformatics computing? Choose this program that TECH offers you 100% online and update your knowledge in just 6 months"

This Postgraduate diploma in Bioinformatics and Big Data in Medicine contains the most complete and up-to-date scientific program on the market. The most important features include:

• The development of practical cases presented by experts in bioinformatics and databases
• The graphic, schematic, and practical contents with which they are created, provide practical information on the disciplines that are essential for professional practice
• Practical exercises where the self-assessment process can be carried out to improve learning
• Its special emphasis on innovative methodologies
• Theoretical lessons, questions to the expert, debate forums on controversial topics, and individual reflection assignments
• Content that is accessible from any fixed or portable device with an Internet connection

Thanks to the exhaustiveness with which this syllabus has been designed, you will be able to implement the most effective and innovative strategies for the massive processing of clinical data in your professional practice"

The program’s teaching staff includes professionals from the sector who contribute their work experience to this educational program, as well as renowned specialists from leading societies and prestigious universities.

The multimedia content, developed with the latest educational technology, will provide the professional with situated and contextual learning, i.e., a simulated environment that will provide immersive education programmed to learn in real situations.

This program is designed around Problem-Based Learning, whereby the professional must try to solve the different professional practice situations that arise during the academic year This will be done with the help of an innovative system of interactive videos made by renowned experts.

You will delve into the effective creation of ohmic and protein project databases, which will help you to optimize the information you have available in your practice"

A perfect program to learn in detail the latest developments related to database technology in bioinformatics"

The graduate who enrolls in this Postgraduate diploma will find 450 hours of the best theoretical, practical and additional content. All this will be presented in a convenient and flexible 100% online format, thanks to which you can delve into the latest developments in Bioinformatics and Big Data from wherever you want and whenever you want, without schedules or on-site classes. In addition, all the material will be available from the beginning of the learning activity and can be downloaded to any device with an Internet connection. In this way, the specialists will be able to consult it whenever they need it, even when the educational experience is over.

The use of the Relearning methodology, as well as the inclusion of hours of high-quality additional material will make the program's course a dynamic, multidisciplinary and entertaining educational experience”

Module 1. Computing in Bioinformatics

1.1. Central Dogma in Bioinformatics and Computing. Current State

1.1.1. The Ideal Application in Bioinformatics
1.1.2. Parallel Developments in Molecular Biology and Computing
1.1.3. Dogma in Biology and Information Theory
1.1.4. Information Flows

1.2. Databases for Bioinformatics Computing

1.2.1. Database
1.2.2. Data management
1.2.3. Data Life Cycle in Bioinformatics

1.2.3.1. Use
1.2.3.2. Modifications
1.2.3.3. Archive
1.2.3.4. Reuse
1.2.3.5. Discarded

1.2.4. Database Technology in Bioinformatics

1.2.4.1. Architecture
1.2.4.2. Database Management

1.2.5. Interfaces for Bioinformatics Databases

1.3. Networks for Bioinformatics Computing

1.3.1. Communication Models. LAN, WAN, MAN and PAN Networks
1.3.2. Protocols and Data Transmission
1.3.3. Network Topologies
1.3.4. Datacenter Hardware for Computing
1.3.5. Security, Management and Implementation

1.4. Search Engines in Bioinformatics

1.4.1. Search Engines in Bioinformatics
1.4.2. Search Engine Processes and Technologies in Bioinformatics
1.4.3. Computational Models: Search and Approximation Algorithms

1.5. Data Display in Bioinformatics

1.5.1. Displaying Biological Sequences
1.5.2. Displaying Biological Structures

1.5.2.1. Visualization Tools
1.5.2.2. Rendering Tools

1.5.3. User Interface in Bioinformatics Applications
1.5.4. Information Architectures for Displays in Bioinformatics

1.6. Statistics for Computing

1.6.1. Statistical Concepts for Computing in Bioinformatics
1.6.2. Use Case: MARN Microarrays
1.6.3. Imperfect Data. Statistical Errors: Randomness, Approximation, Noise and Assumptions
1.6.4. Error Quantification: Precision and Sensitivity
1.6.5. Clustering and Classification

1.7. Data Mining

1.7.1. Mining and Data Computing Methods
1.7.2. Infrastructure for Data Mining and Computing
1.7.3. Pattern Discovery and Recognition
1.7.4. Machine Learning and New Tools

1.8. Genetic Pattern Matching

1.8.1. Genetic Pattern Matching
1.8.2. Computational Methods for Sequence Alignments
1.8.3. Pattern Matching Tools

1.9. Modelling and Simulation

1.9.1. Use in the Pharmaceutical Field: Drug Discovery
1.9.2. Protein Structure and Systems Biology
1.9.3. Available Tools and Future

1.10. Collaboration and Online Computing Projects

1.10.1. Grid Computing
1.10.2. Standards and Rules Uniformity, Consistency and Interoperability
1.10.3. Collaborative Computing Projects

Module 2. Biomedical Databases

2.1. Biomedical Databases

2.1.1. Biomedical Databases
2.1.2. Primary and Secondary Databases
2.1.3. Major Databases

2.2. DNA Databases

2.2.1. Genome Databases
2.2.2. Gene Databases
2.2.3. Mutations and Polymorphisms Databases

2.3. Protein Databases

2.3.1. Primary Sequence Databases
2.3.2. Secondary Sequence and Domain Databases
2.3.3. Macromolecular Structure Databases

2.4. Omics Projects Databases

2.4.1. Genomics Studies Databases
2.4.2. Transcriptomics Studies Databases
2.4.3. Proteomics Studies Databases

2.5. Genetic Diseases Databases. Personalized and Precision Medicine

2.5.1. Genetic Diseases Databases
2.5.2. Precision Medicine. The Need to Integrate Genetic Data
2.5.3. Extracting Data from OMIM

2.6. Self-Reported Patient Repositories

2.6.1. Secondary Data Use
2.6.2. Patients' Role in Deposited Data Management
2.6.3. Repositories of Self-Reported Questionnaires. Examples:

2.7. Elixir Open Databases

2.7.1. Elixir Open Databases
2.7.2. Databases Collected on the Elixir Platform
2.7.3. Criteria for Choosing between Databases

2.8. Adverse Drug Reactions (ADRs) Databases

2.8.1. Pharmacological Development Processes
2.8.2. Adverse Drug Reaction Reporting
2.8.3. Adverse Reaction Repositories at Local, National, European and International Levels

2.9. Research Data Management Plans. Data to be Deposited in Public Databases

2.9.1. Data Management Plans
2.9.2. Data Custody in Research
2.9.3. Data Entry in Public Databases

2.10. Clinical Databases. Problems with Secondary Use of Health Data

2.10.1. Medical Record Repositories
2.10.2. Data Encryption
2.10.3. Access to Health Data. Legislation

Module 3. Big Data in Medicine: Massive Medical Data Processing

3.1. Big Data in Biomedical Research

3.1.1. Data Generation in Biomedicine
3.1.2. High-Throughput Technology
3.1.3. Uses of High-Throughput Data. Hypotheses in the Age of Big Data

3.2. Data Pre-Processing in Big Data

3.2.1. Data Pre-Processing
3.2.2. Methods and Approaches
3.2.3. Problems with Data Pre-Processing in Big Data

3.3. Structural Genomics

3.3.1. Sequencing the Human Genome
3.3.2. Sequencing vs. Chips
3.3.3. Variant Discovery

3.4. Functional Genomics

3.4.1. Functional Notation
3.4.2. Mutation Risk Predictors
3.4.3. Association Studies in Genomics

3.5. Transcriptomics

3.5.1. Techniques to Obtain Massive Data in Transcriptomics: RNA-seq
3.5.2. Data Normalization in Transcriptomics
3.5.3. Differential Expression Studies

3.6. Interactomics and Epigenomics

3.6.1. The Role of Cromatine in Gene Expression
3.6.2. High-Throughput Studies in Interactomics
3.6.3. High-Throughput Studies in Epigenetics

3.7. Proteomics

3.7.1. Analysis of Mass Spectrometry Data
3.7.2. Post-Translational Modifications Study
3.7.3. Quantitative Proteomics

3.8. Enrichment and Clustering Techniques

3.8.1. Contextualizing Results
3.8.2. Clustering Algorithms in Omics Techniques
3.8.3. Repositories for Enrichment: Gene Ontology and KEGG

3.9. Applying Big Data to Public Health

3.9.1. Discovery of New Biomarkers and Therapeutic Targets
3.9.2. Risk Predictors
3.9.3. Personalized Medicine

3.10. Big Data Applied to Medicine

3.10.1. Potential for Diagnostic and Preventive Assistance
3.10.2. Use of Machine Learning Algorithms in Public Health
3.10.3. The Problem of Privacy

If you have always been passionate about Bioinformatics and you are thinking of pursuing a career in this field, choose a program like this one to help you on your way"