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Why study at TECH?
Thanks to TECH Global University, you will learn the mininvasive development of clinical practices in only 6 months of academic instruction"
The incorporation of bioinformatics in the health field is an advance that acts in parallel with Big Data and, with COVID, it was fundamental for the knowledge and interpretation of data at a global level. These disciplines enable the management of the enormous volume of data generated by new omics technologies. Bioinformatics is a high-level approach to mutation in biology, which is why it has gained importance over the years and its scientific evidence. Â
Currently, controlling the mutation of epidemiological diseases is the main reason for the increase in bioinformatics studies. If possible, the vaccine would have been unique and it would not be necessary to look for alternatives according to the variation of the disease. For this reason, TECH Global University offers a Postgraduate diploma inBioinformatics and Big Data in Medicine, aimed at graduates in Nursing to expand and update the knowledge of these professionals so that they are able to apply it in their daily work. Â
This Postgraduate diploma is supported by an expert teaching team in biomedicine that will transmit not only theoretical knowledge to the students, but will also instruct them based on their own real experience through case simulations. Also, TECH Global University applies the Relearning methodology to offer dynamic instruction that does not require long hours of memorization. Â Likewise, thanks to its 100% modality and its audiovisual content, students will be able to a dapt the pace of study to their personal and professional possibilities. Â Â
Not proficient in Machine Learning algorithms? Enroll now in a program that will not only teach you to understand public health computing, but will also instruct you in bioinformatics" Â
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: Â
- 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 practiceÂ
- Practical exercises where the self-assessment process can be carried out to improve learningÂ
- Its special emphasis on innovative methodologies Â
- Theoretical lessons, questions to the expert, debate forums on controversial topics, and individual reflection assignmentsÂ
- Content that is accessible from any fixed or portable device with an Internet connection
Thanks to TECH Global University, you will be able to understand the ins and outs of bioinformatics and become a much more competent and competitive professional in the job market"Â
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. Â
Its multimedia content, developed with the latest educational technology, will allow the professional a situated and contextual learning, that is, a simulated environment that will provide an immersive training programmed to train in real situations. Â
The design of this program focuses on Problem-Based Learning, in which the professional will have to try to solve the different professional practice situations that will arise throughout the academic course. This will be done with the help of an innovative system of interactive videos made by renowned experts. Â Â Â
Prevention and health diagnosis is in the hands of technology and how the professionals of the future know how to implement it. Update yourself withTECH Global University"
Enroll now in this Postgraduate diploma to deepen in data preprocessing techniques with Gene Ontology and KEGG"
Syllabus
The syllabus of this Postgraduate diploma in Bioinformatics and Big Data in Medicine has been designed in detail by professionals working in the field of bioinformatics and biomedicine, among other disciplines of Health Sciences. It is a 100% online program that streamlines the educational process around knowledge in computing, biomedical databases and Big Data in medicine. TECH Global University achieves this thanks to the innovative Relearning methodology. With it, students will not have to invest long hours of memorization, but will be able to assimilate the contents gradually and steadily. In this way, the study will be adapted with total flexibility to their availability, obtaining a personalized academic experience in line with their professional and personal obligations. Â
Develop molecular biology and computation in parallel to witness its multiple advantages. This is the only way you will be part of the evolution in Health"
Module 1. Computation in BioinformaticsÂ
1.1. Central Tenet in Bioinformatics and Computing. Current StateÂ
1.1.1. The Ideal Application in BioinformaticsÂ
1.1.2. Parallel Developments in Molecular Biology and ComputingÂ
1.1.3. Dogma in Biology and Information TheoryÂ
1.1.4. Information FlowsÂ
1.2. Databases for Bioinformatics ComputingÂ
1.2.1. DatabaseÂ
1.2.2. Data managementÂ
1.2.3. Data Life Cycle in BioinformaticsÂ
1.2.3.1. UseÂ
1.2.3.2. ModificationsÂ
1.2.3.3. ArchiveÂ
1.2.3.4. ReuseÂ
1.2.3.5. DiscardedÂ
1.2.4. Database Technology in BioinformaticsÂ
1.2.4.1. ArchitectureÂ
1.2.4.2. Database ManagementÂ
1.2.5. Interfaces for Bioinformatics DatabasesÂ
1.3. Networks for Bioinformatics ComputingÂ
1.3.1. Communication Models. LAN, WAN, MAN and PAN NetworksÂ
1.3.2. Protocols and Data TransmissionÂ
1.3.3. Network TopologiesÂ
1.3.4. Datacenter Hardware for ComputingÂ
1.3.5. Security, Management and ImplementationÂ
1.4. Search Engines in BioinformaticsÂ
1.4.1. Search Engines in BioinformaticsÂ
1.4.2. Search Engine Processes and Technologies in BioinformaticsÂ
1.4.3. Computational Models: Search and Approximation AlgorithmsÂ
1.5. Data Display in BioinformaticsÂ
1.5.1. Displaying Biological SequencesÂ
1.5.2. Displaying Biological StructuresÂ
1.5.2.1. Visualization ToolsÂ
1.5.2.2. Rendering ToolsÂ
1.5.3. User Interface in Bioinformatics ApplicationsÂ
1.5.4. Information Architectures for Displays in BioinformaticsÂ
1.6. Statistics for ComputingÂ
1.6.1. Statistical Concepts for Computing in BioinformaticsÂ
1.6.2. Use Case: MARN MicroarraysÂ
1.6.3. Imperfect Data. Errors in statistics: Randomness, Approximation, Noise and AssumptionsÂ
1.6.4. Error Quantification: Precision and SensitivityÂ
1.6.5. Clustering and ClassificationÂ
1.7. Data MiningÂ
1.7.1. Mining and Data Computing MethodsÂ
1.7.2. Infrastructure for Data Mining and ComputingÂ
1.7.3. Pattern Discovery and RecognitionÂ
1.7.4. Machine Learning and New ToolsÂ
1.8. Genetic Pattern MatchingÂ
1.8.1. Genetic Pattern MatchingÂ
1.8.2. Computational Methods for Sequence AlignmentsÂ
1.8.3. Pattern Matching ToolsÂ
1.9. Modelling and SimulationÂ
1.9.1. Use in the Pharmaceutical Field: Drug DiscoveryÂ
1.9.2. Protein Structure and Systems BiologyÂ
1.9.3. Available Tools and FutureÂ
1.10. Collaboration and Online Computing ProjectsÂ
1.10.1. Grid ComputingÂ
1.10.2. Standards and Rules Uniformity, Consistency and InteroperabilityÂ
1.10.3. Collaborative Computing ProjectsÂ
Module 2. Biomedical DatabasesÂ
2.1. Biomedical DatabasesÂ
2.1.1. Biomedical DatabasesÂ
2.1.2. Primary and Secondary DatabasesÂ
2.1.3. Major DatabasesÂ
2.2. DNA DatabasesÂ
2.2.1. Genome DatabasesÂ
2.2.2. Gene DatabasesÂ
2.2.3. Mutations and Polymorphisms DatabasesÂ
2.3. Protein DatabasesÂ
2.3.1. Primary Sequence DatabasesÂ
2.3.2. Secondary Sequence and Domain DatabasesÂ
2.3.3. Macromolecular Structure DatabasesÂ
2.4. Omics Projects DatabasesÂ
2.4.1. Genomics Studies DatabasesÂ
2.4.2. Transcriptomics Studies DatabasesÂ
2.4.3. Proteomics Studies DatabasesÂ
2.5. Genetic Diseases Databases. Personalized and Precision MedicineÂ
2.5.1. Genetic Diseases DatabasesÂ
2.5.2. Precision Medicine. The Need to Integrate Genetic DataÂ
2.5.3. Extracting Data from OMIMÂ
2.6. Self-Reported Patient RepositoriesÂ
2.2.1. Secondary Data UseÂ
2.6.2. Patients' Role in Deposited Data ManagementÂ
2.6.3. Repositories of Self-Reported Questionnaires. Examples:Â
2.7. Elixir Open DatabasesÂ
2.7.1. Elixir Open DatabasesÂ
2.7.2. Databases Collected on the Elixir PlatformÂ
2.7.3. Criteria for Choosing between DatabasesÂ
2.8. Adverse Drug Reactions (ADRs) DatabasesÂ
2.8.1. Pharmacological Development ProcessesÂ
2.8.2. Adverse Drug Reaction Reporting
2.8.3. Adverse Reaction Repositories at European and International Levels
2.9. Research Data Management Plans. Data to be Deposited in Public DatabasesÂ
2.9.1. Data Management PlansÂ
2.9.2. Data Custody in ResearchÂ
2.9.3. Data Entry in Public DatabasesÂ
2.10. Clinical Databases. Problems with Secondary Use of Health DataÂ
2.10.1. Medical Record RepositoriesÂ
2.10.2. Data EncryptionÂ
2.10.3. Access to Health Data. Legislation
Module 3. Big Data in Medicine: Massive Medical Data ProcessingÂ
3.1. Big Data in Biomedical ResearchÂ
3.1.1. Data Generation in BiomedicineÂ
3.1.2. High Performance (High-throughput technology)Â
3.1.3. Uses of High-Throughput Data. Hypotheses in the Age of Big DataÂ
3.2. Data Pre-Processing in Big DataÂ
3.2.1. Data Pre-ProcessingÂ
3.2.2. Methods and ApproachesÂ
3.2.3. Problems with Data Pre-Processing in Big DataÂ
3.3. Structural GenomicsÂ
3.3.1. Sequencing the Human GenomeÂ
3.3.2. Sequencing vs ChipsÂ
3.3.3. Variant DiscoveryÂ
3.4. Functional GenomicsÂ
3.4.1. Functional NotationÂ
3.4.2. Mutation Risk PredictorsÂ
3.4.3. Association Studies in GenomicsÂ
3.5. TranscriptomicsÂ
3.5.1. Techniques to Obtain Massive Data in Transcriptomics: RNA-seqÂ
3.5.2. Data Normalization in TranscriptomicsÂ
3.5.3. Differential Expression StudiesÂ
3.6. Interactomics and EpigenomicsÂ
3.6.1. The Role of Cromatine in Gene ExpressionÂ
3.6.2. High-Throughput Studies in InteractomicsÂ
3.6.3. High-Throughput Studies in EpigeneticsÂ
3.7. ProteomicsÂ
3.7.1. Analysis of Mass Spectrometry DataÂ
3.7.2. Post-Translational Modifications StudyÂ
3.7.3. Quantitative ProteomicsÂ
3.8. Enrichment and Clustering TechniquesÂ
3.8.1. Contextualizing ResultsÂ
3.8.2. Clustering Algorithms in Omics TechniquesÂ
3.8.3. Repositories for Enrichment: Gene Ontology and KEGGÂ
3.9. Applying Big Data to Public HealthÂ
3.9.1. Discovery of New Biomarkers and Therapeutic TargetsÂ
3.9.2. Risk PredictorsÂ
3.9.3. Personalized MedicineÂ
3.10. Big Data Applied to MedicineÂ
3.10.1. Potential for Diagnostic and Preventive AssistanceÂ
3.10.2. Use of Machine Learning Algorithms in Public HealthÂ
3.10.3. The Problem of PrivacyÂ
A program designed for you to discover new biomarkers and therapeutic targets, thanks to the application of Big Data" Â Â
Postgraduate Diploma in Bioinformatics and Big Data in Medicine.
Bioinformatics and big data are areas in constant evolution that are becoming indispensable tools in research and medicine. In this context, the Postgraduate Diploma in Bioinformatics and Big Data in Medicine designed by TECH Global University is a unique opportunity for those who wish to deepen their knowledge of these disciplines and their application in the field of health. This graduate program focuses on the study of bioinformatics and big data, providing participants with the skills and knowledge necessary to work in the healthcare industry and biomedical research. Through the Postgraduate Diploma in Bioinformatics and Big Data in Medicine, they will be able to acquire comprehensive training in the analysis of large biological datasets and the application of data mining techniques to extract useful information.
This postgraduate program offered by TECH, is particularly relevant in a context where precision medicine and personalized therapy are becoming increasingly important. The use of bioinformatics and big data tools is fundamental to be able to carry out a more personalized approach in disease treatment and prevention. If you are passionate about the world of research and precision medicine, enroll in our Postgraduate Diploma in Bioinformatics and Big Data in Medicine!