Thanks to this Postgraduate certificate you will be able to advance your career immediately by incorporating the most advanced techniques in Bioinformatics and Data Automation into your professional work"

Bioinformatics is a discipline that has developed in collaboration with other areas of knowledge, such as Molecular Biology. As the virtues of data management at different scales have been exploited, the practice of this discipline has acquired a series of specifications that distinguish it from other branches of computer engineering: a specific way of visualizing biological data, a specific way of managing such data, a strict life cycle for bioinformatics data, and so on.

The Postgraduate certificate in Bioinformatics Computing offered by TECH covers all this and more, with a program that delves into aspects such as the visualization of biological sequences, data mining and genetic pattern matching, among many others. In this way, this degree will show the student the relationship between Computing and the current scientific and clinical scene.

This training is 100% online. Therefore, the student will be able to study in a comprehensive way about information architectures for bioinformatics, search engines, applications in the pharmaceutical or genetic field at a distance. The interested person will be supported not only by the prestigious group of specialists who have designed the program, but also by a variety of very useful virtual tools with a large amount of information that will support both the course and the professional practice.

Stand out in this interdisciplinary sector and support different areas of health and knowledge thanks to the innovative knowledge you will acquire with this 100% online TECH" program”

This Postgraduate certificate in Bioinformatics Computing: Medical Process Digitization and Automation contains the most complete and up-to-date program on the market. The most important features include:

• The development of case studies presented by experts in Bioinformatics Computing
• The graphic, schematic, and practical contents with which they are created, provide scientific and practical information on the disciplines that are essential for professional practice.
• Practical exercises where self-assessment can be used to improve learning.
• Its special emphasis on innovative methodologies
• Theoretical lessons, questions to the expert, debate forums on controversial topics, and individual reflection assignments
• The availability of access to content from any fixed or portable device with an Internet connection

With this degree, it deepens, with this degree, in genetic pattern matching using the data analysis of Bioinformatics"

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.

Its 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 an immersive education programmed  to learn in real situations.

The design of this program focuses on Problem-Based Learning, by means of which the professional must try to solve the different professional practice situations that are presented throughout the academic course. For this purpose, the student will be assisted by an innovative interactive video system created by renowned experts.

Statistics is an essential part of computer science and throughout this curriculum you will gain the necessary tools to identify imperfect data"

Learn about the latest news on data mining and machine learning from the best professionals"

The content of this program introduces the latest developments in the handling and management of biological data with information technologies and statistical models. Therefore, this Postgraduate certificate includes in its division and structure all the procedures, proven for their efficiency and currently used, of information flow management for biological-clinical topics. This is achieved by deepening, in turn, in the statistical techniques that comprise computation and its applications in topics such as genetics. All this content is taught completely online with a host of virtual tools that make this a complete and comprehensive course.

Get to know all the current applications of bioinformatics thanks to this carefully structured program with the latest information on this complex and exciting subject"

Module 1. Computation in Bioinformatics

1.1. Central Tenet 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 

Delve into computing and Bioinformatics and explore all the professional possibilities of this field"