Big Data Fundamentals & Applications in Bioinformatics

  Course
Mode: On Campus
Language English
Duration 3 weeks, 60 contact hours
Fees €2,500 /student
Campus Murcia

Services provided:
1 Professor/tutor for free Professor/tutor for free
Accommodation (triple or double room upon availability)
Breakfast and lunch (excluded weekends)
Group airport transfer service (Alicante or Murcia San Javier)
Bus ticket  (Murcia city)
Teaching materials
UCAM welcome pack - Murcia city center tour
Objetives
To explore techniques and tools for interpreting and analyzing large volumes of data
To study and analyze different hardware architectures in Big Data environments
To analyze and understand different strategies for cleaning, modeling and analyzing data from the Big Data perspective
To learn security and privacy techniques applied to Big Data
To learn about real problems where the problem of large volumes of data is present, especially in Bioinformatics
SCHEDULE
WEEK 1
Session 1: Introduction to Big Data (Dr. Andrés Muñoz) What is Big Data? Datification The value of data Big Data examples and success stories Big Data challenges Data Visualization in Big Data              
Session 2: Big Data technologies (Dr. Andrés Muñoz) Hadoop Map-Reduce Spark Latest technologies                  
Session 3: Hands-on Session on Big Data technologies (Dr. Andrés Muñoz) Lab session with small exercises on Hadoop Projectors Digital conference platforms                    
Session 4: Addressing the Challenge of Securizing Big Data / Interface and Costs of Big Data (Dr. Fernando Pereñíguez / Dr. Joaquín Lasheras) Security and Big Data Why security is necessary in Big Data? Security Risks in the Big Data Era The necessary basic security services Overview of existing solutions Interfaces in Big Data Need for a good visualization Good practices in visualization Tools Cost in Big data The value of the data Who is it addressed to? Providers
Session 5: Company Visit I (Dr. Andrés Muñoz / / Dr. Joaquín Lasheras)      
SCHEDULE
WEEK 2
Session 1: The landscape of HPC platforms for the Big data challenge. (Dr. José Luis Abellán) Introduction to computing platforms Current landscape of supercomputers Future trends in developing computer architectures    
Session 2: Graphics supercomputer for big data era. (Dr. José María Cecilia) Introduction to Graphics Processing Units General purpose on Graphics Processing Units Application examples    
Session 3: Towards data processing in Big Data (Dra. Raquel Martínez) Introduction to Intelligent Data Analysis What is data preprocessing? Important tasks in data preprocessing Techniques from data preprocessing Examples of application
Session 4: (All faculties) Laboratory exercise 1. Video signals and formats (intermediate Laboratory exercise 2. Video cameras and mixers (intermediate Laboratory exercise 3. Displays and conference rooms (intermediate    
Session 5: (Jorge Hernández-Bellot) Company Visit II (Auvycom)        
SCHEDULE
WEEK 3
Session 1: Introduction to Big Data in Structural Bioinformatics and Drug Discovery (Dr. Horacio Pérez Sánchez) What is Structural Bioinformatics? What is Computational Chemistry? Need of HPC in Structural Bioinformatics and Computational Chemistry Success cases Technology Transfer State of the art and future perspectives
Session 2: Hands on session: Big Data in Structural Bioinformatics and Drug Discovery (I). (Helena den Haan) Virtual Screening of Chemical databases: general background Structure based approaches in Virtual screening        

Contact Us

International Admissions Office

 

(+34) 968 278 786

 

admissions@ucam.edu

 

international.ucam.edu

Teaching Staff