Guías Docentes Electrónicas
1. General information
Course:
BIOINFORMATICS AND BIG DATA
Code:
60622
Type:
CORE COURSE
ECTS credits:
6
Degree:
402 - UNDERGRADUATE DEGREE PROGRAMME IN BIOTECHNOLOGY
Academic year:
2022-23
Center:
601 - E.T.S. AGRICULTURAL ENGINEERS AND MOUNTS AB
Group(s):
10 
Year:
3
Duration:
First semester
Main language:
Spanish
Second language:
Use of additional languages:
English Friendly:
Y
Web site:
Bilingual:
N
Lecturer: LUIS DE LA OSSA JIMENEZ - Group(s): 10 
Building/Office
Department
Phone number
Email
Office hours
ESII / 0.A.12
SISTEMAS INFORMÁTICOS
2413
luis.delaossa@uclm.es

2. Pre-Requisites
Not established
3. Justification in the curriculum, relation to other subjects and to the profession
Not established
4. Degree competences achieved in this course
Course competences
Code Description
CB01 Prove that they have acquired and understood knowledge in a subject area that derives from general secondary education and is appropriate to a level based on advanced course books, and includes updated and cutting-edge aspects of their field of knowledge.
CB02 Apply their knowledge to their job or vocation in a professional manner and show that they have the competences to construct and justify arguments and solve problems within their subject area.
CB03 Be able to gather and process relevant information (usually within their subject area) to give opinions, including reflections on relevant social, scientific or ethical issues.
CB04 Transmit information, ideas, problems and solutions for both specialist and non-specialist audiences.
CB05 Have developed the necessary learning abilities to carry on studying autonomously
CE14 Know the handling of biological, biochemical and genetic databases.
CG01 Organizational and planning skills.
CG02 Capacity for analysis and synthesis.
CG03 Ability to work in multidisciplinary teams collaboratively and with shared responsibility.
CT01 Know a second foreign language.
CT02 Know and apply the Information and Communication Technologies.
CT03 Use correct oral and written communication.
CT04 Know the ethical commitment and professional deontology.
5. Objectives or Learning Outcomes
Course learning outcomes
Description
Additional outcomes
Description
6. Units / Contents
  • Unit 1:
  • Unit 2:
    • Unit 2.1:
    • Unit 2.2:
    • Unit 2.3:
    • Unit 2.4:
  • Unit 3:
    • Unit 3.1:
    • Unit 3.2:
    • Unit 3.3:
  • Unit 4:
    • Unit 4.1:
    • Unit 4.2:
    • Unit 4.3:
    • Unit 4.4:
    • Unit 4.5:
  • Unit 5:
    • Unit 5.1:
    • Unit 5.2:
    • Unit 5.3:
    • Unit 5.4:
  • Unit 6:
    • Unit 6.1:
    • Unit 6.2:
    • Unit 6.3:
7. Activities, Units/Modules and Methodology
Training Activity Methodology Related Competences (only degrees before RD 822/2021) ECTS Hours As Com Description
Class Attendance (theory) [ON-SITE] Lectures CB02 CE14 CT02 1 25 N N
Class Attendance (practical) [ON-SITE] Problem solving and exercises CB02 CB03 CB05 CE14 CT02 0.8 20 N N
Class Attendance (practical) [ON-SITE] Practical or hands-on activities CB01 CB02 CB03 CB04 CB05 CE14 CG01 CG03 CT01 CT02 0.4 10 N N
Practicum and practical activities report writing or preparation [OFF-SITE] Guided or supervised work CB01 CB02 CB03 CB04 CB05 CE14 CG01 CG02 CG03 CT01 CT02 CT03 CT04 0.8 20 Y Y
Progress test [ON-SITE] Assessment tests CB01 CB03 CE14 CG02 CT03 0.16 4 Y N
Group tutoring sessions [ON-SITE] Group tutoring sessions CB04 CT04 0.04 1 N N
Study and Exam Preparation [OFF-SITE] Self-study CB02 CB03 CB05 CE14 CG01 CG02 2.6 65 N N
Project or Topic Presentations [ON-SITE] Individual presentation of projects and reports CB02 CB03 CB04 CB05 CG02 CG03 CT02 CT03 CT04 0.2 5 Y N
Total: 6 150
Total credits of in-class work: 2.6 Total class time hours: 65
Total credits of out of class work: 3.4 Total hours of out of class work: 85

As: Assessable training activity
Com: Training activity of compulsory overcoming (It will be essential to overcome both continuous and non-continuous assessment).

8. Evaluation criteria and Grading System
Evaluation System Continuous assessment Non-continuous evaluation * Description
Progress Tests 65.00% 65.00%
Practicum and practical activities reports assessment 15.00% 15.00%
Practical exam 20.00% 20.00%
Total: 100.00% 100.00%  
According to art. 4 of the UCLM Student Evaluation Regulations, it must be provided to students who cannot regularly attend face-to-face training activities the passing of the subject, having the right (art. 12.2) to be globally graded, in 2 annual calls per subject , an ordinary and an extraordinary one (evaluating 100% of the competences).

Evaluation criteria for the final exam:
  • Continuous assessment:
    Evaluation criteria not defined
  • Non-continuous evaluation:
    Evaluation criteria not defined

Specifications for the resit/retake exam:
Evaluation criteria not defined
Specifications for the second resit / retake exam:
Evaluation criteria not defined
9. Assignments, course calendar and important dates
Not related to the syllabus/contents
Hours hours
Progress test [PRESENCIAL][Assessment tests] 4
Group tutoring sessions [PRESENCIAL][Group tutoring sessions] 1
Study and Exam Preparation [AUTÓNOMA][Self-study] 65

Unit 1 (de 6):
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 1

Unit 2 (de 6):
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 6
Class Attendance (practical) [PRESENCIAL][Problem solving and exercises] 4
Class Attendance (practical) [PRESENCIAL][Practical or hands-on activities] 2
Practicum and practical activities report writing or preparation [AUTÓNOMA][Guided or supervised work] 5

Unit 3 (de 6):
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 2
Class Attendance (practical) [PRESENCIAL][Problem solving and exercises] 4
Class Attendance (practical) [PRESENCIAL][Practical or hands-on activities] 2
Practicum and practical activities report writing or preparation [AUTÓNOMA][Guided or supervised work] 5

Unit 4 (de 6):
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 6
Class Attendance (practical) [PRESENCIAL][Problem solving and exercises] 4
Class Attendance (practical) [PRESENCIAL][Practical or hands-on activities] 2
Practicum and practical activities report writing or preparation [AUTÓNOMA][Guided or supervised work] 5

Unit 5 (de 6):
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 5
Class Attendance (practical) [PRESENCIAL][Problem solving and exercises] 4
Class Attendance (practical) [PRESENCIAL][Practical or hands-on activities] 2
Practicum and practical activities report writing or preparation [AUTÓNOMA][Guided or supervised work] 5

Unit 6 (de 6):
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 5
Class Attendance (practical) [PRESENCIAL][Problem solving and exercises] 4
Class Attendance (practical) [PRESENCIAL][Practical or hands-on activities] 2
Practicum and practical activities report writing or preparation [AUTÓNOMA][Guided or supervised work] 5

Global activity
Activities hours
10. Bibliography and Sources
Author(s) Title Book/Journal Citv Publishing house ISBN Year Description Link Catálogo biblioteca
Documentación de Pandas http://pandas.pydata.org/  
Documentación Matplotlib http://matplotlib.org/  
Introducción a la programación con Python https://www.u-cursos.cl/ingenieria/2011/2/CC3501/1/material_docente/bajar?id_material=381752  
Jake VanderPlas Python Data Science Handbook O'Reilly Media, Inc. 9781491912058 2016 https://jakevdp.github.io/PythonDataScienceHandbook/  
Ravishankar Chityala Image Processing and Acquisition using Python Chapman & Hall/CRC 978-1466583757  
Sebastian Bassi Python for Bioinformatics (Chapman & Hall/CRC Computational Biology Series) 978-1138035263 2018  
Tim J. Stevens, Wayne Boucher Python Programming for Biology: Bioinformatics and Beyond Cambridge University Press 978-0521720090 2015  
William W. Cohen A Computer Scientists Guide to Cell Biology Springer 978-0-387-48275-0 2007  



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