Course guide of Fundamentals of Computer Science for Biology (2001113)
Grado (bachelor's degree)
Branch
Module
Subject
Year of study
Semester
ECTS Credits
Course type
Teaching staff
Theory
- Rafael Alcalá Fernández. Grupo: C
- Alberto Luis Fernández Hilario. Grupo: B
- Francisco Javier García Castellano. Grupos: A y D
Practice
- Rafael Alcalá Fernández Grupos: 10, 11, 12 y 9
- Manuel Chica Serrano Grupos: 5 y 6
- Waldo Fajardo Contreras Grupos: 1, 2, 3 y 4
- Ignacio Javier Pérez Gálvez Grupos: 13, 14, 15 y 16
- Isaac Triguero Velázquez Grupos: 7 y 8
Timetable for tutorials
Rafael Alcalá Fernández
EmailAlberto Luis Fernández Hilario
EmailFrancisco Javier García Castellano
EmailManuel Chica Serrano
EmailWaldo Fajardo Contreras
EmailIgnacio Javier Pérez Gálvez
EmailIsaac Triguero Velázquez
EmailPrerequisites of recommendations
High school mathematics is recommended.
Basic use of computer systems.
Some minor programming skills could be necessary.
In the case of using AI tools for the development of the subject, the student must adopt an ethical and responsible use of them. The recommendations contained in the document “Recommendations for the use of artificial intelligence in the UGR” published in this location must be followed: https://ceprud.ugr.es/formacion-tic/inteligencia-artificial/recomendaciones-ia#contenido0
Brief description of content (According to official validation report)
- Tools for work and communication: Operating systems, ofimatics, thematic dictionaries, Image processing, e-learning platforms, and presentations.
- Information search: browsers, databases, university libraries.
- Scientific/technical software: Data processing, Mathematics, Simulation, Cartography.
- Introduction to programming: applications, programming, and statistics with Python.
General and specific competences
General competences
- CG01. Organisational and planning skills
- CG02. Teamwork
- CG03. Applying knowledge to problem solving
- CG04. Capacity for analysis and synthesis
- CG05. Knowledge of a foreign language
- CG07. Informatic knowledge regarding the field scope
Specific competences
- CE25. Design models of biological processes
- CE36. Implantar y desarrollar sistemas de gestión relacionados con la Biología
- CE41. Manejar las bases de datos y programas informáticos que pueden emplearse en el ámbito de Ciencias de la Vida
- CE77. Knowing computer science applied to Biology
Objectives (Expressed as expected learning outcomes)
- Know and handle some work and communication tools: Operating systems, office software, and thematic dictionaries.
- Know and handle software for image processing, e-learning platforms, and presentations.
- Know and perform information searches using browsers, databases, and university libraries.
- Know and handle some scientific/technical software: Data processing, Mathematics, Simulations, or Cartography, among others.
- Design and implement simple computer programs and know how to apply them to solve specific problems in biology.
- Solve statistical problems with a programming language such as Python.
Detailed syllabus
Theory
- Introduction to Computer Science
- Representation of information
- Databases
- Programming fundamentals
- Programming fundamentals in Python
- Basic data types
- Control structures
- Advanced data types
- Introduction to bioinformatics
Practice
Seminars / Workshops:
- Ofimatics skills.
- Python applications.
Laboratory practices:
- Spreadsheets. Charts.
- Databases.
- Basic programming in Python
Bibliography
Basic reading list
-
Allesina, S.; Wilmes, M. 2019. Computing Skills for Biologists: A Toolbox. Princeton University Press
-
Fox, R. 2013. Information Technology. Chapman and Hall
-
Beekman, G. 2009. Tomorrow's technology and you. Prentice Hall.
-
Arias-Silva, N. 2018. Office 365 essentials: get up and running with the fundamentals of Office 365. Packt Publishing
-
Thorsten Altenkirch and Isaac Triguero. Complete book on Python Programming: Conceptual Programming with Python. 1st Edition, University of Nottingham. 30th September 2019, Paperback: ISBN 978-0-244-82276-7; http://conceptual-programming.com/
-
Ryan, M. 2018. Python Fundamentals. Packt Publishing.
Complementary reading
-
Youens-Clark, K. 2021. Mastering Python for bioinformatics: how to write flexible, documented, tested Python code for research computing. O'Reilly Media
Recommended links
Python. https://www.python.org/doc/
W3Schools: it provides extensive tutorials and documentation for learning Python, covering a wide range of topics from basic syntax to advanced web development with Python. https://w3schools.com/python/
PRADO teaching platform. https://prado.ugr.es
Microsoft 365 help & learning. https://support.microsoft.com/en-us/microsoft-365
OpenOffice documentation. https://wiki.openoffice.org/wiki/Documentation
Codedex.io: it provides an easy and entertaining approach to learning Python by solving different levels and tasks in a gamification way https://www.codedex.io/python ;
CodeCombat: it offers an interactive platform where users can learn Python by solving coding challenges within a game-like environment. https://codecombat.com/play
Programming for Lovers. https://programmingforlovers.com/
Studio Code. https://studio.code.org/
Teaching methods
- MD01. Lección magistral/expositiva
- MD02. Sesiones de discusión y debate
- MD03. Resolución de problemas y estudio de casos prácticos
- MD04. Prácticas de laboratorio y/o clínicas y/o talleres de habilidades
- MD06. Prácticas en sala de informática
- MD07. Seminarios
- MD10. Realización de trabajos en grupo
- MD11. Realización de trabajos individuales
Assessment methods (Instruments, criteria and percentages)
Ordinary assessment session
Continuous evaluation:
Formative activities | Weight |
---|---|
Theory | 50% |
Practice | 50% |
- Theory (50%) [S1]: There will be three tests (20%, 15% and 15% of the evaluation, respectively). The first one will occur after Lesson 3, the second in the middle of the Python lessons, and the third will take place on the date established by the grade for the computer science exam in the ordinary examination. These tests enable a continuous evaluation of the theory part of the course.
- Practice (50%) [SE2, SE3, SE4]: Participation and evaluation of laboratory activities, seminars, and supervised work will be comprised of participation and assessment.
The details of this ponderation are as follows:
- SE1: Evaluation of the acquired level through theory classes: 50% (Theory)
- SE2: Evaluation of the acquired level through laboratory activities: 20% (Practice)
- SE3: Evaluation of the acquired level through seminars and guided work: 20% (Practice)
- SE4: Evaluation of assistance, attitude, and participation in activities: 10% (Practice)
To pass the course, it will be necessary to obtain a final mark of 5 (out of 10) or higher. A minimum mark of 4 is required in both theory and practice. If that is not met, the final evaluation for the course will be the minimum between 4.9 and the student's marks.
Extraordinary assessment session
- The student will take an exam including theory and practice. All the lessons and activities in the syllabus will be included in the exam.
- Students not attending the practical part of the exam will maintain the marking they obtained during the ordinary session in this part.
- The final mark of the course will be the sum of each part with a weight of 50% each.
- To pass the course, it is necessary to obtain a mark of 5 (out of 10) or higher. It is also mandatory to obtain 4 or more in each part (theory and practice), otherwise, the final mark for the course will be the minimum between 4.9 and the student's marks.
Single final assessment
- The students will take two tests: one to evaluate their knowledge regarding the theory aspects of the course, and another to evaluate acquired competencies related to the practical part.
- The final mark will be the average of both marks. To pass the course, it is necessary to obtain a mark of 5 (out of 10) or higher. It is also mandatory to obtain 4 or more in each part (theory and practice), otherwise, the final mark for the course will be the minimum between 4.9 and the student's marks.
Additional information
Following the recommendations of CRUE and the Secretariat of Inclusion and Diversity of the UGR, the mechanisms for the acquisition and assessment of competencies included in this syllabus will be applied according to the design principle for all people, facilitating learning and demonstration of knowledge according to the needs and functional diversity of the students.
The platform of support resources for teaching (PRADO) at https://prado.ugr.es
Información de interés para estudiantado con discapacidad y/o Necesidades Específicas de Apoyo Educativo (NEAE): Gestión de servicios y apoyos (https://ve.ugr.es/servicios/atencion-social/estudiantes-con-discapacidad).