Course guide of Fundamentals of Computer Science for Biology (2001113)

Curso 2022/2023
Approval date: 14/06/2022

Grado (bachelor's degree)

Bachelor'S Degree in Biology

Branch

Sciences

Module

Materias Básicas Instrumentales para la Biología

Subject

Informática

Year of study

1

Semester

1

ECTS Credits

6

Course type

Core course

Teaching staff

Theory

  • Jesús Alcalá Fernández. Grupo: D
  • Rafael Alcalá Fernández. Grupo: C
  • Alberto Luis Fernández Hilario. Grupo: B
  • Salvador García López. Grupo: A

Practice

  • Jesús Alcalá Fernández Grupo: 15
  • Rafael Alcalá Fernández Grupos: 11, 12 y 9
  • Manuel Jesús Cobo Martín Grupos: 10, 16 y 2
  • Alberto Luis Fernández Hilario Grupo: 6
  • Francisco Javier García Castellano Grupos: 13 y 14
  • Salvador García López Grupos: 1, 3 y 4
  • Miguel José Molina Solana Grupos: 5, 7 y 8

Timetable for tutorials

Jesús Alcalá Fernández

Email
  • First semester
    • Monday
      • 09:30 a 11:00 (M1 (F Ciencias))
      • 12:00 a 13:30 (M1 (F Ciencias))
    • Tuesday de 16:00 a 17:00 (M1 (F Ciencias))
    • Friday
      • 10:00 a 11:00 (M1 (F Ciencias))
      • 12:00 a 13:00 (M1 (F Ciencias))
  • Second semester
    • Monday de 10:00 a 13:00 (D16 Etsiit)
    • Thursday de 10:00 a 13:00 (D16 Etsiit)

Rafael Alcalá Fernández

Email
  • First semester
    • Monday
      • 08:30 a 09:00 (Mect (Fciencias))
      • 12:00 a 13:30 (Mect (Fciencias))
    • Tuesday de 12:00 a 13:30 (Mect (Fciencias))
    • Wednesday
      • 09:30 a 10:00 (Mect (Fciencias))
      • 12:30 a 14:00 (D21 Etsiit)
  • Second semester
    • Monday de 10:00 a 13:00 (D21 Etsiit)
    • Wednesday de 10:00 a 13:00 (D21 Etsiit)

Alberto Luis Fernández Hilario

Email
  • First semester
    • Tuesday de 12:00 a 14:00 (Mect (F Ciencias))
    • Wednesday de 11:00 a 13:00 (Mect (F Ciencias))
    • Thursday de 11:00 a 13:00 (Mect (F Ciencias))
  • Second semester
    • Wednesday de 10:00 a 13:00 (D16 Etsiit)
    • Thursday de 10:00 a 13:00 (D16 Etsiit)

Salvador García López

Email
  • First semester
    • Monday de 10:30 a 12:00 (Mect (F Cienicas))
    • Tuesday de 10:00 a 12:00 (Mect (F Ciencias))
    • Wednesday de 10:00 a 12:00 (Mect (F Cienicas))
  • Second semester
    • Monday de 13:00 a 13:30 (D26 Etsiit)
    • Tuesday de 09:00 a 12:00 (D26 Etsiit)

Manuel Jesús Cobo Martín

Email
  • First semester
    • Tuesday de 16:00 a 19:00 (Fo15 Etsiit)
    • Thursday de 15:30 a 17:30 (Fo15 Etsiit)
    • Friday de 16:30 a 17:30 (Fo15 Etsiit)
  • Second semester
    • Wednesday
      • 10:00 a 14:30 (Fo15 Etsiit)
      • 15:30 a 17:00 (Fo15 Etsiit)

Francisco Javier García Castellano

Email
  • First semester
    • Tuesday de 10:00 a 12:00 (M4 (F Cienicas))
    • Thursday de 00:00 a 13:00 (M4 (F Cienicas))
    • Friday de 12:00 a 13:00 (Bo (Fcyd))
  • Second semester
    • Tuesday de 10:00 a 13:00 (M4 (F Cienicas))
    • Wednesday de 10:00 a 13:00 (M4 (F Cienicas))

Miguel José Molina Solana

Email
  • First semester
    • Thursday
      • 10:30 a 11:30 (Fo17 Etsiit)
      • 12:30 a 13:30 (Fo17 Etsiit)
      • 14:30 a 15:30 (Fo17 Etsiit)
    • Friday de 10:30 a 13:30 (Fo17 Etsiit)
  • Second semester
    • Monday de 11:30 a 13:30 (Fo17 Etsiit)
    • Tuesday de 11:30 a 13:30 (Fo17 Etsiit)
    • Wednesday de 11:30 a 13:30 (Fo17 Etsiit)

Prerequisites of recommendations

High school mathemathics are recommended.

Brief description of content (According to official validation report)

  • Tools for work and communication: Operating systems, ofimatics, thematic dictionaries, Image processing, e-learning platforms, 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, ofimatics, 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, Cartography.
  • 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

  1. Introduction to Computer Science
  2. Representation of information
  3. Databases
  4. Programming fundamentals
  5. Programming fundamentals in python
  6. Basic data types
  7. Control structures
  8. Advanced data types
  9. Introduction to bioinformatics

Practice

Seminars / Workshops:

  • Ofimatics skills.
  • Python applications.

Laboratory practices:

  1. Spreadsheets. Charts.
  2. Databases.
  3. Basic programming in python

Bibliography

Basic reading list

Complementary reading

Recommended links

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 happen after lesson 3 (4th November), the second in the middle of python lessons (2nd December) and the third one after all lessons (20th December). These tests enable a continuous evaluation of the theory part of the course.
  • Practice (50%) [SE2, SE3, SE4]: It will comprise participation and evaluation of laboratory activities, seminars and supervised works.

The detail of this ponderation is 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)

It will be necessary to obtain a final mark of 5 (out of 10) or higher to pass the course. A minimum mark of 4 in both theory and practice is required. If that is not met, the final evaluation for the course will be the minimum between 4.9 and the student 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 marks.

Single final assessment

  • The students will take two tests: one to evaluate their knowledge regarding the theory aspects of the course, and another for evaluating acquired competences 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 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 competences 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.

Platform of support resources for teaching (PRADO2) at https://prado.ugr.es