Bioinformatics II

Objectives

This aim of this course is to use bioinformatic tools more deeply, covering sequence alignments, evolution and phylogeny, and genome wide association studies. Moreover, the students will have to solve biological problems using bioinformatic tools and programming.

Learning outcomes

1. Aplica els coneixements de la bioinformàtica a problemes i exercicis relacionats amb l'evolució i la filogènia.
2. Prediu gens i regions promotores amb l'ajut d'eines bioinformàtiques.
3. Utilitza les eines bioinformàtiques avançades per resoldre problemes correctament.
4. Es mou amb desimboltura en l'ús general de les TIC i especialment en els entorns tecnològics propis de l'àmbit professional.
5. Comprèn missatges orals i escrits de diferent tipologia de forma completa expressats en les llengües pròpies i en anglès.
6. Elabora informes i documents escrits (principalment de caràcter tècnic) amb correcció ortogràfica i gramatical en català, castellà i anglès.

Competencies

General skills

• Combine scientific knowledge with technical skills and technological resources to deal with problems in professional practice.

Specific skills

• Apply the tools of mathematics, statistics, computer science, and the principles of physics and chemistry in the context of biotechnology.
• Search, obtain and interpret information in the main biological and bibliographic databases using bioinformatics tools, and use programming techniques for problem solving.

Basic skills

• Students can apply their knowledge to their work or vocation in a professional manner and have competencies typically demonstrated through drafting and defending arguments and solving problems in their field of study.
• Students have developed the learning skills necessary to undertake further studies with a high degree of independent learning.

Core skills

• Be a critical thinker before knowledge in all its dimensions. Show intellectual, cultural and scientific curiosity and a commitment to professional rigour and quality.
• Display professional skills in complex multidisciplinary contexts, working in networked teams, whether face-to-face or online, through use of information and communication technology.
• Use oral, written and audiovisual forms of communication, in one's own language and in foreign languages, with a high standard of use, form and content.

Content

1. Sequence alignments. Fundamentals of sequence alignments. Pairwise sequence alignments. Multiple sequence alignments
2. Evolution and phylogeny
3. Sequence and data analysis using programming
4. Genome wide association studies

Evaluation

• Partial exam 1: 25 % of the overall grade. It can be reassessed. RA1, RA3
• Partial exam 2: 25 % of the overall grade. It can be reassessed. RA2, RA6
• Partial exam 3: 25 % of the overall grade. It can be reassessed. RA2, RA6
• Exercises and practicals during the course. 25% of the overall grade. These activities can not be reassessed. RA1, RA2, RA3, RA4, RA8

To pass the subject it is necessary to obtain a minimum score of 5 for each partial exam and an overall grade of 5. Partial exams can be reassessed.

The mark obtained in the reassessment will substitute the mark obtained in the first assessment for the partial exams.

All sessions are mandatory. If a student does not attend to a session without any justified reason, there will be a penalisation of 0,5 points of the final score for each failed session.

Total or partial copy and/or plagiarism will imply a failure in the subject with a final grade of zero points and no access to retake exams.

Methodology

The sessions will combine theoretical concepts and hands-on-sessions. It is necessary that the student brings a laptop in order to follow the sessions.

Bibliography

Bibliography

• Baxevanis, A. D., Francis, B.F. (2005). Bioinformatics: A practical guide to the analysis of genes and proteins (3 ed.). Wiley.
• Model, M. L., Tisdall, J. (2010). Bioinformatics programming using Python: Practical programming for biological data. O'Reilly.
• Mount, D. W. (2001). Bioinformatics: Sequence and genome analysis. Cold Spring Harbour.
• Stevens, T. J. (MRC Laboratory of Molecular Biology), Boucher, W. (University of Cambridge) (2014). Python programming for biology, bioinformatics, and beyond. Cambridge University Press.