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Type A
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Code |
Competences Specific | | | A7 |
Be able to search, obtain, analyse and interpret information from the main biological databases: genomic, transcriptomic, proteomic, metabolomics, taxonomic and other, as well as bibliographic data, and use basic bioinformatics tools. |
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Type B
|
Code |
Competences Transversal | | | CT1 |
Use information in a foreign language effectively. |
| | CT2 |
Managing information and knowledge through the efficient use of IT. |
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Type C
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Code |
Competences Nuclear |
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Type A
|
Code |
Learning outcomes |
| | A7 |
Use bioinformatic tools to: a) analyse the structures and sequences of proteins and nucleic acids and b) search for information in the main biological and bibliographic databases.
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Type B
|
Code |
Learning outcomes |
| | CT1 |
Use information in a foreign language effectively.
| | | CT2 |
Master the tools for managing their own identity and activities in a digital environment. (Be digital)
Search for and find information autonomously with criteria of reliability and relevance. (Search)
Organize information with appropriate tools (online and face-to-face) so that they can carry out their academic activities. (Organize)
Produce information with tools and formats appropriate to the communicative situation and with complete honesty. (Create)
Use IT to share and exchange information. (Share)
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Type C
|
Code |
Learning outcomes |
| Topic |
Sub-topic |
| 1) Introduction |
Definition and field of study.
Bioinformatics Web sites (EBI-EMBL, NCBI, Expasy).
|
| 3) Bioinformatics databases |
Bibliographic databases (PubMed, ISI Web of Knowledge), sequences databases (UniProt, GenBank). Other databases. |
| 2) Introduction to the Linux operating system and Python |
Introduction to Lynux (installing packages, terminal for simple tasks) and Python. |
| 4) Search and sequence analysis |
Concept of homology. Pair-wise alignments (Needelman-Wunsch and Smith-Waterman algorithms). Dotplot. Substitution matrices (PAM, BLOSUM). Search for similar sequences (BLAST). |
| 5) Multiple alignments and construction of phylogenetic trees |
Multiple sequence alignment programs (CLUSTAL). Databases derived from multialineaments (PROSITE). Methods of phylogenetic reconstruction. Visualization of phylogenetic trees. |
| Methodologies :: Tests |
| |
Competences |
(*) Class hours
|
Hours outside the classroom
|
(**) Total hours |
| Introductory activities |
|
2 |
1 |
3 |
| Lecture |
|
28 |
21 |
49 |
| IT-based practicals |
|
20 |
30 |
50 |
| Assignments |
|
3 |
10 |
13 |
| Collaborative work |
|
3 |
10 |
13 |
| Personal attention |
|
4 |
0 |
4 |
| |
| Practical tests |
|
2 |
16 |
18 |
| |
(*) On e-learning, hours of virtual attendance of the teacher.
(**) The information in the planning table is for guidance only and does not take into account the heterogeneity of the students. |
Methodologies
| |
Description |
| Introductory activities |
Activities designed to make contact with students, collect information from them and introduce the subject. |
| Lecture |
Description of the contents of the subject. Students' participation will be stimulated by asking questions during the class related to what is being explained and what makes them think. |
| IT-based practicals |
Practices in the computer classroom. Exercises will also be carried out using databases and internet servers. |
| Assignments |
Bibliographic search |
| Collaborative work |
group assignment. |
| Personal attention |
Resolution of doubts by emailing or face-to-face. |
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Description |
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<p>Time reserved for individual attention and doubt solving with students. Due to the health emergency, this attention can be carried out through online meetings, previously appointed by e-mail, or with other online tools.</p> |
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Methodologies |
Competences
|
Description |
Weight |
|
|
|
|
| IT-based practicals |
|
Individual resolution of a questionnaire for each topic. |
10% |
| Assignments |
|
Bibliographic search |
20% |
| Collaborative work |
|
Pyhton assignment. |
20% |
| Practical tests |
|
Theoretical-practical exam |
50% |
| Others |
|
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| |
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Other comments and second exam session |
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Second call: It is an essential requirement to present the assignments (bibliographic search and python assignment) to pass the subject. A minimum of 4.0 will be necessary in the examination (in the first and second call) will be necessary to count the score of the questionnaires. The second-chance will consist of an exam, keeping the note of the questionnaires, bibliographic search and pyhton assignment, with the same weights as in the first chance. The grades from a previous course are not kept. The exams will be held in person. In case of lockdown or mobility restrictions caused by the Covid-19 health emergency, the assessment activities, including exams, would be done online on the scheduled dates. Updated information can be found on Moodle (virtual teaching space). |
| Basic |
Gibas, Cynthia; Jambeck, Per, Developing bioinformatics computer skills, Beijing: O'Reilly, 2001
Claverie, Jean-Michel; Notredame, Cedric, Bioinformatics for dummies, New York: Wiley Pub., cop., 2007
Attwood, Teresa K.; Parry-Smith, David J., Introducción a la bioinformática, Madrid: Prentice Hall, DL, 2002
Lesk, Arthur M., Introduction to bioinformatics, Oxford: Oxford University Press, 2008
Solé-Llussà A; Casanoves M; Salvadó Z; Garcia-Vallve S; Valls C; Novo M, Annapurna expedition game: applying molecular biology tools to learn genetics., , J Bio Educ. 2019 53(5):516-523. doi:10.1080/002192
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| Complementary |
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Garcia-Vallve S & Puigbo P. Ciento cincuenta años tras el árbol de la vida. Nuevos retos sobre el origen de las especies. Revista de la SEBBM. Junio 2009. Num. 160:18-21 |
(*)The teaching guide is the document in which the URV publishes the information about all its courses. It is a public document and cannot be modified. Only in exceptional cases can it be revised by the competent agent or duly revised so that it is in line with current legislation. |
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