Study programme competencies |
Code
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Study programme competences / results
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A1 |
CE1 - Ability to know the scope of Bioinformatics and its most important aspects |
A2 |
CE2 – To define, evaluate and select the architecture and the most suitable software for solving a problem in the field of bioinformatics |
A3 |
CE3 – To analyze, design, develop, implement, verify and document efficient software solutions based on an adequate knowledge of the theories, models and techniques in the field of Bioinformatics |
A8 |
CE8 - Understanding the basis of the information of the hereditary material, its transmission, analysis and evolution |
A9 |
CE9 – To understand the benefits and the problems associated with the sequencing and the use of biological sequences, as well as knowing the structures and techniques for their processing |
B1 |
CB6 - Own and understand knowledge that can provide a base or opportunity to be original in the development and/or application of ideas, often in a context of research |
B2 |
CB7 - Students should know how to apply the acquired knowledge and ability to problem solving in new environments or little known within broad (or multidisciplinary) contexts related to their field of study |
B8 |
CG3 - Be able to work in a team, especially of interdisciplinary nature |
C6 |
CT6 - To assess critically the knowledge, technology and information available to solve the problems they face to. |
C7 |
CT7 – To maintain and establish strategies for scientific updating as a criterion for professional improvement. |
Learning aims |
Learning outcomes |
Study programme competences / results |
To know the data structures and the algorithms used for compactly storing and processing of biological sequences. |
AJ1 AJ2 AJ9
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|
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To analyze and compare the data structures and the complexity of the algorithms used. |
AJ2 AJ3
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BJ1
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CJ6 CJ7
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To understand, analyze, design and implement solutions for different fundamental problems of sequence alignment, read error correction, contig assembly, gap filling, etc. |
AJ1 AJ2 AJ3 AJ8 AJ9
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BJ1 BJ2 BJ8
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CJ6 CJ7
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To explain, analyze, design and implement solutions to the problems related with evolution, such as haplotype assembly, motif finding, permutation patterns, genomic rearrangement, etc. |
AJ1 AJ2 AJ3 AJ8 AJ9
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BJ1 BJ2 BJ8
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CJ6 CJ7
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Contents |
Topic |
Sub-topic |
Introduction to algorithms complexity analysis |
Algorithms analysis
Complexity |
Sequence pattern search |
Exact string matching methods
Approximate string matching methods
Suffix trees and suffix arrays
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Introduction to sequence compression and indexing |
Compression techniques
Indexes and self-indexes |
Applications to biological sequences |
Sequence comparison
Motif finding
Genomic rearrangements
Sequence alignment
Sequence assembly
Phylogenetic analysis |
Planning |
Methodologies / tests |
Competencies / Results |
Teaching hours (in-person & virtual) |
Student’s personal work hours |
Total hours |
ICT practicals |
A2 A3 B1 B2 B8 C7 C6 |
14 |
70 |
84 |
Mixed objective/subjective test |
A1 A2 A3 A8 A9 B2 |
3 |
0 |
3 |
Guest lecture / keynote speech |
A1 A2 A3 A8 A9 |
28 |
32 |
60 |
|
Personalized attention |
|
3 |
0 |
3 |
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(*)The information in the planning table is for guidance only and does not take into account the heterogeneity of the students. |
Methodologies |
Methodologies |
Description |
ICT practicals |
Students will complete practical exercises to develop all the knowledge acquired during lectures. |
Mixed objective/subjective test |
It consists of a written test to show that the student has acquired the knowledge and skills during lectures and practice sessions. |
Guest lecture / keynote speech |
Lectures where the course contents are exposed. Active participation will be monitored on a continuous and objective basis. |
Personalized attention |
Methodologies
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Guest lecture / keynote speech |
ICT practicals |
|
Description |
There may exist differences among the students regarding their background on algorithms and data structures. Thus, teachers will provide personalized attention for practice sessions and for the supervised project, both individual or in small groups. |
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Assessment |
Methodologies
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Competencies / Results |
Description
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Qualification
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Mixed objective/subjective test |
A1 A2 A3 A8 A9 B2 |
It will consist of a written test where the students must prove the knowledge and competences acquired during lectures and practice sessions.
To pass the course globally it is necessary to obtain in the mixed test a minimum grade of 1.5 (over 4). If that minimum grade is not achieved, the maximum grade cannot exceed 4.9 (and therefore the course is failed) |
40 |
Guest lecture / keynote speech |
A1 A2 A3 A8 A9 |
There will be a continuous and objectifiable follow-up of the active participation during the master classes, by means of exercises delivered during these classes. This part of the evaluation will not be able to be recovered in the second opportunity. |
10 |
ICT practicals |
A2 A3 B1 B2 B8 C7 C6 |
The work done by the students during practice sessions will be assessed. Students must submit and defend their work in front of the teaching staff. Submissions out of time may result in a grade penalty. |
50 |
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Assessment comments |
FIRST OPPORTUNITY: Students that do not take the written exam will obtain a grade of "Non presentado" (Absent). SECOND OPPORTUNITY: Only those students that have not passed the course in the first opportunity can be evaluated in the second opportunity. Students can recover any of the parts as follows: - ICT practicals (50%): the students can repeat the ICT practicals under the same circumpstances than in the first opportunity (those submitted out of time can obtain a maximum of 80% of the grade). Thus, in case of repeating all the assignments, the maximum grade will be 4 points.
- Written test (40%): in the same conditions as in the first opportunity.
- The grade obtained from the continuous and objective monitoring of the active participation during the lectures cannot be recovered.
- In case of not retaking one of the parts, the grade obtained in the first opportunity for that part will be kept.
- To pass the course globally it is necessary to obtain in the mixed test a minimum grade of 1.5 (over 4).
- Students that do not retake any part will obtain a grade of "Non presentado" (Absent).
ADVANCED OPPORTUNITY: The assessment for the advanced opportunity will be: 50% ICT practicals, 50% written text.
ACADEMIC DISPENSATION: Students officially enrolled part-time who have been granted an official dispensation from attending classes, as stipulated in the regulations of this University, must contact with the responsible of the course within the first two weeks to establish the conditions for submitting and defending the practical exercises and the supervised project. ACADEMIC FRAUD: The fraudulent performance of tests or evaluation activities, once verified, will directly imply the qualification of failure in the call in which it is committed: the student will be graded with "suspenso" (numerical grade 0) in the corresponding call of the academic year, whether the commission of the fault occurs in the first opportunity or in the second. For this, the student's grade will be modified in the first opportunity report, if necessary.
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Sources of information |
Basic
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Dan Gusfield (1997). Algorithms on Strings, Trees and Sequences. Cambridge University Press
Neil C. Jones, Pavel A. Pevzner (2004). An Introduction to Bioinformatics Algorithms. MIT Press
Veli Mäkinen, Djamal Belazzougui, Fabio Cunial, Alexandru I. Tomescu (2015). Genome-Scale Algorithm Design. Cambridge University Press |
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Complementary
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Enno Ohlebusch (2013). Bioinformatics Algorithms: Sequence Analysis, Genome Rearrangements, and Phylogenetic Reconstruction. Oldenbusch Verlag
A. Moffat y A. Turpin (2002). Compression and Coding Algorithms. Kluwer Academic Publishers
G. Navarro y M Raffinot (2002). Flexible Pattern Matching in Strings. Cambridge University Press
T. C. Bell, J. G. Clearly y I. H. Witten (1990). Text Compression. Prentice Hall |
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Recommendations |
Subjects that it is recommended to have taken before |
Introduction to molecular biology/614522004 | Genetics and molecular evolution/614522005 | Genomics/614522006 | Fundamentals of bioinformatics/614522008 | Introduction to programming/614522001 |
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Subjects that are recommended to be taken simultaneously |
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Subjects that continue the syllabus |
Advanced processing of biological sequences/614522020 | New trends and applications in bioinformatics and biomedical engineering/614522021 |
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Other comments |
Gender perspective: According to the different regulations applicable to university teaching, the gender perspective must be incorporated in this subject (use of non-sexist language, etc.). Work will be done to identify and modify sexist prejudices and attitudes and influence the environment to modify them and promote values of respect and equality. The aim will be to detect situations of gender discrimination and to propose actions and measures to correct them. |
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