Teaching GuideTerm
Faculty of Computer Science
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Mestrado Universitario en Bioinformática para Ciencias da Saúde
 Subjects
  Data structures and algorithmics for biological sequences
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Identifying Data 2020/21
Subject (*) Data structures and algorithmics for biological sequences Code 614522013
Study programme
Mestrado Universitario en Bioinformática para Ciencias da Saúde
Descriptors Cycle Period Year Type Credits
Official Master's Degree 2nd four-month period
First Obligatory 6
Language
Spanish
English
Teaching method Hybrid
Prerequisites
Department Ciencias da Computación e Tecnoloxías da Información
Computación
Coordinador
Ladra González, Susana
E-mail
susana.ladra@udc.es
Lecturers
Ladra González, Susana
Silva Coira, Fernando
E-mail
susana.ladra@udc.es
fernando.silva@udc.es
Web
General description This course introduces the basics of the algorithms and data structures that are commonly used in the field of computational biology.
Contingency plan 1. Modifications to the contents - No changes will be made 2. Methodologies *Teaching methodologies that are maintained - Guest lecture / keynote speech - ICT practicals - Supervised projects - Personalized attention *Teaching methodologies that are modified - Mixed test: in case it cannot be performed in person, it will be replaced by "Problem solving") 3. Mechanisms for personalized attention to students - Email: Daily. Used to make queries, request virtual meetings to resolve doubts and monitor the work being supervised. - Moodle: Daily. According to the needs of the students. They will have "thematic forums" associated to the modules of the subject, to formulate the necessary consultations. - Teams: Telematic session in the time slot assigned to the subject in the faculty's classroom calendar for the advancement of the expository and practical subject. Individual or small group telematic sessions to resolve doubts about the subject of the presentation, practice or supervised work 4. Modifications in the evaluation The 30% of the mixed test is replaced by "Problem solving", which will also have a 30% weight in the evaluation. It will consist of the resolution of four exercises in which the knowledge and the competencies acquired during the master classes. The students will have to hand in the solution of the proposed exercises, having to defend it orally. *Evaluation observations: The minimum requirements for the different parts of the evaluation will not be applied. The final mark will be the sum of those obtained in each part. FIRST OPPORTUNITY: Any student who does not send a proposal for the proposed problem-solving tasks will be marked as "Non presentado" (Absent). SECOND OPPORTUNITY: Only those students who do not pass the subject in the first opportunity will be able to present themselves to the second opportunity. The recovery of each part will be done in the following way: - ICT practicals (50%): students will be able to repeat the proposed ICT practicals during the course in the same conditions as in the first opportunity (the internships delivered late will obtain a maximum of 80%). Thus, in case of repeating all the practices, the maximum mark that can be obtained is 4 points. - Supervised project (20% of the final mark): carried out under the same conditions as at the first opportunity, but on an individual basis. - Problem solving (30%): carried out under the same conditions as the first time. - In case of not recovering any of the parts, the grade obtained at the first opportunity in that part will be kept. - Any student who does not opt for the recovery of any of the parties will have a grade of "Non presentado" (Absent). 5. Modifications to the bibliography or webgraphy - No changes will be made.
(*)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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