Identifying Data 2021/22
Subject (*) Fundamentals of bioinformatics Code 614522008
Study programme
Mestrado Universitario en Bioinformática para Ciencias da Saúde
Descriptors Cycle Period Year Type Credits
Official Master's Degree 1st four-month period
First Obligatory 6
Language
English
Teaching method Hybrid
Prerequisites
Department Ciencias da Computación e Tecnoloxías da Información
Computación
Fisioterapia, Medicina e Ciencias Biomédicas
Coordinador
Munteanu , Cristian Robert
E-mail
c.munteanu@udc.es
Lecturers
Fernández Lozano, Carlos
Munteanu , Cristian Robert
E-mail
carlos.fernandez@udc.es
c.munteanu@udc.es
Web http://moodle.udc.es
General description Esta materia impártese en inglés. Expóñense os conceptos sobre os principios básicos da anotación do xenoma, o análise de secuencias, as ferramentas de procesamento de información molecular, as ferramentas para deseño de fármacos e a avaliación da toxicidade, as bases de datos biolóxicas, omics e epixenética, os proxectos Xenoma humano, Varioma e Exposoma, e as aplicacións de bioinformática en la clínica.
Contingency plan 1. Modificacións nos contidos
sen modificacións

2. Metodoloxías
Metodoloxías docentes que se manteñen
Mantéñense as mesmas metodoloxías excepto polos mecanismos de avaliación e as clases que se pasarán da aula a sistemas online como Teams

Metodoloxías docentes que se modifican

3. Mecanismos de atención personalizada ao alumnado
Usarase moodle para proporcionar o material docente aos estudantes. Usaranse os foros de moodle como medio de comunicación de cambios na materia (cambios, entregas de prácticas, etc). Realizaranse clases síncronas en horario oficial de clase e poderanse deixar vídeos asíncronos en Stream. As titorías realizaranse vía Teams e responderanse dúbidas por email.

4. Modificacións na avaliación
Os mecanismos de avaliación manteranse coa condición de que se pasarán de clase presencial na facultade para ser vía Teams.

Observacións de avaliación:

5. Modificacións da bibliografía ou webgrafía
sen cambios

Study programme competencies
Code Study programme competences
A1 CE1 - Ability to know the scope of Bioinformatics and its most important aspects
A6 CE6 - Ability to identify software tools and most relevant bioinformatics data sources, and acquire skill in their use
A7 CE7 - Ability to identify the applicability of the use of bioinformatics tools to clinical areas.
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
B3 CB8 - Students to be able to integrate knowledge and deal with the complexity of making judgements from information that could be incomplete or limited, including reflections on the social and ethical responsibilities linked to the application of their skills and judgments
B5 CB10 - Students should possess learning skills that allow them to continue studying in a way that will largely be self-directed or autonomous.
B6 CG1 -Search for and select the useful information needed to solve complex problems, driving fluently bibliographical sources for the field
B7 CG2 - Maintain and extend well-founded theoretical approaches to enable the introduction and exploitation of new and advanced technologies
B8 CG3 - Be able to work in a team, especially of interdisciplinary nature
C1 CT1 - Express oneself correctly, both orally writing, in the official languages of the autonomous community
C2 CT2 - Dominate the expression and understanding of oral and written form of a foreign language
C3 CT3 - Use the basic tools of the information technology and communications (ICT) necessary for the exercise of their profession and lifelong learning
C6 CT6 - To assess critically the knowledge, technology and information available to solve the problems they face to.
C8 CT8 - Rating the importance that has the research, innovation and technological development in the socio-economic and cultural progress of society

Learning aims
Learning outcomes Study programme competences
To identify the characteristics of the computer science applications in health sciences AJ1
AJ6
BJ1
BJ2
BJ3
To be able to develop a research project in the field of biomedical informatics according to ethical and security health data requirements AJ7
BJ5
BJ6
BJ7
BJ8
CJ1
CJ2
CJ3
CJ6
CJ8
To know how to identify fields of application of information technologies and communications to improve the delivery of health services to citizens AJ7
CJ1
CJ2
CJ3
CJ6
CJ8

Contents
Topic Sub-topic
Basic principles for Genome Annotation
Sequence analysis
Processing tools of molecular information
Tools for drug design and evaluation of toxicity
Biological databases
Omics and epigenetics: genomics, proteomics, transcriptomics
Projects: Human Genome, Variome, Exposome
Bioinformatics applications in clinical practice
.

Planning
Methodologies / tests Competencies Ordinary class hours Student’s personal work hours Total hours
ICT practicals A1 A6 A7 B1 B2 B3 B5 B6 B7 B8 C1 C2 C3 C6 C8 30 30 60
Oral presentation A1 C1 C2 C3 C6 C8 5 5 10
Supervised projects A1 C1 C2 C3 C6 C8 10 10 20
Objective test A1 A6 A7 B1 B2 B3 B5 B6 B7 B8 C1 C2 C3 C6 C8 1 14 15
Guest lecture / keynote speech A1 A6 A7 B1 B2 B3 B5 B6 B7 B8 C1 C2 C3 C6 C8 20 20 40
 
Personalized attention 5 0 5
 
(*)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 Laboratory practice can be face-to-face or through computer platforms such as TEAMS.
Oral presentation Public presentation of the supervised work can be face-to-face or through computer platforms such as TEAMS.
Supervised projects Practical work on the theoretical content of the course can be face-to-face or through computer platforms such as TEAMS.
Objective test Exam on the theoretical content and supervised work carried out throughout the course if there is no supervised work. It can be face-to-face or through computer platforms such as TEAMS.
Guest lecture / keynote speech In the theory sessions, the teacher describes the objectives and contents of the subject, to give a particular view of the subject to be dealt with and to relate it to others within the subject.

Then the corresponding topic is developed in the form of a lecture session, using the technical tools available, emphasizing certain issues in which the student must deepen his self-learning.

The master sessions can be face-to-face or through computer platforms such as TEAMS. It is also possible to include explanatory videos of different parts of the theoretical contents.

Personalized attention
Methodologies
Supervised projects
Objective test
Oral presentation
Guest lecture / keynote speech
ICT practicals
Description
To solve the most complex aspects of the course, individual or group tutorials with students will be held.

Assessment
Methodologies Competencies Description Qualification
Supervised projects A1 C1 C2 C3 C6 C8 The proposed work on the subject will be part of the evaluation. 30
Objective test A1 A6 A7 B1 B2 B3 B5 B6 B7 B8 C1 C2 C3 C6 C8 If deemed necessary, a test on the theoretical and practical content of the course (including the topics of the lectures and publicly exposed supervised projects) may be conducted. The teacher can distribute points of this test among other methods if deemed appropriate. 30
Oral presentation A1 C1 C2 C3 C6 C8 The public presentation of the supervised work will be part of the final assessment. 30
ICT practicals A1 A6 A7 B1 B2 B3 B5 B6 B7 B8 C1 C2 C3 C6 C8 The quality and delivery in time of the practices will be assessed. 10
 
Assessment comments

To pass this course, the student needs to obtain a minimum percentage in each of the methodologies.

Plagiarism:

In any submission in which plagiarism is detected, the submission will be assessed a zero. Plagiarism in the objective test will be penalized in accordance with current university regulations.


Sources of information
Basic Ohlebusch, Enno (2013). Bioinformatics algorithms : sequence analysis, genome rearrangements, and phylogenetic reconstruction. Ulm : Oldenbusch Verlag
Dan E. Krane, Michael L. Raymer (2003). Fundamental concepts of bioinformatics. San Francisco, California : Benjamin Cummings
Edward Keedwell and Ajit Narayanan (2005). Intelligent bioinformatics the application of artificial intelligence techniques to bioinformatics problems. Chichester : John Wiley & Sons
Stekel, Dov. (2003). Microarray bioinformatics. Cambridge: Cambridge University Press, 2003

Graph-based Processing of Macromolecular Information, Current Bioinformatics 10(5): 606-631 (2016), DOI: 10.2174/1574893610666151008012438 | Cristian R. Munteanu, Vanessa Aguiar-Pulido, Ana Freire, Marcos Martínez-Romero, Ana B. Porto-Pazos, Javier Pereira, Julian Dorado | online


RRegrs: An R package for Computer-aided Model Selection with Multiple Regression Models, Journal of Cheminformatics  7(1), 1-16, doi:10.1186/s13321-015-0094-2 (2015) | Georgia Tsiliki, Cristian R. Munteanu, Jose A Seoane, Carlos Fernandez-Lozano, Haralambos Sarimveis, Egon L. Willighagen | GitHub| 10.5281/zenodo.21946 | online 

Bio-AIMS Collection of Chemoinformatics Web Tools based on Molecular Graph Information and Artificial Intelligence Models, Combinatorial Chemistry & High Throughput Screening 18(8):735-50 (2015) | Cristian R. Munteanu, Humberto González-Díaz, Rafael García, Mabel Loza, Alejandro Pazos | online 

S2SNet: A Tool for Transforming Characters and Numeric Sequences into Star Network Topological Indices in Chemoinformatics, Bioinformatics, Biomedical, and Social-Legal sciences, Current Bioinformatics 8(4), 429-437 (2013) | Cristian R. Munteanu, Alexandre L Magalhães, Aliuska Duardo Sánchez, Alejandro Pazos, Humberto González-Díaz | online

Tutorial Biopython: http://biopython.org/DIST/docs/tutorial/Tutorial.html
Complementary


Recommendations
Subjects that it is recommended to have taken before

Subjects that are recommended to be taken simultaneously

Subjects that continue the syllabus

Other comments

Materia impartida en inglés



(*)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.