Identifying Data 2023/24
Subject (*) Bioinformatics and Biomolecular models Code 610441021
Study programme
Máster Universitario en Bioloxía Molecular, Celular e Xenética
Descriptors Cycle Period Year Type Credits
Official Master's Degree 2nd four-month period
First Optional 3
Language
Spanish
Teaching method Face-to-face
Prerequisites
Department Bioloxía
Ciencias da Computación e Tecnoloxías da Información
Computación
Coordinador
Dorado de la Calle, Julian
E-mail
julian.dorado@udc.es
Lecturers
Becerra Fernandez, Manuel
Dorado de la Calle, Julian
Puente Castro, Alejandro
E-mail
manuel.becerra@udc.es
julian.dorado@udc.es
a.puentec@udc.es
Web
General description A xestión do coñecemento en bioloxía é o terreo da bioinformática, e inclúe tanto a formalización da información obtida como a súa organización en bases de datos adecuadas, a extracción de relacións entre a información dispersa, o modelado dos procesos biolóxicos e a xeración de hipóteses para sustentar novas aproximacións experimentais. Dende un punto de vista técnico, a bioinformática utiliza métodos computacionais (o propio desenrolo de métodos nesta área suele denominarse bioloxía computacional) e recibe aportacións das matemáticas, a física e a enxeñería informática. Sen embargo, dende o punto de vista dos obxectivos, a bioinformática é unha rama da bioloxía, como poden ser a bioquímica ou a microbiología. Neste carácter claramente interdisciplinario da bioinformática reside tanto a súa forza como a súa debilidade: por unha parte, a aplicación de ideas traídas doutros campos produce constantemente avances espectaculares; pero, por outra parte, é difícil desenrolar os programas de formación adecuados.

Para darse de conta da importancia da bioinformática na bioloxía actual, quizais sea bastane dicir que o método máis citado nas publicacións desta área é Blast, un método computacional que busca e identifica secuencias de proteínas e ácidos nucleicos en bases de datos: e dicir, a operación técnica máis realizada por biólogos é computacional, e non experimental. De feito, a interpretación de calquer experimento complexo en bioloxía require, case ineludiblemente, a análise bioinformática, algo especialmente obvio se se trata de experimentos masivos.

Study programme competencies
Code Study programme competences / results
A3 Skills of understanding the functioning of cells through the structural organization, biochemistry, gene expression and genetic variability.
A9 Skills of understanding the structure and dynamics of proteins to individual and proteomic level, as well as the techniques that are necessary to analyze them and to study their interactions with other biomolecules.
A11 Skills of understanding the structure, dynamics and evolution of genomes and to apply tools necessary to his study.
B1 Analysis skills to understand biological problems in connection with the Molecular and Cellular Biology and Genetics.
B2 Skills of decision making for the problem solving: that are able to apply theoretical knowledges and practical acquired in the formulation of biological problems and the looking for solutions.
B3 Skills of management of the information: that are able to gather and to understand relevant information and results, obtaining conclusions and to prepare reasoned reports on scientific and biotechnological questions
B9 Skills of preparation, show and defense of a work.
C3 Using ICT in working contexts and lifelong learning.
C6 Acquiring skills for healthy lifestyles, and healthy habits and routines.
C8 Valuing the importance of research, innovation and technological development for the socioeconomic and cultural progress of society.
C9 Ability to manage times and resources: developing plans, prioritizing activities, identifying critical points, establishing goals and accomplishing them.

Learning aims
Learning outcomes Study programme competences / results
Know access to Channels Bioinformatics Web Resources AR3
BR3
BR9
CC3
Understand and manage properly the area of Bioinformatics AR3
BR3
BR9
CC3
CC6
Being able to function independently to find information about the different programs and their changeable parameters and understand the impact on the results of the analysis AR3
BR2
BR3
BR9
CC3
CC9
To have bioinformatics knowledge of how to make a prediction of the onedimensional characteristics of a protein AR3
AR9
AR11
BR1
BR2
BR3
CC3
CC6
CC8
To be able to perform a simple prediction of the three dimensional structure of a protein based on available data and programs on the Web AR3
BR1
BR2
BR3
CC3
CC6
CC8
CC9
Learn the basic methods of molecular simulation and how they are used for the study of proteins AR3
BR1
BR2
BR3
CC3
CC6
CC8

Contents
Topic Sub-topic
Bioinformatics Web Resources and Databases in molecular biology. Analysis and comparison of sequences.
Sequence alignment. Location of motives. Search of genes. annotation of
genes. Browsers genome project. Examples of applications. Data analysis.
Modeling of Biomolecules Prediction of the characteristics of the protein structure. Obtaining three-dimensional models.
Homology modeling. Modeling by threading or by remote homology design.
Ab initio methods. Evaluation of the prediction methods.

Planning
Methodologies / tests Competencies / Results Teaching hours (in-person & virtual) Student’s personal work hours Total hours
Guest lecture / keynote speech A3 A9 A11 10 20 30
Seminar B3 B9 C6 C8 C9 2 7 9
Laboratory practice B1 B2 C3 C9 9 22.5 31.5
 
Personalized attention 4.5 0 4.5
 
(*)The information in the planning table is for guidance only and does not take into account the heterogeneity of the students.

Methodologies
Methodologies Description
Guest lecture / keynote speech Oral presentation complemented by the use of audiovisual media for the purpose of transmitting knowledge and facilitate learning.
Seminar Working technique that aims to make powerpoint and word documents on a topic proposed by the teacher.
Laboratory practice Methodology that allows students to learn effectively through practical activities (demonstrations, simulations, etc.) the theory of a field of knowledge through the use of information technology and communications.

Personalized attention
Methodologies
Seminar
Laboratory practice
Description
The personal attention that is described in relation to these methodologies are conceived as moments of classroom student work with teacher, this involve mandatory participation for the student.
The manner and time in which it was held is indicated in relation to each activity along the course according to the work plan of the course

Assessment
Methodologies Competencies / Results Description Qualification
Guest lecture / keynote speech A3 A9 A11 A test will be realized to assess the knowledge acquired in the course of lectures.

With this methodology the A5, B2 skillls will be assessed
45
Seminar B3 B9 C6 C8 C9 The seminar will be evaluated by taking into account the ability to extract the most relevant information obtained for the student, the capacity for teamwork and the ability to expose in public.

Whit this methodology B1, B3 and B9 competencies will be evaluated
25
Laboratory practice B1 B2 C3 C9 Regular attendance and active participation in the lab, as well as the bulletin responses made by students will be assessed. They also perform a test to assess the knowledge acquired.

With this methodology the A5 and B2 competencies will be assessed
30
 
Assessment comments

Students presented in the first opportunity of June will be eligible to get honours.

Students
with a part-time or assistance or exemption ("dispensa académica") may
agree with teachers specific methods for evalaution early in the course .

In
the second opportunity or in the early call, students will only be able
to repeat the exam corresponding to the evaluation of the Master
Session and deliver the laboratory practice bulletins, if they did not
deliver them at the first opportunity, specifying with the corresponding
teacher the date of delivery.

Plagiarism:

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


Sources of information
Basic

BIOINFORMATICS
• Attwood, T.K. & D.J. Parry-Smith. 1999. Introduction to Bioinformatics. Addison Wesley Longman Limited, Edimburgo.
• Baxevanis, A.D. & B.F. Francis Oullette (Eds.). 2002. Bioinformatics. A practical guide to the analysis of genes and proteins. 2nd Ed.
Wiley-Interscience.
• Bishop, M. 1999. Bioinformatics. Taylor & Francis, UK.
• Claverie, J.M. and C. Notredame. 2003. Bioinformatics for dummies. Wiley Publishing, Inc.
• Gibas, C. y P. Jambeck. 2001. Developing Bioinformatics Computer Skills. O'Reilly
• Higgins, D. y W. Taylor. 2000. Bioinformatics: Sequence, structure and databanks. Oxford University Press.
• Higgs, P. & T.K. Attwood 2005. Bioinformatics and molecular evolution. Blackwell Publishing.
• Kanehisa, M. 2000. Post-genome informatics. Oxford University Press
• Li, W-H. 1999. Molecular evolution. Sinauer Associates Inc., Massachusetts, 2nd. Ed.
• Mount, David W. 2001. Bioinformatics. Sequence and Genome Analysis. Cold Spring Harbor Laboratory Press.
• Nei, M. y S. Kumar. 2000. Molecular Evolution and Phylogenetics. Oxford University Press.
• Pevsner, J. 2003. Bioinformatics and Functional Genomics. John Wiley & Sons, Inc.
• Rashidi, H.H. and L.K. Buehler. 2000. Bioinformatics Basics. Applications in Biological Science and Medicine. CRC Press, Boca Raton.
• Salzberg, S., D. Searls, and S. Kasif (Eds). 1998. Computational Methods in Molecular Biology. Elsevier Science.
• Swindell, S.R., R.R. Miller y G.S.A. Myers. 1997. Internet for the Molecular Biologist. Horizon Scientific Press, Norfolk, UK.
• Tisdall, J. 2001. Beginning Perl for Bioinformatics. O'Reilly
MODELING OF BIOMOLECULES
• Bnaszak,L. J. 2000. Foundations of structural biology. Academic Press.
• Bourne, P. E., Weissig,H. 2003. Structural Bioinformatics. John Wiley & Sons.
• Branden,C. & Tooze, J. 1998. INTRODUCTION TO PROTEIN STRUCTURE. 2nd editionGarland Publishing, Inc, New York .
• Creighton,T. E. 1993. PROTEINS: STRUCTURES AND MOLECULAR PROPERTIES, 2nd edition. W.H.Freeman & Company, New York .
• Gómez-Moreno,C. & Sancho, J. (Coords). 2003. ESTRUCTURA DE PROTEÍNAS. Ariel Ciencia, Barcelona .
• Lesk, A.M. 2000. INTRODUCTION TO PROTEIN ARCHITECTURE. THE STRUCTURAL BIOLOGY OFPROTEINS. Oxford University Press, Oxford .
• Tramontano,A. 2006. Protein Structure Prediction. Wiley-Vch.

Complementary

Molecular visualization programs:

Rasmol: http://www.umass.edu/microbio/rasmol

Swiss-PdbViewer: http://www.expasy.ch/spdbv/

MOLMOLhttp://www.mol.biol.ethz.ch/wuthrich/software/molmol

Cn3Dhttp://www.ncbi.nlm.nih.gov/Structure/CN3D/cn3d.shtml

Chime http://www.umass.edu/microbio/chime

Modeling and prediction servers:

SWISS-MODEL http://expasy.ch/swissmod/

ThePredictProtein Server http://ww.embl-heidelberg.de/predictprotein/predictprotein.html

Center for MolecularModeling: http://cmm.info.nih.gov/modeling/

GRAMM: http://reco3.musc.edu/gramm/

PQS(Probable Quat. Structure): http://msd.ebi.ac.uk/services/quaternary/quaternary.html


Recommendations
Subjects that it is recommended to have taken before
Molecular Techniques/610441002

Subjects that are recommended to be taken simultaneously
Protein Structure and Dynamics/610441012
Proteomics/610441014
Genomics /610441015

Subjects that continue the syllabus
Project/610441023

Other comments

Green Campus Program of Facultade de Ciencias

To help achieve a sustainable immediate environment and comply with point 6 of the "Declaración Ambiental da Facultade de Ciencias (2020)", the documentary works carried out in this subject:

a. They will be requested mainly in virtual format and computer support.

b. If done on paper:

- Plastics will not be used.

- Double-sided prints will be made.

- Recycled paper will be used.

- The realization of drafts will be avoided.



(*)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.