Guía Docente 2023-24 FILOGENÉTICA |
BASIC DETAILS:
Subject: | FILOGENÉTICA | ||
Id.: | 33296 | ||
Programme: | GRADUADO EN BIOINFORMÁTICA. PLAN 2019 (BOE 06/02/2019) | ||
Module: | CIENCIAS DE LA VIDA | ||
Subject type: | OBLIGATORIA | ||
Year: | 3 | Teaching period: | Primer Cuatrimestre |
Credits: | 6 | Total hours: | 150 |
Classroom activities: | 62 | Individual study: | 88 |
Main teaching language: | Inglés | Secondary teaching language: | Castellano |
Lecturer: | Email: |
PRESENTATION:
The main goal of this subject is providing the tools to analyze molecular sequences in order to establish evolutionary relationships between each other by the creation of trees.
Historical background will be provided and how the discovers in biotechnology have provided new theories in the phylogenetics field. The process of tree building by detecting the difference between a given set of biological sequence will be analyzed. Substitution methods of evolution will be explored by using mathematical concepts.
Tree building algorithms based on distances or probabilistics approaches will be analyzed to determine which performs the best outcome. Already developed tools, as well as, R packages of functions and in-house python algorithms will be used for phylogenetics tree building.
Validation of trees will be also determined and the computational limitations due to genomic complexity will be analyzed.
PROFESSIONAL COMPETENCES ACQUIRED IN THE SUBJECT:
General programme competences | G04 | Reason critically based on information, data and lines of action and their application on relevant issues of a social, scientific or ethical nature. |
G05 | Communicate professional topics in Spanish and / or English both orally and in writing. | |
G07 | Choose between different complex models of knowledge to solve problems. | |
G08 | Recognise the role of the scientific method in the generation of knowledge and its applicability to a professional environment. | |
G10 | Apply creativity, independence of thought, self-criticism and autonomy in the professional practice. | |
Specific programme competences | E13 | Apply omics technologies for the extraction of statistically significant information and for the creation of relational databases of biodata that can be updated and publicly accessible to the scientific community. |
E16 | Plan linkage and association studies for medical and environmental purposes. | |
E17 | Induce complex relationships between samples by applying statistical and classification techniques. | |
E18 | Apply statistical and computational methods to solve problems in the fields of molecular biology, genomics, medical research and population genetics. | |
Learning outcomes | R01 | Definir el concepto de filogenética. |
R02 | Describir los principales términos asociados a la filogénetica. | |
R03 | Explicar los mecanismos evolutivos requeridos para construir árboles filogenéticos. | |
R04 | Discriminar las diferentes metodologías de construcción de árboles filogenéticos. | |
R05 | Componer árboles filogenéticos a partir de datos morfológicos. |
PRE-REQUISITES:
Basic statistics, probabilistic, genomics and alignement theory are needed to understand the underlying knowledge of phylogenetics. Programming skills in R and Python are mandatory to understand the provided code.
SUBJECT PROGRAMME:
Observations:
Subject contents:
1 - Introduction to Phylogenetics |
1.1 - Introduction and terminology |
1.2 - Speciation. Tree topologies. |
1.3 - Theories |
1.4 - Applications |
2 - Phylogenetics Analysis |
2.1 - Types of trees |
2.2 - Molecular markers |
2.3 - Multiple sequence alignment |
2.4 - Model evolution of nucleotides |
2.5 - Model evolution of amino acids |
2.6 - Model selection |
2.7 - Tree building method |
2.8 - Assessing tree reliability |
2.9 - Available softwares |
3 - Building algorithms based on distances. Neighbour joining. |
4 - Building algorithms based on distances. Unweighted pair group method with arithmetic mean. |
5 - Building algorithms based on distances. Maximum parsimony. |
6 - Building algorithms based on probabilistic approaches. Maximum likelihood. |
7 - Building algorithms based on probabilistic approaches. Bayesian inference. |
8 - Assessing tree reliability. |
9 - Genome complexity and phylogenetics analysis. |
Subject planning could be modified due unforeseen circumstances (group performance, availability of resources, changes to academic calendar etc.) and should not, therefore, be considered to be definitive.
TEACHING AND LEARNING METHODOLOGIES AND ACTIVITIES:
Teaching and learning methodologies and activities applied:
This subject is based on active participation, for which different teaching and learning methodologies will be applied: master classes, problem-based learning and case-study learning.
Student work load:
Teaching mode | Teaching methods | Estimated hours |
Classroom activities | ||
Master classes | 20 | |
Other theory activities | 2 | |
Practical exercises | 20 | |
Practical work, exercises, problem-solving etc. | 20 | |
Individual study | ||
Tutorials | 6 | |
Individual study | 40 | |
Individual coursework preparation | 10 | |
Project work | 15 | |
Research work | 10 | |
Recommended reading | 7 | |
Total hours: | 150 |
ASSESSMENT SCHEME:
Calculation of final mark:
Written tests: | 20 | % |
Individual coursework: | 20 | % |
Final exam: | 50 | % |
Case-study: | 10 | % |
TOTAL | 100 | % |
*Las observaciones específicas sobre el sistema de evaluación serán comunicadas por escrito a los alumnos al inicio de la materia.
BIBLIOGRAPHY AND DOCUMENTATION:
Basic bibliography:
PEVSNER, Jonathan. Bioinformatics and functiona genomics. Oxford: John Wiley and Sons, 2015. |
DURBIN, Richard. Biological sequence analysis. Cambridge: Cambridge University Press, 1998 |
BLEIDORN, Christoph. Phylogenomics An Introduction. Gewerberstrasse: Springer. 2017 |
Recommended bibliography:
ROCHA Miguel. Bioinformatics Algorithms Design and Implementation in Python. London: Academic Press 2018 |
XIONG, Jin. Essential Bioinformatics. Cambridge: Cambridge University Press, 2006 |
Recommended websites:
Bioconductor | https://www.bioconductor.org/ |
* Guía Docente sujeta a modificaciones