Code: | B4001 | Acronym: | B4001 |
Keywords | |
---|---|
Classification | Keyword |
OFICIAL | Biology |
Active? | Yes |
Responsible unit: | Department of Biology |
Course/CS Responsible: | Master in Biodiversity, Genetics and Evolution |
Acronym | No. of Students | Study Plan | Curricular Years | Credits UCN | Credits ECTS | Contact hours | Total Time |
---|---|---|---|---|---|---|---|
E:BBC | 0 | PE_Bioinformatics and Computational Biology | 1 | - | 6 | 42 | 162 |
M:BBC | 4 | The study plan since 2018 | 2 | - | 6 | 42 | 162 |
M:BGE | 16 | Official Study Plan | 1 | - | 6 | 42 | 162 |
M:GF | 0 | plano de estudos do Mestrado em Genética Forense a partir de 2013_2014 | 1 | - | 6 | 42 | 162 |
The course aims to give students an understanding of the importance of phylogenetics for systematics, comparative biology, biomedical issues and conservation planning. Widely used methodologies are discussed and compared, along with the relative philosophies behind each method.
The aim is that by the end of the course students can take data from the web and analyse it in a phylogenetic framework, while appreciating the differences between alternative methods.
Introduction to phylogenetics. Why is it so important?
A brief history. From Darwin and the first "trees", through debates of
cladistics vs phenetics, to parsimony vs likelihood and to the present
situation.
Methodologies. Maximum Parsimony, Distance methods (minimum evolution,
neighbor-joining and UPGMA), Maximum Likilhood and Bayesian Inferences.
The pros and cons of different methods.
Consensus methods. How to combine sources of information.
Support methods. Bootstrapping, Bayesian Posterior Probabilities, Decay
Index. What do they mean and how to compare them.
Philosophy. If Popper was right, are we barking up the wrong tree?
An assessment of the interplay between population genetics and
phylogenetics. Why use networks instead of trees? Comparing the methodologies above and below the species level.
Theoretical and practical classes. During the practical classes students will obtain and analyse real data obtained from GeneBank and other molecular databases.
designation | Weight (%) |
---|---|
Participação presencial | 20,00 |
Trabalho escrito | 80,00 |
Total: | 100,00 |
designation | Time (hours) |
---|---|
Estudo autónomo | 120,00 |
Frequência das aulas | 42,00 |
Total: | 162,00 |
Attendance to the practical component and report delivery.
Final report: 80%
Attendance and participation: 20%