27615 Molecular Evolution
Point( ECTS )
Taught under single-course student
|Technological specialization course, MSc. Eng., Bioinformatics Systems Biology|
|F5B (Wed 13-17)
Scope and form:
|Lectures and computer exercises|
Duration of Course:
Type of assessment:
| , |
General course objectives:
To provide the student with broad knowledge in the field of
molecular evolution (i.e., the evolution of DNA, RNA, and
proteins), and with in-depth knowledge of model-based methods for
phylogenetic tree reconstruction and hypothesis testing in an
evolutionary context. Although the study of molecular evolution
does require a certain level of mathematical understanding, this
course has been designed to attract a diverse range of
A student who has met the objectives of the course will be able to:
- Account for natural selection and the neutral theory of
- Solve simple population genetic problems.
- Account for important properties of phylogenetic tree
- Construct phylogenetic trees under the parsimony, distance, and
maximum likelihood criteria (using the PAUP* program); construct
Bayesian phylogenetic trees (using the MrBayes program).
- Use the Fitch algorithm to manually compute the length of a
tree given an alignment; use this as the basis for selecting the
most parsimonious tree(s).
- Manually compute the likelihood for a phylogenetic model given
a set of parameter values and an alignment.
- Manually compute the posterior probabilities for a set of
phylogenetic models, given a set of parameter values and prior
model probabilities; use this as the basis for selecting the best
- Use the program modeltest to choose a suitable nucleotide
substitution model for a phylogenetic analysis.
- Use the PAML program package to detect positively selected
sites in a protein-encoding gene.
- Use likelihood ratio testing for manually selecting the best of
two alternative phylogenetic models.
- Use the PAUP* program for investigating the degree of
uncertainty in a phylogenetic tree by non-parametric
- Use the PAML program package for comparing alternative
phylogenetic hypotheses by parametric
Brief introduction to evolutionary theory and population genetics.
Mechanisms of molecular evolution. Models of DNA and protein
substitution. Reconstruction of phylogenetic trees using distance
based methods, parsimony, maximum likelihood, and Bayesian
techniques. Advanced models of nucleotide substitution
(gamma-distributed mutation rates, molecular clock models, codon
models and analysis of selective pressure). Statistical analysis of
biological hypotheses (likelihood ratio tests, parametric
bootstrapping, Bayesian statistics).
The student will acquire practical experience in the use of
computational methods by analyzing sequences from the scientific
Green challenge participation:
Please contact the teacher for information on whether this course
gives the student the opportunity to prepare a project that may
participate in DTU´s Study Conference on sustainability, climate
technology, and the environment (GRØN DYST). More infor
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Last updated: 04. maj, 2015