NCHU Course Outline
Course Name (中) 親緣關係資料分析(6234)
(Eng.) Phylogenetic Data Analysis
Offering Dept Department of Entomology
Course Type Elective Credits 3 Teacher Dávid Rédei
Department Department of EntomologyPh.D Language English Semester 2025-SPRING
Course Description This course is an introduction to basic principles and methods of phylogenetic inference (estimating the evolutionary relationships among a set of taxa), with focus on methods with relevance to systematics and taxonomy. It covers inference from both morphological and molecular characters. The course is practice-oriented, emphasis will be on learning how to use particular softwares and methods. Accordingly, students will required to bring their own notebook computer for each class.
Prerequisites
self-directed learning in the course Y
Relevance of Course Objectives and Core Learning Outcomes(%) Teaching and Assessment Methods for Course Objectives
Course Objectives Competency Indicators Ratio(%) Teaching Methods Assessment Methods
On completion of the course the students will become familiar with the basic principles and procedure of phylogenetic inference; acquire a solid theoretical knowledge of phylogenetic analysis of morphological and molecular data sets with cladistic methods; become familiar with softwares used for cladistic analysis and acquire skill in using them; become able to generate, analyze and interpret phylogenetic trees for his own groups of interest; acquire "tree thinking"; will learn important applications of phylogenetic methods in treating different scientific problems; and improve their English vocabulary, listening and oral skills.
topic Discussion/Production
Discussion
Practicum
Lecturing
Assignment
Course Content and Homework/Schedule/Tests Schedule
Week Course Content
Week 1 Some basic principles. Artificial and natural classifications. Reconstructing phylogenies. Different kinds of evidences used in systematics. Morphological evidence: homology and its criteria. Trait evolution, divergent and convergent evolution, parallelism. Plesiomorphic and advanced characters. Homoplasy. Higher taxonomic categories, basis for their recognition, ranking. Monophyletic and non-monophyletic taxa. Phenetics, cladistics.
Week 2 An introduction to cladistics: basic concepts and terms. Taxonomic characters, their kinds and importance in the cladistic paradigm. Character coding, transformation series and ordering. Character state polarity and its determination, ordering character states. Handling missing data. Tree thinking.
Week 3 Introduction to online resources and softwares of application in systematics. Getting familiar with softwares and file formats. Selecting and coding of characters, building a character matrix.
Week 4 Constructing a cladogram from morphological datasets. Principle of parsimony in biology; finding the most parsimonious cladogram; exact and heuristic methods; parsimony versus likelihood. Weighting data. Character optimization. Performing simple searches, dealing with outputs, tree formats, simple tree manipulation, saving results; practice.
Week 5 The quality of the cladogram. Measures of character fit: cladogram length, consistency index, retention index. A priori and a posteriori character weighting. Measures of support of individual clades, Bremer support, bootstrap, jackknife.
Week 6 Comparison of trees. Consensus trees. Understanding and interpreting cladograms, common misconceptions. Using trees to study character evolution. Testing hypotheses of adaptation. Ancestral reconstructions.
Week 7 Further discussion and practice on selected concrete problems.
Week 8 Mid-semester test.
Week 9 Special features of molecular datasets, similarities and differences to morphological data. Acquiring sequences: databases and online resources. Getting familiar with softwares and file formats. Homology in molecular datasets. Sequence alignment.
Week 10 Constructing a cladogram from molecular datasets. Basic features of nucleotide substitutions. Nucleotide substitution models. Distance-based methods. Neighbour-joining trees, their advantages and disadvantages. Chosing an evolutionary model.
Week 11 Constructing a cladogram from molecular datasets. Basic features of nucleotide substitutions. Nucleotide substitution models. Parsimony analysis of molecular data, problems. Distance-based methods. Neighbour-joining trees, their advantages and disadvantages. Chosing an evolutionary model.
Week 12 Maximum likelihood in theory and practice. Estimating support of clades of a molecular tree by bootstrapping.
Week 13 Bayesian inference in theory and practice.
Week 14 Combining different sources of data: simultaneous and partitioned analysis. Application of results in taxonomy: turning cladograms into formal classifications. Phylogenies and taxonomic ranks. Artifacts. Applications and case studies. Phylogenetic approaches to special problems (coevolution, biogeography).
Week 15 Further practice, discussion of additional topics and interesting problems.
Week 16 Student self-directed learning: analyzing data sets provided by instructor.
Week 17 Student self-directed learning: analyzing data sets provided by instructor.
Week 18 Final test.
Evaluation
Half-semester test results: 50%
Final test results: 50%
Textbook & other References
No textbook required, articles from primary literature treating special topics, different handouts and books will be discussed and distributed. Recommended major textbooks:
Baum, D.A. & Smith, S.D. (2013) Three thinking. An introduction to phylogenetic biology. Roberts and Co., Greenwood Village, xx+476 pp.
Hall, B.G. (2018) Phylogenetic trees made easy. A how-to manual. (Fifth edition.) Oxford University Press, New York, Oxford, XVI+352 pp.
Teaching Aids & Teacher's Website
to be determined
Office Hours
to be determined
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Update Date, year/month/day:2025/01/31 22:32:13 Printed Date, year/month/day:2025 / 2 / 12
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