Bioinformatics lecture slides

Slides of the lecture "Introduction to Bioinformatics for Computer Scientists". Click a lecture title to open the slides; click a red Video button to watch the recorded lecture. See the course page for general information.

Current semester

Winter 2026/27

Slides will appear here as the lectures take place.

Preceding years

Winter 2025/26

1. 0
   Meet and Greet with UoC Students (Crete only)
2. 1
   Preliminaries and Introduction to Basic Molecular Biology
3. 2
   Pairwise Sequence Alignment
4. 3
   BLAST & Genome Assembly
5. 4
   Multiple Sequence Alignment & Introduction to Phylogenetics
6. 5
   Introduction to Phylogenetics & Phylogenetic Search Algorithms
7. 6
   Parsimony, Phylogenetic Search Algorithms, Introduction to Markov Chains
8. 7
   Introduction to Markov Chains & Computing the Likelihood on Phylogenetic Trees
9. 8
   Maximum Likelihood Optimization, Advanced Models of Evolution, Bayesian Inference
10. 9
    Advanced Bayesian Inference & Course Wrap-up

Winter 2024/25

1. 1
   Preliminaries and Introduction to Basic Molecular Biology
2. 2
   Pairwise Sequence Alignment
3. 3
   BLAST & Genome Assembly
4. 4
   Multiple Sequence Alignment & Introduction to Phylogenetics
5. 5
   Introduction to Phylogenetics & Phylogenetic Search Algorithms
6. 6
   Parsimony & Phylogenetic Search Algorithms
7. 7
   Introduction to Markov Chains
8. 8
   Stochastic Models of Evolution and Maximum Likelihood Optimization
9. 9
   Implementing & Parallelizing Likelihood Computations, Bayesian Inference & MCMC
10. 10
    Advanced Bayesian Inference & Course Wrap-up

Winter 2023/24

1. 0
   Meet and Greet with UoC Students (Crete only)
2. 1
   Preliminaries and Introduction to Basic Molecular Biology
3. 3
   Pairwise Sequence Alignment
4. 4
   BLAST & Genome Assembly
5. 5
   Multiple Sequence Alignment & Introduction to Phylogenetics
6. 6
   Introduction to Phylogenetics & Phylogenetic Search Algorithms
7. 7
   Markov Chains and the Phylogenetic Likelihood Function
8. 8
   Stochastic Models of Evolution and Maximum Likelihood Optimization
9. 9
   Parallelizing Likelihood Computations, Bayesian Inference & MCMC
10. 10
    Advanced Bayesian Inference & MCMC and Introduction to Population Genetics
11. 11
    Introduction to Population Genetics & Course Wrap-up

Winter 2022/23

1. 1
   Introduction
2. 2
   Basic Molecular Biology
3. 3
   Pairwise Sequence Alignment (slides from 2021/22)Video 2020/21, part 1 Video 2020/21, part 2
4. 4
   BLAST & Genome Assembly
5. 5
   Multiple Sequence Alignment
6. 6
   Introduction to Phylogenetics
7. 7
   Phylogenetic Search Algorithms
8. 8
   A Brief Introduction to Markov Chains
9. 9
   Discrete Operations on Trees
10. 10
    Maximum LikelihoodSmall exercise Video
11. 11
    Advanced Maximum LikelihoodVideo
12. 12
    Bayesian Inference & MCMCVideo
13. 13
    Advanced Bayesian Inference & MCMCVideo
14. 14
    Introduction to Population GeneticsVideo
15. 15
    Wrap-up & Exam Preparation (live lecture via Zoom, no video)

Winter 2021/22

1. 1
   IntroductionVideo
2. 2
   Basic Molecular BiologyVideo 2020/21, part 1 Video 2020/21, part 2
3. 3
   Pairwise Sequence AlignmentVideo 2020/21, part 1 Video 2020/21, part 2
4. 4
   BLAST & Genome AssemblyVideo 2020/21, part 1 Video 2020/21, part 2
5. 5
   Multiple Sequence AlignmentVideo 2020/21, part 1 Video 2020/21, part 2
6. 6
   Introduction to PhylogeneticsVideo, part 1 Video, part 2
7. 7
   Phylogenetic Search AlgorithmsExercise: computing the parsimony score Video, part 1 Video, part 2
8. 8
   Phylogenetic Search Algorithms and Markov Chains

   • Search algorithms Video
   • Markov chains Video, part 1 Video, part 2
   • Markov chains: exercises (discussed in the Zoom Q&A session, no video)
9. 9
   Maximum Likelihood

   • Motivation for likelihood Video
   • Computing the likelihood on a tree Video
   • Computing the maximum likelihood on a tree Video
   • Exercise: computing the likelihood on simple trees
10. 10
    Maximum Likelihood IISmall exercise Video, part 1 Video, part 2
11. 11
    Discrete Operations on TreesExercises Video, part 1 Video, part 2
12. 12
    Bayesian Statistics and Markov Chain Monte Carlo MethodsVideo
13. 13
    Introduction to Population GeneticsVideo, part 1 Video, part 2
14. 14
    Knowledge Check and Research in the LabVideo, part 1 Video, part 2
15. 15
    Wrap-up and Exam Preparation (live lecture via Zoom, no video)

Winter 2020/21

1. 1
   IntroductionVideo, part 1 Video, part 2
2. 2
   Basic Molecular BiologyVideo, part 1 Video, part 2
3. 3
   Pairwise Sequence AlignmentVideo, part 1 Video, part 2
4. 4
   BLAST & Genome AssemblyVideo, part 1 Video, part 2
5. 5
   Multiple Sequence AlignmentVideo, part 1 Video, part 2
6. 6
   Introduction to PhylogeneticsVideo, part 1 Video, part 2
7. 7
   Phylogenetic Search AlgorithmsVideo, part 1 Video, part 2
8. 8
   Phylogenetic Search Algorithms and Markov Chains

   • Search algorithms Video
   • Markov chains Video, part 1 Video, part 2
9. 9
   Maximum Likelihood

   • Motivation for likelihood Video
   • Computing the likelihood on a tree Video
   • Computing the maximum likelihood on a tree Video
10. 10
    Maximum Likelihood IIAnswers to questions Video, part 1 Video, part 2
11. 11
    Discrete Operations on TreesVideo
12. 12
    Bayesian Statistics and Markov Chain Monte Carlo MethodsAnswers to questions Video
13. 13
    Introduction to Population GeneticsVideo, part 1 Video, part 2
14. 14
    Wrap-up and Exam Preparation

Winter 2019/20

1. 1
   Introduction
2. 2
   Basic Molecular Biology
3. 3
   Pairwise Sequence Alignment
4. 4
   BLAST & Genome Assembly
5. 5
   Multiple Sequence Alignment
6. 6
   Introduction to Phylogenetics
7. 7
   Phylogenetic Search Algorithms
8. 8
   The Maximum Likelihood Model
9. 9
   The Maximum Likelihood Model II
10. 10
    Discrete Operations on Sets of Phylogenetic Trees
11. 11
    Likelihood Models, Implementation & Parallelization
12. 12
    Bayesian Inference and MCMC
13. 13
    Advanced (MC)MCMC Methods
14. 14
    Introduction to Population Genetics
15. 15
    Course Summary

Winter 2018/19

1. 1
   Introduction
2. 2
   Basic Molecular BiologyPart 2a: continued, and some questions answered
3. 3
   Pairwise Sequence Alignment
4. 4
   BLAST & Genome Assembly
5. 5
   Multiple Sequence Alignment
6. 6
   Introduction to Phylogenetics
7. 7
   Phylogenetic Search Algorithms
8. 8
   The Maximum Likelihood Model
9. 9
   Discrete Operations on Sets of Phylogenetic Trees
10. 10
    The Maximum Likelihood Model II (on the blackboard, using the slides of lecture 8)
11. 11
    Likelihood Models, Implementation & Parallelization
12. 12
    Bayesian Inference and MCMC
13. 13
    Advanced (MC)MCMC Methods
14. 14
    Course Summary

Winter 2017/18

1. 1
   Introduction
2. 2
   Basic Molecular Biology
3. 3
   Pairwise Sequence Alignment
4. 4
   BLAST & Genome Assembly
5. 5
   Multiple Sequence Alignment
6. 6
   Introduction to Phylogenetics
7. 7
   Phylogenetic Search Algorithms
8. 8
   The Maximum Likelihood Model
9. 9
   The Maximum Likelihood Model II (on the blackboard)
10. 10
    Likelihood Models, Implementation & Parallelization
11. 11
    Discrete Operations on Trees
12. 12
    Bayesian Inference and MCMC
13. 13
    Advanced (MC)MCMC Methods
14. 14
    Course Summary

Winter 2016/17

1. 1
   Introduction
2. 2
   Basic Molecular Biology
3. 3
   Pairwise Sequence Alignment
4. 4
   BLAST & Genome Assembly
5. 5
   Multiple Sequence Alignment
6. 6
   Introduction to Phylogenetics
7. 7
   Phylogenetic Search Algorithms
8. 8
   The Maximum Likelihood Model
9. 9
   The Maximum Likelihood Model II
10. 10
    Discrete Operations on Sets of Phylogenetic Trees
11. 11
    The Maximum Likelihood Model III and Parallel Computing in Phylogenetics
12. 12
    Bayesian Inference and MCMC
13. 13
    Advanced (MC)MCMC Methods
14. 14
    Introduction to Population Genetics
15. 15
    Course Summary

Winter 2015/16

1. 1
   Introduction
2. 2
   Basic Molecular Biology
3. 3
   Pairwise Sequence Alignment
4. 4
   BLAST & Genome Assembly
5. 5
   Multiple Sequence Alignment
6. 6
   Introduction to Phylogenetics
7. 7
   Phylogenetic Search Algorithms
8. 8
   The Maximum Likelihood Model
9. 9
   The Maximum Likelihood Model II
10. 10
    Discrete Operations on Sets of Phylogenetic Trees
11. 11
    Model Selection
12. 12
    Bayesian Inference and MCMC
13. 13
    Advanced (MC)MCMC Methods
14. 14
    Introduction to Population Genetics
15. 15
    Course Summary

Winter 2014/15

1. 1
   Introduction
2. 2
   Basic Molecular Biology
3. 3
   Pairwise Sequence Alignment
4. 4
   BLAST & Genome Assembly
5. 5
   Multiple Sequence Alignment
6. 6
   Introduction to Phylogenetics
7. 7
   Phylogenetic Search Algorithms
8. 8–9
   Statistical Models of EvolutionBlackboard notes
9. 10
   Discrete Operations on Tree Sets
10. 11
    Bayesian Phylogenetic Inference
11. 12
    Advanced Bayesian Inference
12. 13
    Introduction to Population Genetics
13. 14
    A Review of the Knowledge Check and Some Coding Wisdom
14. 15
    Course Wrap-up and Exam Preparation

Summer 2014

1. 1
   Introduction
2. 2
   Molecular Biology 101
3. 3
   Pairwise Sequence Alignment
4. 4
   BLAST and Genome Assembly
5. 5
   Multiple Sequence Alignment
6. 6
   Introduction to Phylogenetics
7. 7
   Phylogenetic Search Algorithms
8. 8
   Stochastic Models of EvolutionBlackboard notes
9. 9
   Discrete Operations on Tree Sets
10. 10
    Bayesian Phylogenetic Inference

Winter 2012/13

1. 1
   Introduction
2. 2
   Basic Molecular Biology
3. 3
   More Biology and Review of the Knowledge Test (Alexis)
4. 4a
   Sequencing Insect Transcriptomes & Review of the Knowledge Test
5. 4b
   Pairwise Sequence Alignment (Solon & Alexis)
6. 5
   BLAST & Genome Assembly (Solon & Alexis)
7. 6
   Suffix Trees (Tomas & Alexis)
8. 7
   Multiple Sequence Alignment (Alexis)
9. 8
   Introduction to Phylogenetics (Alexis)
10. 9
    Phylogenetic Inference Algorithms (Alexis)
11. 10a
    Phylogenetic Search Operators (Alexis)
12. 10b
    The Maximum Likelihood Model in Phylogenetics (Kassian)Kassian's whiteboard: Jukes-Cantor model Q matrix exponentiation Newton-Raphson method
13. 11
    Advanced Maximum Likelihood Models & Parallel Computing in Phylogenetics (Alexis)
14. 12
    Discrete Operations on Phylogenetic Trees (Andre)Handout version
15. 13
    Introduction to Population Genetics (Pavlos)Blackboard drawings & equations
16. 14
    The Coalescent (Pavlos)
17. 15
    Wrap-up and Exam Preparation (Alexis)

Further reading for 2012/13: a nice outline of Tomasulo's algorithm for out-of-order execution in pipelines can be found in these slides by D.A. Patterson (Berkeley), who also wrote the book "Computer Architecture: A Quantitative Approach" with J.L. Hennessy. A textual description of the maximum likelihood model can be found on pages 20 to 31 of Alexis' PhD thesis.