### Messages

### Timetable

### Material

The lecture slides will be posted here during the course.

The course is based on the book "Bioinformatics Algorithms: An Active Learning Approach" by Philip Compeau and Pavel Pevzner. The book is available in the library but the essential information can be found in the other course materials too.

## Lecture material

### Video

Pavel Pevzner's lecture videos.

Please watch the corresponding video before each lecture on Friday.

- Before study group 0: Chapter 1: Where in the Genome Does DNA Replication Begin? (Algorithmic Warmup)
- Before lecture 1 on 13.9: Chapter 2: Which DNA Patterns Play the Role of Molecular Clocks? (Randomized Algorithms)
- Before lecture 2 on 20.9: Chapter 3: How Do We Assemble Genomes? (Graph Algorithms)
- Before lecture 3 on 27.9: Chapter 5: How Do We Compare Biological Sequences? (Dynamic Programming)
- Before lecture 4 on 4.10: Chapter 6: Are There Fragile Regions in the Human Genome? (Combinatorial Algorithms)
- Before lecture 5 on 11.10: Chapter 9: How Do We Locate Disease-Causing Mutations? (Combinatorial Pattern Matching)

### Tasks

#### Study group 0

Read the material described in the assignments below before the study group meeting on Monday 9.9.

#### Exercise 1

Solve Rosalind problems BA1B, BA1C, BA1D, BA1E, BA1F, BA1H, BA1I,BA1J. Submit your solution to the Rosalind system before the exercise session on Thursday 12.9. and be prepared to present your solution.

To get started, a solution to the problem BA1B is provided below. (The file is python code but is called ba1b.txt because .py ending is not allowed.)

#### Study group 1

Read the material assigned to you (by your last name) before the study group session on Monday 16.9.

#### Exercise 2

Solve Rosalind problems BA2H, BA2B, BA2C, BA2D, BA2E, BA2F, and two additional problems below, before the exercise session on Thursday 19.9. and prepare to present your solutions.

#### Study group 2

Study the material assigned to you (by your *first* name) before the study group session on Monday 23.9.

#### Exercise 3

Solve Rosalind problems BA3A, BA3B, BA3D, BA3F, BA3G, BA3H before the exercise session on Thursday 26.9. and prepare to present your solutions.

#### Study group 3

Study the material assigned to you (by the *2nd* character of your *first* name) before the study group session on Monday 30.9.

#### Exercise 4

Solve the two additional problems below and the Rosalind problems BA5G, BA5C, BA5E, BA5F, BA5H, BA5I before the exercise session on Thursday 3.10. and prepare to present your solutions.

To help with problems BA5E and BA5F, python code for reading in the BLOSUM/PAM scoring matrix is provided below.

#### Study group 4

Study the material assigned to you (based on the length of you *last* name) before the study group session on Monday 7.10.

#### Exercise 5

Solve Rosalind problems BA6A and BA6B and the three additional problems before the exercise session on Thursday 10.10. and prepare to present your solutions.

#### Study group 5

Read the material assigned to you (by your first name) before the study group session on Monday 14.10.

#### Exercise 6

Solve the Rosalind problems BA9A, BA9B, BA9G, BA9I and the two additional exercise problems given below before the exercise session on Thursday 17.10., and be prepared to present your solutions.

### Conduct of the course

The course follows a weekly cycle consisting of the following steps for the students:

1. Watch lecture videos before lecture

2. Attend lecture on Friday. Prepare to ask questions raised by the videos.

3. Read the study group materials at home.

4. Attend study group session on Monday. Prepare to discuss the study group material.

5. Solve the exercises at home.

6. Attend exercise session on Thursday. Prepare to present your solutions.

To pass the course, the student needs to:

1. Attend all study group session. If you cannot attend a particular session, you need to submit a compensatory assignment to the course moodle.

2. Solve at least 30% of the exercises.

3. Take the course exam.

Grading:

The maximum score for the exam is 48 points. An additional 12 points can be earned through solved exercises (30%->1p,85%->12p, linear scale). The grading is based on the total points (30/60->1, 50/60->5, depending on the difficulty of the exam).

### Feedback

We had a feedback session after the course exam, where couple of students participated. Anonymous feedback form was submitted by 14 students (that is, almost all who took the exam), and the statistics are shown below (scale 1-5 with 5 being strongly agree).

Anonymous textual feedback contains very good ideas how to improve the course. Study groups were frequently mentioned as the most useful part of the course. Exercise sessions could be flipped into workshops rather than checking the final solutions. Exam was a bit challenging due to its misalignment with coding exercises.

These considerations will be taken into account in the next edition, which is actually a new course that will replace this one: Elements of Bioinformatics, Autumn 2020.

Thanks everyone for very active attendance to the course and for excellent feedback!

***

The objectives of the course were clear to me from the beginning ("I knew what to learn")

4.07

The material used in the course (eg assignments, lecture material, other literature) supported the achievement of learning goals

4.5

Activity at the course (eg scheduling, guidance, other lessons) supported the achievement of learning goals

4.36

Assessment of the course (eg exercises, work, experiments, their relationship) measured the achievement of the core learning objectives

4.07

The course was laborious

4.07

I give the course as a whole the grade

4.14

### Description

Master's Programme in Life Science Informatics is responsible for the course.

Module where the course belongs to:

- Algorithmic bioinformatics

The course is available to students from other degree programmes.

Basic programming skills

Other courses in Algorithmic Bioinformatics study track

Describes the biological motivation, formulation as an algorithmic problem and a solution using basic algorithmic techniques of several computational problems in molecular biology. Solves small instances of the problems by simulating the algorithms and implements simple algorithms.

First or Second year, no prerequisite courses.

The course is offered in autumn, period 1, every second year (odd years)

The course introduces some basic algorithmic concepts and techniques through motivation by selected computational molecular biology problems.

The course follows the book: Phillip Compeau and Pavel Pevzner: Bioinformatics Algorithms - An Active Learning Approach. Active Learning Publishers, 2014.

An older course book covers a lot of the same topics: Neil C. Jones & Pavel A. Pevzner: An Introduction to Bioinformatics Algorithms. MIT Press, 2004.

The following is the current plan for Autumn 2017: teaching methods may evolve from year to year.

One chapter of the course book is covered in a one week period consisting of a lecture, a study group and exercises.

The lecture gives an overview of the topic. During the study group, students discuss additional material such as scientific articles, which they have read in advance.

To test their learning, students are given exercises, which they solve at home and then present and discuss during exercise session.

The following is the current plan for Autumn 2017: assesment practices may evolve from year to year.

Grading scale is 1...5.

One can earn up to 12 points from exercises and up to 48 points from course exam, up to 60 points in total.

Alternatively, one can earn up to 60 points from a separate exam, offered outside the course's contact teaching periods.

One should obtain 30 points to pass the course with grade 1. Grade 5 is obtained with 50 points out of the maximum 60. Linear scale is applied for other grades.

Deviations from the scheme are possible depending on the difficulty of the exam.

The contact teaching consists of weekly lectures, study groups and execises. Activive participation into the study groups and completion of sufficient number of exercises in addition to the course exam is required to pass the course as specified later.

Alternatively one can take a separate exam.