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Advanced Algorithms for Computational Biology

Course Description

This course is for bioinformatics students and researchers who want to deepen their informatics skills and understanding. The course builds upon basic algorithms and data structures up to the state-of-the-art methods in computational biology (focusing on sequence alignment).

The central problems of the course will be sequence alignment and pangenomics․ The course will cover graph algorithms, string data structures, hashing techniques, theoretical analysis, and modern heuristic approaches.

The course assumes solving 1-2 coding problems every week. Additionally, research tasks will be available as bonus topics for students who are interested in further exploration.


Pesho Ivanov, PhD Student, ETH Zurich

Pesho studied applied mathematics and informatics in Sofia and Moscow. He enjoys solving and discussing olympiad informatics problems. In the last 10 years, he is mostly interested in modeling and solving biological problems using combinatorial algorithms. Pesho used to work as a teacher and a programmer, and happened to do projects on single-cell RNA-seq on T-cell receptors, phylogenetic tree intersection, and assembly scaffolding. Currently finishing his PhD program in ETH Zurich with a thesis on Optimal sequence alignment using the A* shortest path algorithm.

Who is the Course For?

The course is for those who already have some experience writing discrete algorithms and want to deepen it to state-of-the-art approaches in computational biology.


For the completion of the course, it is required to have written dynamic programming solutions for global (Needleman-Wunsch) and local alignment (Smith-Waterman), to think in asymptotic runtime, and feel comfortable coding in any programming language. The course will be in English.

Course Outline

Below is a summary of the topics covered in the course.

  • Central problems: Sequence alignment (global, semi-global, local, suboptimal, MSA), Assembly, Pangenomics
  • Algorithms: Exact, approximate, probabilistic, heuristic algorithms; Greedy, Minimizers
  • Data structures: Genome graph, Suffix tree and suffix array, Bloom filter, HMMs
  • Concepts: Heuristic, Matroid, Amortized analysis, average-case asymptotics, Evaluation
  • Optimizations: Four Russians method, Bit-parallel
  • Tools: State-of-the-art aligners (minimap2, Edlib, WFA, AStarix, A*PA, GraphAligner)
  • Homeworks: solve problems, edit a Wikipedia page in computational biology
  • Bonus: Genetic algorithms, research tasks on request

Venue and Details

Location: ABI
Format: Offline

Start date: 28th of February

Duration: 2 months, once a week, 3 hours.
Tuesday: 10:00-13:00


In order to get enrolled in the course, you need to fill in our registration form and wait for confirmation (a limited number of places are available for participation), after the confirmation email the participant should transfer the Course fee via Donation.

The registration deadline is 26th of February.

Course Fee

  • MSc students – 10 000 AMD
  • BSc students – 5 000 AMD
  • Industry – 25000 AMD

Please make sure to add comment and or description to your transfer by using this form:


Contacts: [email protected]

*You are invited to sign up at the ABI Student Chapter for more information and activities like this.