CourseSpecifications
Valid as from the academic year 2024-2025

Computational Challenges in Bioinformatics (C003711)

Course size
Credits 6.0(nominal values; actual values may depend on programme)
Study time 180 h

Course offerings and teaching methods in academic year 2024-2025
A (semester 2)
EnglishGent

Lecturers in academic year 2024-2025
Dawyndt, Peter
Fostier, Jan

independent work
seminarlectureWE02
TW05

lecturer-in-charge
co-lecturer

Offered in the following programmes in 2024-2025
Master of Science in Teaching in Science and Technology(main subject Mathematics)
Bridging Programme Master of Science in Bioinformatics(main subject Engineering)
Master of Science in Bioinformatics(main subject Engineering)
Master of Science in Computer Science
Master of Science in Computer Science Engineering
Master of Science in Mathematics
Exchange Programme in Bioinformatics (master's level)
Exchange Programme in Computer Science (master's level)
Exchange Programme in Mathematics (master's level)

crdts
666666666offering
AA
A
A
A
A
A
A
A

Teaching languages
EnglishKeywords
Performance, compute intensive applications, big data, hardware acceleration, data structures
and algorithms, bioinformatics
Position of the course
The objective of this course is to focus on existing computational challenges in the field ofbioinformatics and the techniques that are applied in scientific literature to deal with thosechallenges. Both compute intensive and data intensive ('big data') problems are considered.
Even though the main focus of the course is on the software aspects, certain hardware
acceleration techniques are covered. The goal of this course is aimed at students that areinterested in software development in the field of bioinformatics.
Contents• Sequence alignment• • Needleman-Wunsch and Smith-Waterman algorithm, advanced variants• • Multiple sequence alignment• • Implementation aspects and hardware acceleration• Gene prediction• • Markov models• • Viterbi algorithm• String matching and applications• • Data structures and algorithms for string matching: suffix trees, suffix arrays, Burrows• • Wheeler transformation, FM index• • Applications to read mapping• Graph-based algorithms and applications(Approved)1• • De Bruijn graphs• • Application to genome assembly
Initial competences
Advanced programming skills in Java, Python or C/C++, advanced knowledge of datastructures and algorithms
Final competences
1 To understand the commonly used data structures and algorithms that are commonly used
1 in bioinformatics applications.
2 To understand the most important computationally intensive problems in bioinformatics and
1 the existing solutions (or heuristics) to solve them.
3 Being able to estimate the runtime and memory footprint based on the computational
1 complexity of the underlying algorithm and the size of the problem.
4 Being able to design advanced algorithms and software implementations based on standard
1 data structures and algorithms.
5 To take into account the computational feasibility when critically assessing several
1 algorithmic approaches.
6 To spend enough time on the design and the computational complexity evaluation prior to
1 the actual implementation of software.
7 To understand the tradeoffs between performance, memory footprint and accuracy.
Conditions for credit contract
Access to this course unit via a credit contract is determined after successful competences assessment
Conditions for exam contract
This course unit cannot be taken via an exam contract
Teaching methods
Seminar, Lecture, Independent work
Study material
Type: Slides
Name: Course slides
Indicative price: Free or paid by faculty
Optional: noLanguage : EnglishReferences• "Biological Sequence Analysis", Richard Durbin, Cambridge University Press, 1998
• "Algorithms on Strings, Trees and Sequences: Computer Science and Computational• Biology", Dan Gusfield, 2001
• "Bioinformatics Algorithms: Sequence Analysis, Genome Rearrangements, and Phylogenetic• Reconstruction", Enno Ohlebusch, Oldenbusch-Verlag, 2013.
Course content-related study coaching• By e-mail or after appointment• Additional information through Ufora
Assessment moments
end-of-term and continuous assessment
Examination methods in case of periodic assessment during the first examination period
Oral assessment, Written assessment
Examination methods in case of periodic assessment during the second examination period
Oral assessment, Written assessment
Examination methods in case of permanent assessment
Skills test, Assignment
Possibilities of retake in case of permanent assessment
examination during the second examination period is not possible
Extra information on the examination methods• Periodic evaluation: open-book examination (exercises), oral examination with written• preparation• Permanent evaluation: graded homework assignments (source code + report)(Approved)2

Calculation of the examination markFor both examination periods, the final mark will be composed as follows: 25% homeworkassignments, 75% exam. For both examination periods, a minimum score of 50% is required
for the examination part. If this condition is not fulfilled, the final mark for this course will belimited to 9/20.

(Approved)3