The course will cover both algorithms as well as practical aspects within the field of computation molecular biology. Important basic algorithms for pair wise alignment, computations of phylogenic trees, physical mapping of sequences, gene finding, multiple sequence alignment, heuristic sequence alignment and exact string matching will be discussed. Furthermore, the important field of protein structure prediction will be covered with the study of homology modeling, fold recognition, knowledge based potentials and ab initio methods for structure prediction. Finally RNA structure prediction will be discussed whereby methods based on energy minimization, comparative analysis as well as folding simulations are covered.
At the end of the course, students:
- Will have acquired a thorough understanding of the basic algorithms for:
- Sequence alignment
- Models and Machine learning algorithms for bio-sequences.
- Profile and multiple alignment
- Protein secondary and tertiary structure prediction
- Next generation sequencing data processing
- Will have acquired hands-on experience with several molecular biology applications of the important methods using the above listed algorithms.
The most recent timetable can be found at the LIACS website
Mode of instruction
“There will be several assignments and a final exam. The grade will be based on the assignments (40%) and the
exam (60%). The final grade will be determined using the formula: final grade = 0.6 * grade for the exam + 0.25 *
grade for the lab assignments + 0.15* the final assignment, where the grade for the exam should be >5.
Furthermore, after 4 lectures a set of lecture-assignments related to the contents of the slides will be handed out.
These will be graded either sufficient or insufficient. At least 3 of the 4 sets should be graded sufficient in order to
obtain a final grade.”
Slides and other materials available on the website
You have to sign up for classes and examinations (including resits) in uSis. Check this link for more information and activity codes.
Study coordinator Computer Science, Riet Derogee