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Computational Molecular Biology Spring 2019 ( Last update: 17-6
2019 ) |
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Organizer: Dr. Alexander P. Goultiaev and Dr Erwin M Bakker Assistant: -
Period: February - May 2019 Place: Room 401 (LIACS, Snelliusgebouw) Time: Tuesday 13.30 - 15.15
ECTS: 6
Description:
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. RNA structure
prediction will be discussed whereby methods based on
energy minimization, comparative analysis as well as
folding simulations are covered. 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, bio polymer
design, and protein protein docking and interaction
will be studied.
Grading: There will be several assignments and a final exam. The grade will be based on the assignments (40%) and the exam (60%). The grade for the exam should always be greater than 5. 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. Furthermore, 4 sets 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.
Exam:
Retake:
Schedule (tentative, will be regularly update, please check before each lecture!:
Note: Slides or reading materials will be available the day before the lectures.
Assignments:
------------------------------------------------------------------------------------------------------------------------------------------- Exam Materials (Please note: This list is tentative, it will be updated after each lecture!)
Lecture 1
End Exam Materials -------------------------------------------------------------------------------------------------------------------------------------------
Other Self-Study Materials (will not be examined):
Links: Databases publicly available on the web:
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