Examination
Examination is done using four sets of homework which will require the
student to develop skills and knowledge in the course contents.
The course handbook lists the course objectives as ability to...
- implement, describe, and discuss the algorithms treated during the course as well as how they relate to each other,
- apply the fundamental algorithm design methodologies dynamic programming, MCMC, and EM to problems in computational biology and bioinformatics,
- apply, describe, and discuss the modeling principles parsimony, maximum likelihood, and bayesian modelling.
We will try to "encode" these objectives in homework problems. The
problems can be partitioned into three classes,
General,
Implementation, and
Algorithms, and to get a good grade you will
have to do well in all three classes.
Grading
The four homeworks gives scores on three different subjects:
General, Implementation, and Algorithm. It is not yet decided
what the maximum score is, so we are giving the grading criteria
in relative terms.
To pass the course and get at least an E, you need to get more than
50 % of general scores on each homework. All homeworks must be
on time for a grade higher than E.
By doing well on the Implementation and Algorithm scores, you can earn Titles. For every title you earn, you raise your grade one step.
Implementation scores
>50 % earns the title "Implementor of Bioinformatics Algorithms"
>75 % earns the title "Master Implementor of Bioinformatics Algorithms"
Algorithm scores
> 50 % earns the title "Designer of Bioinformatics Algorithms"
> 75 % earns the title "Master Designer of Bioinformatics Algorithms"