Forår
Syv hele tirsdage i forårssemesteret. Første gang den 1.
marts.
Undervisningens placering:
Campus Lyngby
Kursets varighed:
[Kurset følger ikke DTUs normale
skemastruktur]
Evalueringsform:
Hjælpemidler:
Bedømmelsesform:
Pointspærring:
Deltagerbegrænsning:
Minimum 6 Maksimum: 30
Overordnede kursusmål:
The student should be able to use bioinformatic tools in the UNIX
environments at DTU Lyngby and Risø campus supercomputers, as well
as on their own laptops.
Læringsmål:
En studerende, der fuldt ud har opfyldt kursets mål, vil kunne:
log on the supercomputers at the Risø and Lyngby campuses. Be
familiar with the strengths and weaknesses of each computer
including their own laptop.
use basic UNIX commands ls (+command line options), cd, mv, cp,
rm, etc. Know about good coding practices.
be familiar with the use of machine learning methods, PSSM,
SMM, ANN (shallow and deep), for construction of prediction tools
for B and T cell epitopes.
Install R on personal computer and on a UNIX server and be
familiar with installing packages.
Understand the benefits and problems with different versions of
R. Do basic statistics in R, Students t-test, ANOVA, Pearson’s R,
AROC, etc.
Use R for Plotting 1D and 2D clustering, and plotting in
R.
The students should be familiar with NGS technologies, Data
basics and trimming, Mapping with bwa, De novo assembly with ,
Base/variant calling, Basic NGS file formats fasta, fastq, SAM,
BAM, CRAM, vcf
Use methods for structure prediction and visualisation. Use
tools for protein structure prediction Visualise of protein
structure with PyMol Transfer information from gene or protein
information to protein structure visualisation
Kursusindhold:
The supercomputers at the Risø and Lyngby campuses. UNIX commands
and good coding practices. Using R. Machine learning methods. NGS
technologies. Methods for structure prediction and
visualisation.
