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. 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

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. 07. juli, 2016