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Courses of the Bioinformatics Master
Fall year 1:
- Bioinformatics, KB7004, 7.5 ECTS
Course page
Arne Elofsson
The amount of available data in life sciences is rapidly increasing.
and to use this data in the best possible way is rapidly becoming one
of the corners stones in all biological research. In the future, or
already today, we believe it will only be possible to become a
successful life science scientist if you, in addition to your own
data, fully can use data available from large scale studies. In this
course we will cover the basic bioinformatical methods to analyze
protein sequence and protein structure. The goals are that after this
course you should be able to use state of the art methods to predict
the function and structure of an unknown protein sequence.You will
learn to use and understand the basic tools in bioinformatics,
including tools for: Sequence searching, Sequence alignments,
Secondary structure, Fold recognition, and Homology modeling.
- Structural biochemistry, KB7002, 7.5 ECTS
Course page
Martin Högbom
The course covers basic concepts in structural biochemistry and the
experimental methods used to determine biological macromolecules at
the molecular level. The course also deals with the relationship
between structure and function from a molecular perspective and how
the structural knowledge has increased our understanding of important
biological processes.
- Molecular Modeling KB8005, 7.5 ECTS
Course page
Erik Lindahl
Modeling of biological systems at the molecular level is becoming
increasingly important. In this course we will provide an introduction
to methods that are used to in molecular modeling. Both methods using
quantum mechanical descriptions and classical descriptions will be
discussed. Methods that will be discussed include: Coordinate
systems, molecular graphics, hartree-fock, basis sets, semi-empirical
methods, Density Function Theory, Molecular Mechanics, Energy
Minimization, Molecular dynamics simulations, Monte Carlo
methods. Sequence Alignments.
- Applied bioinformatics DA7021, 7.5 ECTS
Course page
Course page 2010
Lars Arvestad
This is a course aimed at improving your efficiency as a
bioinformatician. Here you will learn practical methods that are
needed to produce good bioinformatical code, using tools such as
Bio-Python and related projects.
Spring year 1:
Period A-B:
- Protein Physics KB8011, 7.5 ECTS
Course page
Erik Lindahl This is an advanced level course
in collaboration between Stockholm University and KTH that covers
structure, self-organization, and function of the biological
macromolecules of life - primarily proteins. It covers the biophysical
chemistry of protein folding, denaturation, stability and function.
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Analysis of
Data from High-throughput Molecular Biology Experiments BB2490, 7.5 ECTS
Olof Emanuelsson and Lukas Käll
This is an advanced course in bioinformatics. The course contains the
fundamentals of bioinformatics analysis of large-scale data sets from
genomics and proteomics experiments (in particular, DNA sequencing and
mass spectrometry). The course consists of lectures and computer-based
laboratory exercises.
or
Omic Data and Systems Biology DD2399, 7.5 ECTS
Lars Arvestad
Modern high-throughput biology methods; popular tools for analysis of
omics data; algorithms and methods for analysis of omics data as well
as their implementation.
Period C (21/3-1/5):
- Structure Prediction of Globular and Membrane Proteins KB8008, 7.5 ECTS
Course page
Course page
Arne Elofsson In this course we use (and
develop) state of the art methods to predict the structure of globular
and membrane proteins. In particular we focus on the structure
prediction CASP process and analyze how we can solve one of the
hardest problems in biology today, predicting a protein structure from
its sequence. The course consist of three parts, lectures describing
different methods for structure prediction, a literature assignment of
CASP papers and a project aimed at the development of an improved
structure predictor. The course is based on weekly seminars and
assignments.
Period D (2/5-5/6):
- Comparative Genomics KB8007, 7.5 ECTS
Course page
Erik Sonnhammer Today the genome sequence of hundreds of
organisms is known, including our own genome sequence and that of many
closely related species. To understand human biology and orgins as
well as how life in general has evolved it is necessary to compare
these genomes. In this course you will learn how to compare genomes
using bioinformatical techniques such as phylogeny and orthology
prediction as well as other methods to understand the evolution of
genes and genomes. Moreover, you will learn how to do functional
annotation of proteins on the genome scale, and how to analyse the
interactome.
Year 2
- Master thesis project, normally
2 semesters (KB9018, 60 ECTS). It can also be 1.5 semesters (KB9017,
45 ECTS) or 1 semester (KB9016, 30 ECTS) and be complemented with
electable courses to obtain 60 ECTS in total.
- Electable courses, possible choices include:
- Statistics for scientists MT1001, 7.5 ECTS
Course page
- Algorithmic bioinformatics DD2450, 6 ECTS
- Quantitative systems biology DD2398, 7.5 ECTS
- Analysis of Data from High-throughput Molecular Biology Experiments BB2490, 7.5 ECTS
- Structure and dynamics of biological membranes KB8001, 15 ECTS
- Molecular properties of proteins KB8010, 15 ECTS
- Algorithms, Data Structures and Complexity DD1352, 9 ECTS
- Algorithms and Complexity DD2354, 6 ECTS
- Machine Learning DD2431, 6 ECTS
- Statistical Methods in Applied Computer Science DD2447, 6 ECTS
- Proteomics technology BB2320, 4.5 ECTS
- Applied gene technology BB2250 , 6 ECTS
- Pattern Recognition EN2200, 6 ECTS
- Information Theory and Source Coding EN2500, 7.5 ECTS
- Optimization SF1811, 6 ECTS
- Statistical Theory SF2960, 6 ECTS
- Computer Intensive Methods in Mathematical Statistics SF2955, 7.5 ECTS
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