BB2491 Analysis of Data from High-Throughput Molecular Biology Experiments 7.0 credits

Analys av data från storskaliga molekylärbiologiska experiment

  • Educational level

    Second cycle
  • Academic level (A-D)

  • Subject area

    Biotechnology
  • Grade scale

    A, B, C, D, E, FX, F

Course offerings

Autumn 17 TMTLM for programme students

  • Periods

    Autumn 17 P2 (7.0 credits)

  • Application code

    50463

  • Start date

    2017 week: 44

  • End date

    2018 week: 3

  • Language of instruction

    English

  • Campus

    AlbaNova

  • Number of lectures

    11 (preliminary)

  • Number of exercises

  • Tutoring time

    Daytime

  • Form of study

    Normal

  • Number of places *

    Min. 7

    *) The Course date may be cancelled if number of admitted are less than minimum of places.

  • Course responsible

    Lukas Käll <lukask@kth.se>

  • Teacher

    Olof Emanuelsson <olofem@kth.se>

Autumn 16 TMTLM for programme students

  • Periods

    Autumn 16 P2 (7.0 credits)

  • Application code

    50067

  • Start date

    2016 week: 44

  • End date

    2017 week: 3

  • Language of instruction

    English

  • Campus

    AlbaNova

  • Number of lectures

    11 (preliminary)

  • Number of exercises

  • Tutoring time

    Daytime

  • Form of study

    Normal

  • Number of places *

    Min. 7

    *) The Course date may be cancelled if number of admitted are less than minimum of places.

  • Schedule

    Schedule (new window)

  • Course responsible

    Lukas Käll <lukask@kth.se>

  • Teacher

    Olof Emanuelsson <olofem@kth.se>

Intended learning outcomes

After passing the course, the student should be able to:

1. Describe widely used high-throughput experimental techniques employed to investigate the DNA, RNA, and protein contents of a cell, tissue, or organism.

2. Explain the theory of state-of-the-art tools/algorithms for processing data from high-throughput molecular biology experiments.

3. Choose appropriate tools for processing data from high-throughput molecular biology experiments.

4. Apply tools for processing data from high-throughput molecular biology experiments.

5. Interpret the results of these analyses in a biologically or medically relevant context.

6. Reflect over the choice of methods and tools and how it influences the outcome of the analyses.

Course main content

The course contains the fundamental theory of bioinformatics analysis of large data sets from high-throughput genomics, transcriptomics, and proteomics experiments – in particular, massively parallel DNA sequencing and protein mass spectrometry: how this theory is implemented in state-of-the-art tools for analyzing the data; how these tools are applied on real high-throughput molecular biology data; and how the outcome of the analysis may be interpreted in a biologically or medically relevant context.

Eligibility

Admission requirements for programme students at KTH:
At least 150 credits from grades 1, 2 and 3 of which at least 100 credits from years 1 and 2, and bachelor's work must be completed.  The 150 credits should include a minimum of 20 credits within the fields of Mathematics, Numerical Analysis and Computer Sciences, 5 of these must be within the fields of Numerical Analysis and Computer Sciences, 20 credits of Chemistry, possibly including courses in Chemical Measuring Techniques and 20 credits of Biotechnology or Molecular Biology.

Admission requirements for independent students:
A total of 20 university credits (hp) in life science courses ( e.g. biochemistry, microbiology and gene technology/molecular biology). 10 university credits (hp) in mathematics and 3,5 university credits (hp) bioinformatics. Documented proficiency in English corresponding to English B.

Recommended prerequisites

The following courses, or equivalent, are recommended: Bioinformatics and basic probability theory corresponding to BB2440 Bioinformatics and Biostatistics, and probability theory corresponding to SF1901 Probability theory and statistics. Computer acquaintance equivalent to the course DD2404 Applied bioinformatics.

Literature

Scientific articles and web resources as assigned during the course. Handouts from the lectures.

Examination

  • LAB1 - Computer Exercises, 1.0, grade scale: P, F
  • PRO2 - Project, 6.0, grade scale: A, B, C, D, E, FX, F

No aids are allowed other than those specified in the course PM.

Requirements for final grade

The final grade on the course is determined by the grade on the project (PRO1, grade scale A-F) and the exam (TEN1, grade scale A-F). Passed grade also in the LAB1. There are parts of the course that has compulsory attendance.

Offered by

BIO/Biotechnology

Examiner

Lukas Käll <lukask@kth.se>

Version

Course syllabus valid from: Autumn 2016.
Examination information valid from: Autumn 2017.