Computation for Biologists
Course infoSchedule
Course moduleNWI-BM066A
Credits (ECTS)6
Category03 (Advanced)
Language of instructionEnglish
Offered byRadboud University; Faculty of Science; BioWetenschappen;
dr. S.J. van Heeringen
Other course modules lecturer
dr. S.J. van Heeringen
Other course modules lecturer
Contactperson for the course
dr. S.J. van Heeringen
Other course modules lecturer
dr. S.J. van Heeringen
Other course modules lecturer
Academic year2020
KW1  (31/08/2020 to 01/11/2020)
Starting block
Course mode
RemarksMaximum capacity: 75.
Priority for compulsory course-students (Med.Epi-specialisation)
Registration using OSIRISYes
Course open to students from other facultiesYes
Waiting listYes
Placement procedureIn order of Study programme
ExplanationIn order of Study programme
At the end of this course you can:
  • implement an integrative computational analysis to test a biological hypothesis using high-throughput (epi)genomic and proteomic data;
  • write a simple Python program to read and process big, text-based data files;
  • design and implement simple algorithms to gain biological insights from data;
  • use Python in combination with command line tools to perform critical exploratory analysis of high-dimensional data;
  • visualize complex biological data and analysis results at the genomic level to understand biological systems.
Technological advances in the fields of genomics and proteomics have accelerated the ease and speed of data collection. High-throughput instruments, such as DNA sequencers and mass spectrometers, generate large amounts of biological measurements. This has brought the goal of understanding gene regulation within a living cell at the systems levels much closer. However, to integrate and analyze these various big data sets, a quantitative approach to biology is needed.

In this course you will learn to apply the Python programming language in combination with the Pandas data analysis framework to analyze (epi)genomic and proteomic data. The course will deal with a complete view of data analysis, from reading and processing raw data files to interpretation and visualization within the biological context.

Instructional Modes
  • Lecture
  • Self-study

Presumed foreknowledge
  • Knowledge of the principles of genome architecture and gene regulation (NWI-BB064B or Lodish 7th edition chpt 5-7 or equivalent)
  • Basic statistics (NWI-MOL028 or equivalent)
  • Practical knowledge of Linux and the Bash shell and the ability to use the command-line to manipulate common genomics data files (NWI-BB086 or the on-line edX course “Introduction to Linux” or equivalent).
  • Test information
    - (computer) exam, 100%
    • Please note that every student that enrols in this course will be placed on the waiting list. 
    • If the maximum capacity is exceeded, (first year) students in the Medical Epigenomics specialisation have priority and will be enroled. This cannot be done before the enrolment deadline for the course has ended, so please make sure to enrol for a back-up course in time! 
    Required materials
    Lecture slides and hand outs will be provided during the course (via Brightspace)

    Instructional modes
    computer practical
    Attendance MandatoryYes

    Attendance MandatoryYes

    Test weight1
    Test typeExam
    OpportunitiesBlock KW1, Block KW2