Genomics

6 EC

Semester 1, period 1

5234GENO6Y

Owner Master Biomedical Sciences
Coordinator dr. M.J. Jonker
Part of Master Biomedical Sciences, track Oncology, Master Biomedical Sciences, track Cognitive Neurobiology and Clinical Neurophysiology, Master Biomedical Sciences, track Psychopharmacology and Pathophysiology, Master Biomedical Sciences, track Infection and Immunity, Master Biomedical Sciences, track Cell Biology and Advanced Microscopy, Master Biomedical Sciences, track Experimental Internal Medicine, Master Biomedical Sciences, track Molecular Neurosciences, Master Biomedical Sciences, track Physiology of Synapses and Networks, Master Biomedical Sciences, track Developmental and Therapeutic Biology, Master Biomedical Sciences, track Medical Biochemistry and Biotechnology, Major Big Biomedical Data Analysis, year 1

Course manual 2021/2022

Study materials

Literature

  • Available on Canvas

Practical training material

  • Available on Canvas

Software

  • R or RStudio. All other software will be provided

Objectives

  • Explain the basic principles of genomics technologies.
  • Advanced scripting skills for the relevant programming languages; R and Linux bash.
  • Explain the statistical concept(s) underlying to some selected relevant methods and tools that are used for genomics data analysis.
  • Explain the principles of some selected relevant bioinformatics methods and tools that are required for analyzing and interpreting large scale genomics data sets.
  • Demonstrate that he/she can use selected relevant bioinformatics methods and tools in a correct way, and such that answers can be formulated to biomedical research questions.
  • Demonstrate that he/she can formulate data analysis questions, generate results, and interpret the results such that these data analysis questions can be answered.
  • Demonstrate that he/she can experiment with large scale omics data sets in a data-driven research approach.

Teaching methods

  • Lecture
  • Computer lab session/practical training
  • Presentation/symposium
  • Self-study
  • Supervision/feedback meeting

Lecture: Theoretical background.

Computer lab session/practical training: Training in using software, computer languages, big data analysis, data visualization and statistics.

Presentation: Formulating answers to biomedical and biological research questions.

Self-study: Training in using software, computer languages, big data analysis, data visualization and statistics.

Working independently on a project: Learning how to use genomics data analysis and bioinformatics to answer biomedical and biological research questions.

Learning activities

Activity

Hours

Laptop practicals

150

Self study

18

Total

168

(6 EC x 28 uur)

Attendance

Requirements of the programme concerning attendance (OER-B):

  1. Attendance during practical components exercises is mandatory.

Additional requirements for this course:

Attendance during practical components exercises is mandatory.

Absence must be reported to the coordinator.

Assessment

Item and weight Details

Final grade

0.5 (50%)

Research Project

0.2 (20%)

Drylab Journal

0.3 (30%)

Presentation

Fraud and plagiarism

The 'Regulations governing fraud and plagiarism for UvA students' applies to this course. This will be monitored carefully. Upon suspicion of fraud or plagiarism the Examinations Board of the programme will be informed. For the 'Regulations governing fraud and plagiarism for UvA students' see: www.student.uva.nl

Course structure

WeeknummerOnderwerpenStudiestof
1
2
3
4
5
6
7
8

Timetable

The schedule for this course is published on DataNose.

Contact information

Coordinator

  • dr. M.J. Jonker