Research Education Subject
- Medical Science
The overall aim of the course is to teach hands-on state-of-the-art analysis of high-throughput molecular datasets (OMICs) towards the development of diagnostic biosignatures. No programming knowledge is needed. Participants will analyze their individual gene expression dataset using univariate and machine learning methods. Software used in this course is RStudio and some of the packages within Bioconductor. Running the course on students' own laptops will be supported.
The course language is English.
The course will be given in spring 2020, during the weeks 6-8 (three preparation days) and during the weeks 9-11 (fulltime weeks).
To gain access to the course and complete the examinations included in the course, the applicant must be admitted to doctoral education at Örebro University. Applicants enrolled at another university can participate in availability.
Application is closed.