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Klinisk institutt 1
Kurs

NEUROSYSM930 - Applied bioinformatics and data analysis in medical research

Learn to apply bioinformatics and data analysis in clinical research on human tissue.

Futuristic illustration of a brain and data analysis.
Foto/ill.:
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Hovedinnhold

The course will focus on practical aspects and methodological considerations that needed to be taken into account when dealing with human derived data, such as data sensitivity, limited sample sizes, sample misclassification, choice of appropriate statistical models, and covariates, and tissue heterogeneity. The course will be composed of seminars, lectures, and hands-on tutorials given by clinicians and researchers based on real-life scenarios. The course will provide an inspiring environment, promoting networking between trainees and researchers, promoting career development, and encouraging future collaborations.

Who: The course will be highly beneficial for all participants with an interest in bioinformatics, biology, medicine, or clinical research in general. It is open to researchers, postdocs, PhD students, master students, students enrolled in the Medical Student Research Program, and others interested in the topic. A basic knowledge of statistics is required. Familiarity with next-generation sequencing and a basic understanding of molecular biology and/or genetics are desirable.  

Place: Campus UiB / Haukeland University Hospital, personal attendance.

When: November 9-11, 2022. Lunch will be provided.

Deadline for registration: September 1. Non-UiB students register through Søknadsweb, and UiB students register through Studentweb. If you don’t need the study points, you can register for non-ECTS participation through this link.

Program: not yet available, will be available on this page.

ECTS: 3, for full attendance in the course including the tasks. 

Organizers: Dr. Kim Brügger, Dr. Fiona Dick, Dr. Gonzalo Nido and Dr. Lilah Toker have the academic responsibility. Research Fellow Haakon Reithe is coordinator of the course.

Contact: kim.brugger@uib.no

More information and pre-reading list: on this website