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Course module: BMB521219
BMB521219
Cancer Genomics
Course info
Course codeBMB521219
EC3
Course goals
At the end of the course, the student has a profound understanding of:
•      The applications and challenges of next-generation sequencing in cancer genomics
•      Key concepts and developments in cancer genomics research
 
At the end of the course, the student is able to:
•      Apply bioinformatics tools to detect, visualize and interpret genomic alterations in tumors
•      Use molecular data for annotation and interpretation of tumors
 
Content
Period: 7 May - 20 May 2020, see www.CSnD.nl/courses

Course Coordinator: Dr. Josephine Daub, Princess Máxima Center for Pediatric Oncology, Utrecht (J.T.Daub@prinsesmaximacentrum.nl)
 
Faculty
Dr. Jayne Hehir-Kwa, Princess Máxima Center for Pediatric Oncology, Utrecht
Dr. Patrick Kemmeren, Princess Máxima Center for Pediatric Oncology, Utrecht
Lecturers from the Máxima Center, UMCU, UU, Hubrecht Institute, Hartwig Medical Foundation
Description of content
  • Introduction to Next-Generation Sequencing (NGS) and Cancer genomics
  • Detection, visualization, interpretation and annotation of somatic variants in tumors, including single nucleotide variants (SNVs), copy number variations (CNVs) and structural variants (SVs)
  • RNA sequencing based analysis
  • Genome browsers and cancer specific databases
  • Invited lectures covering current advances in Cancer Genomics research, e.g.:
    • Mutational signatures
    • Single cell transcriptomics
    • Tumor classification
    • Survival analysis
    • Genetic interactions
    • Pathway and Network analysis
 
Literature/study material used:
Handouts of lectures and practical assignments
Research papers
CoCalc computing environment
Online resources and documentation
Course laptop (students should bring their own)
 
Registration:
You can register for this course via Osiris Student. More information about the registration procedure can be found here on the Studyguide.
 
Mandatory for students in own Master’s programme 
No.
 
Optional for students in other GSLS Master’s programme:
 Yes.

Prerequisite knowledge:
  • Basic-level experience with programming in R and with working in a Unix/Linux environment
  • Basis understanding of bioinformatics and cancer biology
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