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Applied Computational Biology


Technical University of Denmark


General course objectives:
This course covers state-of-the-art methods in computational molecular biology. Topic areas include research in cutting-edge biotechnology sequencing data types, sustainability, medical genomics, deep learning models for molecular datasets, and large-scale multi-omic methods. Recent research by course participants is also covered. There may also be a project presentation and/or a small number of assignments.

Learning objectives:
A student who has met the objectives of the course will be able to:
  • Understand data characteristics in molecular biology at DNA, RNA, proteins and regulatory level
  • Possess tricks to integrate and process multiple data types (for example, in cancer genomics, sustainability)
  • Make use of data integration strategies using deep learning and/or basic algorithm techniques.
  • Make applications in the real-world in engineering strains for bio-based chemical production
  • Long-read sequencing technologies and multi-omic analyses
  • Hi-C sequencing technologies and analyses
  • General statistical techniques in molecular biology
  • Genome assembly methods

Contents:
Day 1 Computational molecular biology: challenges and methods Day 2 Third-generation sequencing and multi-omic methods Day 3 Strain design: methods and applications in sustainability Day 4 Graph-based methods for molecular biology problems Day 5 Rewriting genomes, spatial technologies and data science

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Course organizer
Shilpa
Place/Venue
Anker Engelunds Vej 1
City
2800 Kgs. Lyngby
Country
Denmark
Workload
5
Link
http://kurser.dtu.dk/course/29906