Due to the Corona Virus the information regarding study and examination for semester 2 (block 3 and 4) is not up-to-date. For the latest news please check the course page in Blackboard/Brightspace.

Prospectus

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Computational Molecular Biology

Course
2019-2020

Admission requirements

Not applicable.

Description

The course will cover the approaches, algorithms and practical aspects of Computational Molecular Biology and the closely related fields of genomics and transcriptomics. In particular, the following topics will be covered:

  • RNA structure prediction (secondary and tertiary structure prediction, RNomics)

  • Protein structure prediction (homology modeling, fold recognition, ab initio methods)

  • Biopolymer design

  • Modeling of molecular interactions (molecular docking)

  • Genomic and transcriptomic analysis pipelines

  • Protein functional analysis

  • Protein interaction networks

In addition to lectures, the course will include practical assignments for hands-on experience with computational tools used in Molecular Biology.

Course objectives

By the end of the course students will have acquired an understanding of the strategies and algorithms used in Computational Molecular Biology and have an understanding of the main challenges in the field. They will also gain practical experience in working with commonly used computational molecular biology tools and resources.

Timetable

The most recent timetable can be found at the students' website.

Mode of instruction

  • Lectures

  • Assignments

Course load

Total hours of study: 168 hrs.
Lectures: 26:00 hrs.
Practical work: 60:00 hrs.
Tutoring: 6:00 hrs.
Examination: 3:00 hrs.
Other: 73:00 hrs.

Assessment method

Assignments and a final exam. The grade will be based on exam (60%) and assignments (40%).

Reading list

The syllabus with literature references and links to Internet resources will be distributed at the start of the course.

Registration

You have to sign up for classes and examinations (including resits) in uSis. Check this link for more information and activity codes.

Contact information

Lecturers: dr. Katy Wolstencroft & dr. Alexandre Goultiaev

Remarks

None.