Pharmaceutical Bioinformatics for Drug Discovery and Development

7.5 credits

Syllabus, Master's level, 3FF042

Code
3FF042
Education cycle
Second cycle
Main field(s) of study and in-depth level
Bioinformatics A1N, Drug Discovery and Development A1N, Pharmaceutical Sciences A1N
Grading system
Fail (U), Pass (G), Pass with distinction (VG)
Finalised by
The Educational Board of Pharmacy, 12 October 2023
Responsible department
Department of Pharmaceutical Biosciences

General provisions

The course is a part of the Master Programme in Drug Discovery and Development.

Entry requirements

150 credits, including 120 credits in biomedicine, pharmaceutical science, chemistry, drug discovery, natural science and/or engineering. Proficiency in English equivalent to the Swedish upper secondary course English 6.

Learning outcomes

After having completed the course, the students should be able to:

  • describe bioinformatics tools and methods and how they can be used within pharmaceutical research
  • use bio- and cheminformatics programs for e.g. sequence analysis, expression analysis, and structure-activity relationship based methods
  • configure, populate and extract information from relational databases with Structured Query Language (SQL)
  • locate relevant information in biological and chemical databases
  • train, validate and use predictive models based on biochemical data
  • describe and carry out basic sequence analysis tasks
  • describe questions regarding systems biology and biological networks

Content

The course contains theory and methods for bioinformatics analysis and the basics of how bioinformatics can be used within the pharmacutical area. The course presents introduction and historical account of pharmaceutical bioinformatics, representation of biological and chemical data in computers, biological and chemical databases, theory and methods for analysis of experimental data, sequence analysis, expression analysis, predictive modelling, mode! validation, design of experiments, structure-activity relationships, deep learning and applications in pharmaceutical bioinformatics. The course starts with a short intense introduction to Linux and working with computer clusters. For computationally demanding analysis high performance computing resources will be used.

Instruction

Teaching is in the form of lecture and computer exercises. Compulsory parts: computer exercises and assignments. The course is given in English.

Assessment

Passed course demands a passed written individual examination (4.5 hp) and passed compulsory parts (1+1+1 hp). Completion of compulsory parts of the course may be done earliest at next course instance, if space permits.If there are special reasons for doing so, an examiner may make an exception from the method of assessment indicated and allow a student to be assessed by another method. An example of special reasons might be a certificate regarding special pedagogical support from the University's disability coordinator.

Other directives

The course can not be combined with Pharmaceutical bioinformatics 3FF575 or 8FF575, and pharmaceutical bioinformatics with sequence analysis 3FF276 due to overlap in course contents.

No reading list found.

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