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Structural Bioinformatics (2KV)

Course no.: 365.082
Lecturer: Alois Regl (alois.regl@regl.net, +43 664 4502030)
Pre-meeting: Tue March 5, 2019 (room S3 057)
Times/locations: Tue 8:30-11:00, room see S3 057 
Fri 8:30-11:00, room see S2 053
The final schedule for both lectures (Structural Bioinformatics/Genome Analysis & Transcriptomics) will be presented on Tue March 5, 2019
Start: Tue March 5, 2019
Mode: KV, 2h, weekly
Registration: KUSSS, öffnet eine externe URL in einem neuen Fenster

It is deeply recommended to hear both lectures (Structural Bioinformatics and Genome Analysis & Transcriptomics).

Lecture notes:

There are no lecture notes but all slides will be provided via KUSSS.

Please pay attention to the Big Picture provided in KUSSS!!!

Motivation and course outline

Bioinformatics is an interdisciplinary field at the interface of life sciences and computational sciences that deals with the development and application of methods for storing, retrieving, and, in particular, analyzing biological data. The massive data amounts produced by recent and currently emerging high-throughput biotechnologies provide unprecedented potentials, but also pose yet unseen computational challenges – making bioinformatics an essential success factor for the advancement of fields, such as, molecular biology, genetics, medicine, and pharmacology.

The goal of this course is to provide an overview of foundational and computational aspects of 3D structures of biological macromolecules, such as, DNA, RNA, and proteins. The main goal of structural bioinformatics is to provide computational approaches for predicting and analyzing 3D structures. Understanding the 3D structures of biological macromolecules is crucial for understanding their function. Applications of structural bioinformatics are oriented towards medical fields and pharmacological research, especially, drug design.



  • Databases for 3D structures and molecular viewers
  • Structure prediction (threading, ab initio prediction, molecular dynamics)
  • Structural alignments
  • Protein classification
  • Motif search
  • Functional and structural annotation

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