Seminar 'Systems genetics, proteins, and diseases' WS18/19

 

Type  Seminar (2 SWS)
ECTS 4.0
Lecturer Burkhard Rost, Julien Gagneur et al
Time Monday, 12:00 - 13:30
Room MI 01.09.034
Language English

Application / Registration

Application is organised centrally for all bioinformatics seminars. After you have been assigned to our seminar, we will distribute the topics.

Content

Topics related to the research interests of the group: protein sequence analysis, sequence based predictions, protein structure prediction and analysis; interaction networks.

Pre-meeting

The Pre-meeting will be held on Jul 30th  at 1 p.m.  in Room MI 01.09.034

The rules and hints for preparation of the seminar discussed  in the pre-meeting are also summarised in our Checklist and on these slides (updated Jul 31th).


 

Final Schedule

The order is preliminary and will be adjusted soon. All talks will talk place during the lecture period. The timing will be announced soon.

Date Topic Supervisor Students
19.11. Protein localization prediction from evolutionary profiles Schelling Kaindl, Slawinska
26.11. Protein disorder — a breakthrough invention of evolution? Heinzinger Eska, Schütze
3.12. Transmembrane Proteins/PolyPhobius Bernhofer Descho, Ganswindt
10.12. Human 5′ UTR design and variant effect prediction from a massively parallel translation assay Gagneur Karollus, Wu
17.12.

-- cancelled --

Deep learning sequence-based ab initio prediction of variant effects on expression and disease risk

 Gagneur Li, Roller

 

 

 

Description of Topics

Protein localization prediction from evolutionary profiles

Maria Schelling

Identification of a protein’s subcellular localization is an important step towards elucidating its function. In this seminar, a machine-learning-based methods for predicting localization in prokaryotes and eukaryotes shall be presented. The methods incorporate a hierarchical ontology of subcellular localization classes. The predictions are derived from evolutionary infromation (Loctree2/3) as well as from the powerful sequence homology-based BLAST (Loctree3).

Literature:



Protein disorder — a breakthrough invention of evolution?

Michael Heinzinger

The regions in proteins that do not adopt regular three-dimensional structures in isolation are called disordered regions. In this seminar the functional and structural aspects of disordered proteins shall be discussed. Though only one literature source is provided, the student is expected to use and refer to in his presentation to additional sources for a detailed understanding of protein disorder.

Literature:

  • Schlessinger A, Schaefer C, Vicedo E, Schmidberger M, Punta M, Rost B  (2011). Protein disorder--a breakthrough invention of evolution? Curr Opin Struct Biol. Jun;21(3):412-8 http://www.ncbi.nlm.nih.gov/pubmed/21514145
  • ...

 

 

Transmembrane Proteins / PolyPhobius

Michael Bernhofer

PolyPhobius uses hidden markov models (HMMs) to predict transmembrane helices in protein sequences. This talk shall introduce transmembrane proteins, HMMs and sequence-based transmembrane helix prediction at the example of PolyPhobius.

Literature:

  • Alberts
  • Bioinformatics
  • Lukas Käll, Anders Krogh and Erik Sonnhammer. An HMM posterior decoder for sequence feature prediction that includes homology information. Bioinformatics, 21 (Suppl 1):i251-i257, June 2005.
  • Bernsel, A., Viklund, H., Falk, J., Lindahl, E., Von Heijne, G., & Elofsson, A. (2008). Prediction of membrane-protein topology from first principles. Proceedings of the National Academy of Sciences, 105(20), 7177–7181. doi:10.1073/pnas.0711151105

 

Human 5′ UTR design and variant effect prediction from a massively parallel translation assay

Prof. Julien Gagneur
Literature:
 

Deep learning sequence-based ab initio prediction of variant effects on expression and disease risk

Prof. Julien Gagneur
Literature: