Relating sequence properties to protein secretion

Poster (2011)

Authors

B.A. van den Berg Kluyver Centre for Genomics of Industrial Fermentation, Pattern Recognition and Bioinformatics - EEMCS , Netherlands Bioinformatics Centre, Nijmegen
M.J.T. Reinders Netherlands Bioinformatics Centre, Nijmegen, Kluyver Centre for Genomics of Industrial Fermentation, Pattern Recognition and Bioinformatics - EEMCS
HJ Pel DSM
L Wu DSM
D. de Ridder Kluyver Centre for Genomics of Industrial Fermentation, Netherlands Bioinformatics Centre, Nijmegen, Pattern Recognition and Bioinformatics - EEMCS
Research Group
Pattern Recognition and Bioinformatics (EEMCS) (TU Delft)
Copyright: © 2011 B.A. van den Berg, M.J.T. Reinders, HJ Pel, L Wu, J.A. Roubos, D. de Ridder
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Published Date

2011-9

Language

English

Reuse Rights

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Intelligent Systems

Research Group

Pattern Recognition and Bioinformatics

Abstract

Aspergillus niger is widely used for industrial enzyme production. Knowledge on high-level protein secretion could be useful to improve production rates. We used sequencebased classification methods to identify important properties
for successful high-level secretion, which will be used to redesign proteins for improved secretion.

Files

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