Detecting Glycosylations in Complex Samples View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2012

AUTHORS

Thorsten Johl , Manfred Nimtz , Lothar Jänsch , Frank Klawonn

ABSTRACT

Glycoproteins are the highly diverse key element in the process of cell – cell recognition and host – pathogen interaction. It is this diversity that makes it a challenge to identify the glyco-peptides together with their modification from trypsin-digested complex samples in mass spectrometry studies. The biological approach is to isolate the peptides and separate them from their glycosylation to analyse both separately. Here we present an in-silico approach that analyses the combined spectra by using highly accurate data and turns previously established knowledge into algorithms to refine the identification process. It complements the established method, needs no separation, and works on the most readily available clinical sample of them all: Urine. More... »

PAGES

234-243

Book

TITLE

Artificial Intelligence Applications and Innovations

ISBN

978-3-642-33408-5
978-3-642-33409-2

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-33409-2_25

DOI

http://dx.doi.org/10.1007/978-3-642-33409-2_25

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1018855234


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