Detecting Glycosylations in Complex Samples

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.
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Lazaros Iliadis; Ilias Maglogiannis; Harris Papadopoulos. 8th International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2012, Halkidiki, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-381 (Part I), pp.234-243, 2012, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-642-33409-2_25〉
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Thorsten Johl, Manfred Nimtz, Lothar Jänsch, Frank Klawonn. Detecting Glycosylations in Complex Samples. Lazaros Iliadis; Ilias Maglogiannis; Harris Papadopoulos. 8th International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2012, Halkidiki, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-381 (Part I), pp.234-243, 2012, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-642-33409-2_25〉. 〈hal-01521386〉

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