Proteomics

Dataset Information

5

Drosophila melanogaster exp 132


ABSTRACT: PeptideRank is an approach that uses a rank-based algorithm for peptide detectability prediction from shotgun proteomics data. The best performance is achieved when it is trained on organism-specific shotgun proteomics datasets. The Drosophila shotgun proteomics data presented here have been used amongst others to train and validate PeptideRank.

INSTRUMENT(S): LTQ

ORGANISM(S): Drosophila melanogaster  

TISSUE(S): Cell Culture

DISEASE(S): Not Available

SUBMITTER: Sandra Goetze  

LAB HEAD: Erich Brunner

PROVIDER: PXD000730 | Pride | 2019-06-04

REPOSITORIES: Pride

Dataset's files

Source:
Action DRS
20070903_KcNuc_Subfr_2_14_16.RAW Raw
20070903_KcNuc_Subfr_2_17_18.RAW Raw
20070903_KcNuc_Subfr_2_19_20.RAW Raw
20070903_KcNuc_Subfr_2_21.RAW Raw
20070903_KcNuc_Subfr_2_22.RAW Raw
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Publications

Improved prediction of peptide detectability for targeted proteomics using a rank-based algorithm and organism-specific data.

Qeli Ermir E   Omasits Ulrich U   Goetze Sandra S   Stekhoven Daniel J DJ   Frey Juerg E JE   Basler Konrad K   Wollscheid Bernd B   Brunner Erich E   Ahrens Christian H CH  

Journal of proteomics 20140527


<h4>Unlabelled</h4>The in silico prediction of the best-observable "proteotypic" peptides in mass spectrometry-based workflows is a challenging problem. Being able to accurately predict such peptides would enable the informed selection of proteotypic peptides for targeted quantification of previously observed and non-observed proteins for any organism, with a significant impact for clinical proteomics and systems biology studies. Current prediction algorithms rely on physicochemical parameters i  ...[more]

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