Homology-driven assembly of NOn-redundant protEin sequence sets (NOmESS) for mass spectrometry
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Homology-driven assembly of NOn-redundant protEin sequence sets (NOmESS) for mass spectrometry. / Temu, Tikira; Mann, Matthias; Räschle, Markus; Cox, Jürgen.
In: Bioinformatics (Online), Vol. 32, No. 9, 01.05.2016, p. 1417-9.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - Homology-driven assembly of NOn-redundant protEin sequence sets (NOmESS) for mass spectrometry
AU - Temu, Tikira
AU - Mann, Matthias
AU - Räschle, Markus
AU - Cox, Jürgen
N1 - © The Author 2016. Published by Oxford University Press.
PY - 2016/5/1
Y1 - 2016/5/1
N2 - UNLABELLED: To enable mass spectrometry (MS)-based proteomic studies with poorly characterized organisms, we developed a computational workflow for the homology-driven assembly of a non-redundant reference sequence dataset. In the automated pipeline, translated DNA sequences (e.g. ESTs, RNA deep-sequencing data) are aligned to those of a closely related and fully sequenced organism. Representative sequences are derived from each cluster and joined, resulting in a non-redundant reference set representing the maximal available amino acid sequence information for each protein. We here applied NOmESS to assemble a reference database for the widely used model organism Xenopus laevis and demonstrate its use in proteomic applications.AVAILABILITY AND IMPLEMENTATION: NOmESS is written in C#. The source code as well as the executables can be downloaded from http://www.biochem.mpg.de/cox Execution of NOmESS requires BLASTp and cd-hit in addition.CONTACT: cox@biochem.mpg.deSUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
AB - UNLABELLED: To enable mass spectrometry (MS)-based proteomic studies with poorly characterized organisms, we developed a computational workflow for the homology-driven assembly of a non-redundant reference sequence dataset. In the automated pipeline, translated DNA sequences (e.g. ESTs, RNA deep-sequencing data) are aligned to those of a closely related and fully sequenced organism. Representative sequences are derived from each cluster and joined, resulting in a non-redundant reference set representing the maximal available amino acid sequence information for each protein. We here applied NOmESS to assemble a reference database for the widely used model organism Xenopus laevis and demonstrate its use in proteomic applications.AVAILABILITY AND IMPLEMENTATION: NOmESS is written in C#. The source code as well as the executables can be downloaded from http://www.biochem.mpg.de/cox Execution of NOmESS requires BLASTp and cd-hit in addition.CONTACT: cox@biochem.mpg.deSUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
KW - Amino Acid Sequence
KW - Animals
KW - Base Sequence
KW - High-Throughput Nucleotide Sequencing
KW - Humans
KW - Mass Spectrometry
KW - Proteomics
KW - Journal Article
U2 - 10.1093/bioinformatics/btv756
DO - 10.1093/bioinformatics/btv756
M3 - Journal article
C2 - 26743511
VL - 32
SP - 1417
EP - 1419
JO - Bioinformatics (Online)
JF - Bioinformatics (Online)
SN - 1367-4811
IS - 9
ER -
ID: 186877587