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Homology-driven assembly of NOn-redundant protEin sequence sets (NOmESS) for mass spectrometry

Summary: 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-sequen...

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Detalles Bibliográficos
Autores principales: Temu, Tikira, Mann, Matthias, Räschle, Markus, Cox, Jürgen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4848398/
https://www.ncbi.nlm.nih.gov/pubmed/26743511
http://dx.doi.org/10.1093/bioinformatics/btv756
Descripción
Sumario:Summary: 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.de Supplementary information: Supplementary data are available at Bioinformatics online.