Sequence Protein Identification by Randomized Sequence Database and Transcriptome Mass Spectrometry (SPIDER-TMS): From Manual to Automatic Application of a ‘ de Novo Sequencing’ Approach

peer-reviewed · European Journal of Mass Spectrometry · 2016

peer-reviewed · European Journal of Mass Spectrometry · 2016. Raffaella Pascale et al. Sequence protein identification by a randomized sequence database and transcriptome mass spectrometry…
Date 2016-08-01
Type peer-reviewed
Venue European Journal of Mass Spectrometry
Publisher SAGE Publications
Contribution adjacent
DOI 10.1255/ejms.1434
Citations (OpenAlex) 2

Abstract

Sequence protein identification by a randomized sequence database and transcriptome mass spectrometry software package has been developed at the University of Basilicata in Potenza (Italy) and designed to facilitate the determination of the amino acid sequence of a peptide as well as an unequivocal identification of proteins in a high-throughput manner with enormous advantages of time, economical resource and expertise. The software package is a valid tool for the automation of a de novo sequencing approach, overcoming the main limits and a versatile platform useful in the proteomic field for an unequivocal identification of proteins, starting from tandem mass spectrometry data. The strength of this software is that it is a user-friendly and non-statistical approach, so protein identification can be considered unambiguous.

Authors

  1. Raffaella Pascale · University of Basilicata
  2. Gerarda Grossi · University of Basilicata
  3. Gabriele Cruciani · University of Perugia
  4. Giansalvatore Mecca · University of Basilicata
  5. Donatello Santoro · University of Basilicata
  6. Renzo Sarli Calace
  7. Patrizia Falabella · University of Basilicata
  8. Giuliana Bianco · University of Basilicata

Methods and tools

  • SPIDER-TMS: A software package automating de novo sequencing by matching spectra to a randomized sequence database and transcriptome data for protein identification.

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