Literature DB >> 24304317

A survey of molecular descriptors used in mass spectrometry based proteomics.

Enrique Audain, Aniel Sanchez, Juan Antonio Vizcaíno, Yasset Perez-Riverol1.   

Abstract

The field of proteomics has grown vertiginously in the last years. This has been due fundamentally to technological improvements in the instrumentation, methods, and easy-to-use software, thereby making it possible to address a large number of biological questions and to deepen the study of the proteome of several organisms. The development in the field has imposed a challenge in the computational analysis of the commonly obtained large datasets generated in a single proteomics experiment, which still remains. An alternative to tackle this general issue has been the use of auxiliary information generated during the proteomics experiment to validate the confidence of the identifications. In this manuscript we review the main molecular descriptors used for building predictor models for estimating retention time, isoelectric point and peptide "detectability", which are key tools in the design of several validation strategies based in these criteria. We also give an overview of the main open source tools and libraries used for computing molecular descriptors.

Mesh:

Year:  2014        PMID: 24304317     DOI: 10.2174/1568026613666131204113537

Source DB:  PubMed          Journal:  Curr Top Med Chem        ISSN: 1568-0266            Impact factor:   3.295


  3 in total

1.  MRM-DIFF: data processing strategy for differential analysis in large scale MRM-based lipidomics studies.

Authors:  Hiroshi Tsugawa; Erika Ohta; Yoshihiro Izumi; Atsushi Ogiwara; Daichi Yukihira; Takeshi Bamba; Eiichiro Fukusaki; Masanori Arita
Journal:  Front Genet       Date:  2015-01-30       Impact factor: 4.599

2.  Accurate and fast feature selection workflow for high-dimensional omics data.

Authors:  Yasset Perez-Riverol; Max Kuhn; Juan Antonio Vizcaíno; Marc-Phillip Hitz; Enrique Audain
Journal:  PLoS One       Date:  2017-12-20       Impact factor: 3.240

3.  Accurate estimation of isoelectric point of protein and peptide based on amino acid sequences.

Authors:  Enrique Audain; Yassel Ramos; Henning Hermjakob; Darren R Flower; Yasset Perez-Riverol
Journal:  Bioinformatics       Date:  2015-11-14       Impact factor: 6.937

  3 in total

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