Literature DB >> 22373723

Protein inference: a review.

Ting Huang1, Jingjing Wang, Weichuan Yu, Zengyou He.   

Abstract

Assembling peptides identified from tandem mass spectra into a list of proteins, referred to as protein inference, is a critical step in proteomics research. Due to the existence of degenerate peptides and 'one-hit wonders', it is very difficult to determine which proteins are present in the sample. In this paper, we review existing protein inference methods and classify them according to the source of peptide identifications and the principle of algorithms. It is hoped that the readers will gain a good understanding of the current development in this field after reading this review and come up with new protein inference algorithms.

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Year:  2012        PMID: 22373723     DOI: 10.1093/bib/bbs004

Source DB:  PubMed          Journal:  Brief Bioinform        ISSN: 1467-5463            Impact factor:   11.622


  29 in total

1.  Nonparametric Bayesian evaluation of differential protein quantification.

Authors:  Oliver Serang; A Ertugrul Cansizoglu; Lukas Käll; Hanno Steen; Judith A Steen
Journal:  J Proteome Res       Date:  2013-09-11       Impact factor: 4.466

2.  Mass spectrometry-based protein identification with accurate statistical significance assignment.

Authors:  Gelio Alves; Yi-Kuo Yu
Journal:  Bioinformatics       Date:  2014-10-31       Impact factor: 6.937

Review 3.  Improving protein identification from tandem mass spectrometry data by one-step methods and integrating data from other platforms.

Authors:  Sinjini Sikdar; Ryan Gill; Susmita Datta
Journal:  Brief Bioinform       Date:  2015-07-03       Impact factor: 11.622

4.  gpGrouper: A Peptide Grouping Algorithm for Gene-Centric Inference and Quantitation of Bottom-Up Proteomics Data.

Authors:  Alexander B Saltzman; Mei Leng; Bhoomi Bhatt; Purba Singh; Doug W Chan; Lacey Dobrolecki; Hamssika Chandrasekaran; Jong M Choi; Antrix Jain; Sung Y Jung; Michael T Lewis; Matthew J Ellis; Anna Malovannaya
Journal:  Mol Cell Proteomics       Date:  2018-08-09       Impact factor: 5.911

5.  XGlycScan: An Open-source Software For N-linked Glycosite Assignment, Quantification and Quality Assessment of Data from Mass Spectrometry-based Glycoproteomic Analysis.

Authors:  Paul Aiyetan; Bai Zhang; Zhen Zhang; Hui Zhang
Journal:  MOJ Proteom Bioinform       Date:  2014

6.  Peroxisomal ATP-binding cassette transporters form mainly tetramers.

Authors:  Flore Geillon; Catherine Gondcaille; Quentin Raas; Alexandre M M Dias; Delphine Pecqueur; Caroline Truntzer; Géraldine Lucchi; Patrick Ducoroy; Pierre Falson; Stéphane Savary; Doriane Trompier
Journal:  J Biol Chem       Date:  2017-03-03       Impact factor: 5.157

7.  Improved Protein Inference from Multiple Protease Bottom-Up Mass Spectrometry Data.

Authors:  Rachel M Miller; Robert J Millikin; Connor V Hoffmann; Stefan K Solntsev; Gloria M Sheynkman; Michael R Shortreed; Lloyd M Smith
Journal:  J Proteome Res       Date:  2019-08-23       Impact factor: 4.466

Review 8.  Progress and Challenges in Ocean Metaproteomics and Proposed Best Practices for Data Sharing.

Authors:  Mak A Saito; Erin M Bertrand; Megan E Duffy; David A Gaylord; Noelle A Held; William Judson Hervey; Robert L Hettich; Pratik D Jagtap; Michael G Janech; Danie B Kinkade; Dagmar H Leary; Matthew R McIlvin; Eli K Moore; Robert M Morris; Benjamin A Neely; Brook L Nunn; Jaclyn K Saunders; Adam I Shepherd; Nicholas I Symmonds; David A Walsh
Journal:  J Proteome Res       Date:  2019-03-12       Impact factor: 4.466

9.  PAnalyzer: a software tool for protein inference in shotgun proteomics.

Authors:  Gorka Prieto; Kerman Aloria; Nerea Osinalde; Asier Fullaondo; Jesus M Arizmendi; Rune Matthiesen
Journal:  BMC Bioinformatics       Date:  2012-11-05       Impact factor: 3.169

Review 10.  Computational approaches to protein inference in shotgun proteomics.

Authors:  Yong Fuga Li; Predrag Radivojac
Journal:  BMC Bioinformatics       Date:  2012-11-05       Impact factor: 3.169

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