Literature DB >> 15290788

Bioinformatics meets proteomics--bridging the gap between mass spectrometry data analysis and cell biology.

P Kearney1, P Thibault.   

Abstract

Proteomics research programs typically comprise the identification of protein content of any given cell, their isoforms, splice variants, post-translational modifications, interacting partners and higher-order complexes under different conditions. These studies present significant analytical challenges owing to the high proteome complexity and the low abundance of the corresponding proteins, which often requires highly sensitive and resolving techniques. Mass spectrometry plays an important role in proteomics and has become an indispensable tool for molecular and cellular biology. However, the analysis of mass spectrometry data can be a daunting task in view of the complexity of the information to decipher, the accuracy and dynamic range of quantitative analysis, the availability of appropriate bioinformatics software and the overwhelming size of data files. The past ten years have witnessed significant technological advances in mass spectrometry-based proteomics and synergy with bioinformatics is vital to fulfill the expectations of biological discovery programs. We present here the technological capabilities of mass spectrometry and bioinformatics for mining the cellular proteome in the context of discovery programs aimed at trace-level protein identification and expression from microgram amounts of protein extracts from human tissues.

Entities:  

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Year:  2003        PMID: 15290788     DOI: 10.1142/s021972000300023x

Source DB:  PubMed          Journal:  J Bioinform Comput Biol        ISSN: 0219-7200            Impact factor:   1.122


  11 in total

Review 1.  Advances in proteomics data analysis and display using an accurate mass and time tag approach.

Authors:  Jennifer S D Zimmer; Matthew E Monroe; Wei-Jun Qian; Richard D Smith
Journal:  Mass Spectrom Rev       Date:  2006 May-Jun       Impact factor: 10.946

Review 2.  The coming of age of phosphoproteomics--from large data sets to inference of protein functions.

Authors:  Philippe P Roux; Pierre Thibault
Journal:  Mol Cell Proteomics       Date:  2013-09-13       Impact factor: 5.911

3.  LC-MS Based Detection of Differential Protein Expression.

Authors:  Leepika Tuli; Habtom W Ressom
Journal:  J Proteomics Bioinform       Date:  2009-10-02

4.  Use of colloidal silica-beads for the isolation of cell-surface proteins for mass spectrometry-based proteomics.

Authors:  Yunee Kim; Sarah Elschenbroich; Parveen Sharma; Lusia Sepiashvili; Anthony O Gramolini; Thomas Kislinger
Journal:  Methods Mol Biol       Date:  2011

5.  Spectrin-like repeats 11-15 of human dystrophin show adaptations to a lipidic environment.

Authors:  Joe Sarkis; Jean-François Hubert; Baptiste Legrand; Estelle Robert; Angélique Chéron; Julien Jardin; Eric Hitti; Elisabeth Le Rumeur; Véronique Vié
Journal:  J Biol Chem       Date:  2011-06-28       Impact factor: 5.157

6.  Proteomics: challenges, techniques and possibilities to overcome biological sample complexity.

Authors:  Kondethimmanahalli Chandramouli; Pei-Yuan Qian
Journal:  Hum Genomics Proteomics       Date:  2009-12-08

Review 7.  Analysing the nanoparticle-protein corona for potential molecular target identification.

Authors:  Chandra Kumar Elechalawar; Md Nazir Hossen; Lacey McNally; Resham Bhattacharya; Priyabrata Mukherjee
Journal:  J Control Release       Date:  2020-03-09       Impact factor: 9.776

8.  Using a spike-in experiment to evaluate analysis of LC-MS data.

Authors:  Leepika Tuli; Tsung-Heng Tsai; Rency S Varghese; Jun Feng Xiao; Amrita Cheema; Habtom W Ressom
Journal:  Proteome Sci       Date:  2012-02-27       Impact factor: 2.480

Review 9.  Exploring the human seminal plasma proteome: an unexplored gold mine of biomarker for male infertility and male reproduction disorder.

Authors:  Kambiz Gilany; Arash Minai-Tehrani; Elham Savadi-Shiraz; Hassan Rezadoost; Niknam Lakpour
Journal:  J Reprod Infertil       Date:  2015 Apr-Jun

10.  The MHC class I peptide repertoire is molded by the transcriptome.

Authors:  Marie-Hélène Fortier; Etienne Caron; Marie-Pierre Hardy; Grégory Voisin; Sébastien Lemieux; Claude Perreault; Pierre Thibault
Journal:  J Exp Med       Date:  2008-02-25       Impact factor: 14.307

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