Bottom up proteomics data analysis strategies to explore protein modifications and genomic variants

PROTEOMICS ◽  
2015 ◽  
Vol 15 (11) ◽  
pp. 1789-1792 ◽  
Author(s):  
Ana Sofia Carvalho ◽  
Deborah Penque ◽  
Rune Matthiesen
Keyword(s):  
Data Analysis ◽  
Proteomics Data ◽  
Bottom Up ◽  
Protein Modifications ◽  
Genomic Variants ◽  
Analysis Strategies ◽  
Proteomics Data Analysis

scholarly journals Using the entrapment sequence method as a standard to evaluate key steps of proteomics data analysis process

BMC Genomics ◽  
2017 ◽  
Vol 18 (S2) ◽  
Author(s):  
Xiao-dong Feng ◽  
Li-wei Li ◽  
Jian-hong Zhang ◽  
Yun-ping Zhu ◽  
Cheng Chang ◽  
...  
Keyword(s):  
Data Analysis ◽  
Proteomics Data ◽  
Analysis Process ◽  
Sequence Method ◽  
Key Steps ◽  
Proteomics Data Analysis

scholarly journals Philosopher: a versatile toolkit for shotgun proteomics data analysis

2020 ◽  
Vol 17 (9) ◽  
pp. 869-870 ◽  
Author(s):  
Felipe da Veiga Leprevost ◽  
Sarah E. Haynes ◽  
Dmitry M. Avtonomov ◽  
Hui-Yin Chang ◽  
Avinash K. Shanmugam ◽  
...  
Keyword(s):  
Data Analysis ◽  
Shotgun Proteomics ◽  
Proteomics Data ◽  
Proteomics Data Analysis

scholarly journals Bioinformatics Methods for Mass Spectrometry-Based Proteomics Data Analysis

2020 ◽  
Vol 21 (8) ◽  
pp. 2873 ◽  
Author(s):  
Chen Chen ◽  
Jie Hou ◽  
John J. Tanner ◽  
Jianlin Cheng
Keyword(s):  
Mass Spectrometry ◽  
Protein Interactions ◽  
Protein Identification ◽  
Proteomics Data ◽  
Cellular Mechanisms ◽  
Tremendous Progress ◽  
Analysis Strategies ◽  
Bioinformatics Software ◽  
The Relationship ◽  
Proteomics Data Analysis

Recent advances in mass spectrometry (MS)-based proteomics have enabled tremendous progress in the understanding of cellular mechanisms, disease progression, and the relationship between genotype and phenotype. Though many popular bioinformatics methods in proteomics are derived from other omics studies, novel analysis strategies are required to deal with the unique characteristics of proteomics data. In this review, we discuss the current developments in the bioinformatics methods used in proteomics and how they facilitate the mechanistic understanding of biological processes. We first introduce bioinformatics software and tools designed for mass spectrometry-based protein identification and quantification, and then we review the different statistical and machine learning methods that have been developed to perform comprehensive analysis in proteomics studies. We conclude with a discussion of how quantitative protein data can be used to reconstruct protein interactions and signaling networks.

EasyProt — An easy-to-use graphical platform for proteomics data analysis

2013 ◽  
Vol 79 ◽  
pp. 146-160 ◽  
Author(s):  
Florent Gluck ◽  
Christine Hoogland ◽  
Paola Antinori ◽  
Xavier Robin ◽  
Frederic Nikitin ◽  
...  
Keyword(s):  
Data Analysis ◽  
Proteomics Data ◽  
Proteomics Data Analysis
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