MSTopDiff: A Tool for the Visualization of Mass Shifts in Deconvoluted Top-Down Proteomics Data for the Database-Independent Detection of Protein Modifications

2021 ◽  
Author(s):  
Philipp T. Kaulich ◽  
Konrad Winkels ◽  
Tobias B. Kaulich ◽  
Christian Treitz ◽  
Liam Cassidy ◽  
...  
Keyword(s):  
Proteomics Data ◽  
Top Down ◽  
Protein Modifications ◽  
Mass Shifts

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 SPECTRUM – A MATLAB Toolbox for Proteoform Identification from Top-Down Proteomics Data

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Abdul Rehman Basharat ◽  
Kanzal Iman ◽  
Muhammad Farhan Khalid ◽  
Zohra Anwar ◽  
Rashid Hussain ◽  
...  
Keyword(s):  
Proteomics Data ◽  
Top Down ◽  
Matlab Toolbox

scholarly journals Pyntheon: A Functional Analysis Framework for Protein Modifications and Mutations of 83 Model Organisms

2019 ◽  
Author(s):  
Ahmed Arslan
Keyword(s):  
Posttranslational Modifications ◽  
Protein Modification ◽  
Model Organisms ◽  
Analysis Framework ◽  
Proteomics Data ◽  
Functional Protein ◽  
Protein Modifications ◽  
Community Of Researchers ◽  
Protein Mutations ◽  
The Impact

AbstractMotivationPosttranslational modifications (PTMs) modulate proteins activity depending on the dynamics of cellular conditions, in the highly regulated processes that control the reversible nature of these modifications and a cellular state. Due to the unique importance of PTMs, a number of resources are available to analyze the protein modification data for different organisms. These databases are quite informative on a limited number of popular organisms, mostly human and yeast. However there has not been a single database to date that makes it possible to analyze the modified protein residue data for up to 83 model organisms. Moreover, there are limited resources that rely on both protein mutations and modifications in evaluating a phenotype.ResultsI am presenting a comprehensive python tool Pyntheon that enables users to analyze protein modifications and mutations data. This resource can be used in different ways to know: (i) if the proteins of interest have modifications and (ii) if the modified residues overlap with mutated sites. Additional functions include, analyzing if a PTM-site is present in a functional protein region, like domain and structural regions. In summary, Pyntheon makes it possible for a larger community of researchers to evaluate their curated proteomics data and interpret the impact of mutations on phenotypes.ConclusionPyntheon has multifold functions that can help analyzing the protein mutations impact on the modified residues for a large number of popular model organisms.Code-Availabilityhttps://github.com/AhmedArslan/[email protected]

Top-down proteomics data acquisition v1 (protocols.io.bnh9mb96)

protocols.io ◽  
2020 ◽  
Author(s):  
Jeannie Camarillo ◽  
Bryon Drown ◽  
Rafael Melani ◽  
Neil Kelleher
Keyword(s):  
Data Acquisition ◽  
Proteomics Data ◽  
Top Down

scholarly journals ProteoCombiner: integrating bottom-up with top-down proteomics data for improved proteoform assessment

2020 ◽  
Author(s):  
Diogo B Lima ◽  
Mathieu Dupré ◽  
Magalie Duchateau ◽  
Quentin Giai Gianetto ◽  
Martial Rey ◽  
...  
Keyword(s):  
Search Engines ◽  
High Performance ◽  
Large Scale ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Post Translational Modification ◽  
Proteomics Data ◽  
Top Down ◽  
Proteomic Data ◽  
Demonstration Video

Abstract Motivation We present a high-performance software integrating shotgun with top-down proteomic data. The tool can deal with multiple experiments and search engines. Enable rapid and easy visualization, manual validation and comparison of the identified proteoform sequences including the post-translational modification characterization. Results We demonstrate the effectiveness of our approach on a large-scale Escherichia coli dataset; ProteoCombiner unambiguously shortlisted proteoforms among those identified by the multiple search engines. Availability and implementation ProteoCombiner, a demonstration video and user tutorial are freely available at https://proteocombiner.pasteur.fr, for academic use; all data are thus available from the ProteomeXchange consortium (identifier PXD017618). Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals AA_stat enables extensive characterization of artefact and post-translational modifications in bottom-up proteomics

2020 ◽  
Author(s):  
Lev I. Levitsky ◽  
Julia A. Bubis ◽  
Mikhail V. Gorshkov ◽  
Irina A. Tarasova
Keyword(s):  
Amino Acid ◽  
Mass Spectra ◽  
Large Scale ◽  
Proteomics Data ◽  
Post Translational Modifications ◽  
Tandem Mass Spectra ◽  
Command Line Tool ◽  
Mass Shifts ◽  
Bioinformatic Approach

ABSTRACTWe report on AA_stat, a bioinformatic approach for panoramic profiling of artificial and post-translational modifications and their localization sites in large-scale proteomics data. Presented version of AA_stat provides validation of ultra-tolerant (open) search results followed by interpretation of the observed mass shifts and recommendation of the optimized sets of fixed and variable modifications for subsequent regular searches. Localization of modification sites is based on relative amino acid frequencies and analysis of tandem mass spectra. AA_stat determines groups of peptide identifications with mass shifts from the validated results of the open search and then scores each possible mass shift location by matching the MS/MS spectrum across the theoretical peptide isoforms. Here we demonstrate the utility of AA_stat for blind scanning of abundant and rare amino acid modifications of both artificial and biological origins and analyze advantages and limitations of open search strategies. AA_stat is implemented as an open-source command line tool available at https://github.com/SimpleNumber/aa_stat.

scholarly journals PSpecteR: A User-Friendly and Interactive Application for Visualizing Top-Down and Bottom-Up Proteomics Data in R

2021 ◽  
Author(s):  
David J. Degnan ◽  
Lisa M. Bramer ◽  
Amanda M. White ◽  
Mowei Zhou ◽  
Aivett Bilbao ◽  
...  
Keyword(s):  
Proteomics Data ◽  
Top Down ◽  
Bottom Up ◽  
Interactive Application ◽  
User Friendly

scholarly journals Enhancing Top-Down Proteomics Data Analysis by Combining Deconvolution Results through a Machine Learning Strategy

2020 ◽  
Vol 31 (5) ◽  
pp. 1104-1113 ◽  
Author(s):  
Sean J. McIlwain ◽  
Zhijie Wu ◽  
Molly Wetzel ◽  
Daniel Belongia ◽  
Yutong Jin ◽  
...  
Keyword(s):  
Machine Learning ◽  
Data Analysis ◽  
Learning Strategy ◽  
Proteomics Data ◽  
Top Down ◽  
Proteomics Data Analysis
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