TOPPView: An Open-Source Viewer for Mass Spectrometry Data

2009 ◽  
Vol 8 (7) ◽  
pp. 3760-3763 ◽  
Author(s):  
Marc Sturm ◽  
Oliver Kohlbacher
PROTEOMICS ◽  
2014 ◽  
Vol 14 (20) ◽  
pp. 2275-2279 ◽  
Author(s):  
Óscar Gallardo ◽  
David Ovelleiro ◽  
Marina Gay ◽  
Montserrat Carrascal ◽  
Joaquin Abian

2015 ◽  
Vol 129 ◽  
pp. 63-70 ◽  
Author(s):  
Oliver Horlacher ◽  
Frederic Nikitin ◽  
Davide Alocci ◽  
Julien Mariethoz ◽  
Markus Müller ◽  
...  

2018 ◽  
Vol 90 (20) ◽  
pp. 11908-11916 ◽  
Author(s):  
Markus Pioch ◽  
Marcus Hoffmann ◽  
Alexander Pralow ◽  
Udo Reichl ◽  
Erdmann Rapp

2021 ◽  
Vol 11 ◽  
Author(s):  
Erik Hartman ◽  
Karl Wallblom ◽  
Mariena J. A. van der Plas ◽  
Jitka Petrlova ◽  
Jun Cai ◽  
...  

Wound infection is a common and serious medical condition with an unmet need for improved diagnostic tools. A peptidomic approach, aided by mass spectrometry and bioinformatics, could provide novel means of identifying new peptide biomarkers for wound healing and infection assessment. Wound fluid is suitable for peptidomic analysis since it is both intimately tied to the wound environment and is readily available. In this study we investigate the peptidomes of wound fluids derived from surgical drainages following mastectomy and from wound dressings following facial skin grafting. By applying sorting algorithms and open source third party software to peptidomic label free tandem mass spectrometry data we provide an unbiased general methodology for analyzing and differentiating between peptidomes. We show that the wound fluid peptidomes of patients are highly individualized. However, differences emerge when grouping the patients depending on wound type. Furthermore, the abundance of peptides originating from documented antimicrobial regions of hemoglobin in infected wounds may contribute to an antimicrobial wound environment, as determined by in silico analysis. We validate our findings by compiling literature on peptide biomarkers and peptides of physiological significance and cross checking the results against our dataset, demonstrating that well-documented peptides of immunological significance are abundant in infected wounds, and originate from certain distinct regions in proteins such as hemoglobin and fibrinogen. Ultimately, we have demonstrated the power using sorting algorithms and open source software to help yield insights and visualize peptidomic data.


2016 ◽  
Vol 13 (9) ◽  
pp. 741-748 ◽  
Author(s):  
Hannes L Röst ◽  
Timo Sachsenberg ◽  
Stephan Aiche ◽  
Chris Bielow ◽  
Hendrik Weisser ◽  
...  

FEBS Open Bio ◽  
2017 ◽  
Vol 7 (7) ◽  
pp. 1051-1059
Author(s):  
Geunho Lee ◽  
Hyun Beom Lee ◽  
Byung Hwa Jung ◽  
Hojung Nam

2019 ◽  
Author(s):  
Mathew Gutierrez ◽  
Rob Smith

AbstractMass spectrometry is a fundamental tool for modern proteomics. The increasing availability of mass spectrometry data paired with the increasing sensitivity and fidelity of the instruments necessitates new and more potent analytical methods. To that end, we have created and present XFlow, a feature detection algorithm for extracting ion chromatograms from MS1 LC-MS data. XFlow is a parameter-free procedurally agnostic feature detection algorithm that utilizes the latent properties of ion chromatograms to resolve them from the surrounding noise present in MS1 data. XFlow is designed to function on either profile or centroided data across different resolutions and instruments. This broad applicability lends XFlow strong utility as a one-size-fits-all method for MS1 analysis or target acquisition for MS2. XFlow is written in Java and packaged with JS-MS, an open-source mass spectrometry analysis toolkit.


2007 ◽  
Vol 177 (4S) ◽  
pp. 52-53
Author(s):  
Stefano Ongarello ◽  
Eberhard Steiner ◽  
Regina Achleitner ◽  
Isabel Feuerstein ◽  
Birgit Stenzel ◽  
...  

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