Effective peak alignment for mass spectrometry data analysis using two-phase clustering approach

2014 ◽  
Vol 9 (1) ◽  
pp. 52 ◽  
Author(s):  
Yu Cheng Liu ◽  
Lien Chin Chen ◽  
Chi Wei Liu ◽  
Vincent S. Tseng
Keyword(s):  
Mass Spectrometry ◽  
Data Analysis ◽  
Mass Spectrometry Data ◽  
Two Phase ◽  
Peak Alignment ◽  
Clustering Approach

scholarly journals CLMSVault: A Software Suite for Protein Cross-Linking Mass-Spectrometry Data Analysis and Visualization

2017 ◽  
Vol 16 (7) ◽  
pp. 2645-2652 ◽  
Author(s):  
Mathieu Courcelles ◽  
Jasmin Coulombe-Huntington ◽  
Émilie Cossette ◽  
Anne-Claude Gingras ◽  
Pierre Thibault ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Data Analysis ◽  
Mass Spectrometry Data ◽  
Cross Linking ◽  
Software Suite ◽  
Protein Cross Linking

Advancements in capturing and mining mass spectrometry data are transforming natural products research

2021 ◽  
Author(s):  
Scott A. Jarmusch ◽  
Justin J. J. van der Hooft ◽  
Pieter C. Dorrestein ◽  
Alan K. Jarmusch
Keyword(s):  
Mass Spectrometry ◽  
Data Mining ◽  
Natural Products ◽  
Data Analysis ◽  
Community Participation ◽  
Mass Spectrometry Data ◽  
Metabolomics Data ◽  
Analysis Tools ◽  
Public Data ◽  
Potential Use

This review covers the current and potential use of mass spectrometry-based metabolomics data mining in natural products. Public data, metadata, databases and data analysis tools are critical. The value and success of data mining rely on community participation.

scholarly journals EXIMS: an improved data analysis pipeline based on a new peak picking method for EXploring Imaging Mass Spectrometry data

2015 ◽  
Vol 31 (19) ◽  
pp. 3198-3206 ◽  
Author(s):  
Chalini D. Wijetunge ◽  
Isaam Saeed ◽  
Berin A. Boughton ◽  
Jeffrey M. Spraggins ◽  
Richard M. Caprioli ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Data Analysis ◽  
Imaging Mass Spectrometry ◽  
Mass Spectrometry Data ◽  
Peak Picking ◽  
Analysis Pipeline ◽  
Data Analysis Pipeline ◽  
Imaging Mass Spectrometry Data

XCMS:  Processing Mass Spectrometry Data for Metabolite Profiling Using Nonlinear Peak Alignment, Matching, and Identification

2006 ◽  
Vol 78 (3) ◽  
pp. 779-787 ◽  
Author(s):  
Colin A. Smith ◽  
Elizabeth J. Want ◽  
Grace O'Maille ◽  
Ruben Abagyan ◽  
Gary Siuzdak
Keyword(s):  
Mass Spectrometry ◽  
Metabolite Profiling ◽  
Mass Spectrometry Data ◽  
Peak Alignment

MSDA, a proteomics software suite for in-depth Mass Spectrometry Data Analysis using grid computing

PROTEOMICS ◽  
2014 ◽  
Vol 14 (9) ◽  
pp. 1014-1019 ◽  
Author(s):  
Christine Carapito ◽  
Alexandre Burel ◽  
Patrick Guterl ◽  
Alexandre Walter ◽  
Fabrice Varrier ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Data Analysis ◽  
Grid Computing ◽  
Mass Spectrometry Data ◽  
Software Suite

Mass Spectrometry Data Analysis for Early Detection of Inherited Breast Cancer

2009 ◽  
pp. 21-28
Author(s):  
Francesco Baudi ◽  
Mario Cannataro ◽  
Rita Casadonte ◽  
Francesco Costanzo ◽  
Giovanni Cuda ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Mass Spectrometry ◽  
Data Analysis ◽  
Early Detection ◽  
Mass Spectrometry Data ◽  
Inherited Breast Cancer

scholarly journals VOCCluster: Untargeted Metabolomics Feature Clustering Approach for Clinical Breath Gas Chromatography - Mass Spectrometry Data

2019 ◽  
Author(s):  
Yaser Alkhalifah ◽  
Iain Phillips ◽  
Andrea Soltoggio ◽  
Kareen Darnley ◽  
William H. Nailon ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Gas Chromatography ◽  
Organic Compounds ◽  
Mass Spectra ◽  
Mass Spectrometry Data ◽  
Gas Chromatography Mass Spectrometry ◽  
Feature Clustering ◽  
Software Packages ◽  
Volatile Organic ◽  
Clustering Approach

<div>Our unsupervised clustering technique, VOCCluster, prototyped in Python, handles features of deconvolved GC-MS breath data. VOCCluster was created from a heuristic ontology based on the observation of experts undertaking data processing with a suite of software packages. VOCCluster identifies and clusters groups of volatile organic compounds (VOCs) from deconvolved GC-MS breath with similar mass spectra and retention index profiles.</div>

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