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 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

A collection of open source applications for mass spectrometry data mining

PROTEOMICS ◽  
2014 ◽  
Vol 14 (20) ◽  
pp. 2275-2279 ◽  
Author(s):  
Óscar Gallardo ◽  
David Ovelleiro ◽  
Marina Gay ◽  
Montserrat Carrascal ◽  
Joaquin Abian
Keyword(s):  
Mass Spectrometry ◽  
Data Mining ◽  
Open Source ◽  
Mass Spectrometry Data

Translating Advances in Data Mining in Business Operations

2008 ◽  
pp. 2734-2748
Author(s):  
Henry Dillon ◽  
Beverley Hope
Keyword(s):  
Data Mining ◽  
Information Technology ◽  
Data Analysis ◽  
Knowledge Discovery ◽  
Knowledge Discovery In Databases ◽  
Business Context ◽  
Business Operations ◽  
Analysis Tools ◽  
It Managers ◽  
Tools And Techniques

Knowledge discovery in databases (KDD) is a field of research that studies the development and use of various data analysis tools and techniques. KDD research has produced an array of models, theories, functions and methodologies for producing knowledge from data. However, despite these advances, nearly two thirds of information technology (IT) managers say that data mining products are too difficult to use in a business context. This chapter discusses how advances in data mining translate into the business context. It highlights the art of business implementation rather than the science of KDD.

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

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
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