scholarly journals Software Tools of the Computis European Project to Process Mass Spectrometry Images

2014 ◽  
Vol 20 (5) ◽  
pp. 351-360 ◽  
Author(s):  
Marie-France Robbe ◽  
Jean-Pierre Both ◽  
Brendan Prideaux ◽  
Ivo Klinkert ◽  
Vincent Picaud ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Software Tools ◽  
European Project ◽  
Process Mass Spectrometry

Recent advances in mass-spectrometry based proteomics software, tools and databases

2021 ◽  
Author(s):  
Ankit Halder ◽  
Ayushi Verma ◽  
Deeptarup Biswas ◽  
Sanjeeva Srivastava
Keyword(s):  
Mass Spectrometry ◽  
Software Tools ◽  
Recent Advances

scholarly journals Recent advances in software tools for more generic and precise intact glycopeptide analysis

2020 ◽  
pp. mcp.R120.002090 ◽  
Author(s):  
Weiqian Cao ◽  
Mingqi Liu ◽  
Siyuan Kong ◽  
Mengxi Wu ◽  
Yang Zhang ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Systematic Review ◽  
Quality Control ◽  
Software Tools ◽  
Mass Spectrometry Data ◽  
Identification Process ◽  
Advantages And Disadvantages ◽  
Recent Advances ◽  
Glycopeptide Analysis

Intact glycopeptide identification has long been known as a key and challenging barrier to the comprehensive and accurate understanding the role of glycosylation in an organism. Intact glycopeptide analysis is a blossoming field that has received increasing attention in recent years. Mass spectrometry (MS)-based strategies and relative software tools are major drivers that have greatly facilitated the analysis of intact glycopeptides, particularly intact N-glycopeptides. This manuscript provides a systematic review of the intact glycopeptide identification process using mass spectrometry data generated in shotgun proteomic experiments, which typically focus on N-glycopeptide analysis. Particular attention is paid to the software tools that have been recently developed in the last decade for the interpretation and quality control of glycopeptide spectra acquired using different MS strategies. The review also provides information about the characteristics and applications of these software tools, discusses their advantages and disadvantages, and concludes with a discussion of outstanding tools.

scholarly journals The Application of New Software Tools to Quantitative Protein Profiling Via Isotope-coded Affinity Tag (ICAT) and Tandem Mass Spectrometry

2003 ◽  
Vol 2 (7) ◽  
pp. 426-427 ◽  
Author(s):  
Priska D. von Haller ◽  
Eugene Yi ◽  
Samuel Donohoe ◽  
Kelly Vaughn ◽  
Andrew Keller ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Tandem Mass Spectrometry ◽  
Software Tools ◽  
Protein Profiling ◽  
Tandem Mass ◽  
Affinity Tag

Data‐Independent Acquisition Mass Spectrometry‐Based Proteomics and Software Tools: A Glimpse in 2020

PROTEOMICS ◽  
2020 ◽  
Vol 20 (17-18) ◽  
pp. 1900276 ◽  
Author(s):  
Fangfei Zhang ◽  
Weigang Ge ◽  
Guan Ruan ◽  
Xue Cai ◽  
Tiannan Guo
Keyword(s):  
Mass Spectrometry ◽  
Software Tools ◽  
Data Independent Acquisition

Data normalization strategies in metabolomics: Current challenges, approaches, and tools

2020 ◽  
Vol 26 (3) ◽  
pp. 165-174 ◽  
Author(s):  
Biswapriya B Misra
Keyword(s):  
Mass Spectrometry ◽  
Software Tools ◽  
Data Normalization ◽  
Spectroscopy Data ◽  
Metabolomics Data ◽  
Quantitative Metabolomics ◽  
Research Findings ◽  
Statistical Approaches ◽  
Human Healthcare ◽  
Proper Normalization

Data normalization is a big challenge in quantitative metabolomics approaches, whether targeted or untargeted. Without proper normalization, the mass-spectrometry and spectroscopy data can provide erroneous, sub-optimal data, which can lead to misleading and confusing biological results and thereby result in failed application to human healthcare, clinical, and other research avenues. To address this issue, a number of statistical approaches and software tools have been proposed in the literature and implemented over the years, thereby providing a multitude of approaches to choose from – either sample-based or data-based normalization strategies. In recent years, new dedicated software tools for metabolomics data normalization have surfaced as well. In this account article, I summarize the existing approaches and the new discoveries and research findings in this area of metabolomics data normalization, and I introduce some recent tools that aid in data normalization.

scholarly journals On-line detection and quantification of trace impurities in vaporisable samples by direct liquid introduction process mass spectrometry

2014 ◽  
Vol 6 (20) ◽  
pp. 8148-8153 ◽  
Author(s):  
Andrew W. Owen ◽  
Alison Nordon ◽  
David Littlejohn ◽  
Thomas P. Lynch ◽  
J. Steven Lancaster ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Line Detection ◽  
Trace Impurities ◽  
On Line ◽  
Process Mass Spectrometry ◽  
Detection And Quantification

Data analysis and bioinformatics tools for tandem mass spectrometry in proteomics

2008 ◽  
Vol 33 (1) ◽  
pp. 18-25 ◽  
Author(s):  
Eric W. Deutsch ◽  
Henry Lam ◽  
Ruedi Aebersold
Keyword(s):  
Mass Spectrometry ◽  
Tandem Mass Spectrometry ◽  
Open Source Software ◽  
Software Tools ◽  
Tandem Mass ◽  
Critical Component ◽  
Data Repositories ◽  
The Past ◽  
Proteomics Experiment ◽  
Proteomics Research

Data processing is a central and critical component of a successful proteomics experiment, and is often the most time-consuming step. There have been considerable advances in the field of proteomics informatics in the past 5 years, spurred mainly by free and open-source software tools. Along with the gains afforded by new software, the benefits of making raw data and processed results freely available to the community in data repositories are finally in evidence. In this review, we provide an overview of the general analysis approaches, software tools, and repositories that are enabling successful proteomics research via tandem mass spectrometry.

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