A support for the identification of non-tryptic peptides based on low resolution tandem and sequential mass spectrometry data: The INSPIRE software

2012 ◽  
Vol 718 ◽  
pp. 70-77 ◽  
Author(s):  
Ilario Losito ◽  
Fabio Mavelli ◽  
Annamaria Demarinis Loiotile ◽  
Francesco Palmisano
Keyword(s):  
Mass Spectrometry ◽  
Mass Spectrometry Data ◽  
Low Resolution ◽  
Tryptic Peptides ◽  
Sequential Mass Spectrometry

Assessing Effects of Pre-Processing Mass Spectrometry Data on Classification Performance

2008 ◽  
Vol 14 (5) ◽  
pp. 267-273 ◽  
Author(s):  
Akin Ozcift ◽  
Arif Gulten
Keyword(s):  
Mass Spectrometry ◽  
Ovarian Cancer ◽  
Medical Diagnosis ◽  
Prediction Accuracy ◽  
Mass Spectrometry Data ◽  
Support Vector ◽  
Main Concern ◽  
Disease Prediction ◽  
Baseline Correction ◽  
Low Resolution

Disease prediction through mass spectrometry (MS) data is gaining importance in medical diagnosis. Particularly in cancerous diseases, early prediction is one of the most life saving stages. High dimension and the noisy nature of MS data requires a two-phase study for successful disease prediction; first, MS data must be pre-processed with stages such as baseline correction, normalizing, de-noising and peak detection. Second, a dimension reduction based classifier design is the main objective. Having the data pre-processed, the prediction accuracy of the classifier algorithm becomes the most significant factor in the medical diagnosis phase. As health is the main concern, the accuracy of the classifier is clearly very important. In this study, the effects of the pre-processing stages of MS data on classifier performances are addressed. Three pre-processing stages—baseline correction, normalization and de-noising—are applied to three MS data samples, namely, high-resolution ovarian cancer, low-resolution prostate cancer and a low-resolution ovarian cancer. To measure the effects of the pre-processing stages quantitatively, four diverse classifiers, genetic algorithm wrapped K-nearest neighbor (GA-KNN), principal component analysis-based least discriminant analysis (PCA-LDA), a neural network (NN) and a support vector machine (SVM) are applied to the data sets. Calculated classifier performances have demonstrated the effects of pre-processing stages quantitatively and the importance of pre-processing stages on the prediction accuracy of classifiers. Results of computations have been shown clearly.

154: Integration of TPSA and High-Throughput Mass Spectrometry Data Improves Prostate Cancer Prediction

2007 ◽  
Vol 177 (4S) ◽  
pp. 52-53
Author(s):  
Stefano Ongarello ◽  
Eberhard Steiner ◽  
Regina Achleitner ◽  
Isabel Feuerstein ◽  
Birgit Stenzel ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Mass Spectrometry ◽  
High Throughput ◽  
Mass Spectrometry Data ◽  
Cancer Prediction

Nonparametric Pre-Processing Methods and Inference Tools for Analyzing Time-of-Flight Mass Spectrometry Data.

2007 ◽  
Vol 3 (2) ◽  
pp. 127-147 ◽  
Author(s):  
Anestis Antoniadis ◽  
Jeremie Bigot ◽  
Sophie Lambert-Lacroix ◽  
Frederique Letue
Keyword(s):  
Mass Spectrometry ◽  
Time Of Flight ◽  
Mass Spectrometry Data ◽  
Processing Methods ◽  
Flight Mass Spectrometry

Interlaboratory Comparison of Untargeted Mass Spectrometry Data Uncovers Underlying Causes for Variability

2021 ◽  
Author(s):  
Trevor N. Clark ◽  
Joëlle Houriet ◽  
Warren S. Vidar ◽  
Joshua J. Kellogg ◽  
Daniel A. Todd ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Interlaboratory Comparison ◽  
Mass Spectrometry Data ◽  
Underlying Causes

TopPIC Gateway: A Web Gateway for Top-Down Mass Spectrometry Data Interpretation

2020 ◽  
Author(s):  
In Kwon Choi ◽  
Eroma Abeysinghe ◽  
Eric Coulter ◽  
Suresh Marru ◽  
Marlon Pierce ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Data Interpretation ◽  
Mass Spectrometry Data ◽  
Top Down ◽  
Top Down Mass Spectrometry

scholarly journals mzML—a Community Standard for Mass Spectrometry Data

2010 ◽  
Vol 10 (1) ◽  
pp. R110.000133 ◽  
Author(s):  
Lennart Martens ◽  
Matthew Chambers ◽  
Marc Sturm ◽  
Darren Kessner ◽  
Fredrik Levander ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Mass Spectrometry Data ◽  
Community Standard
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