Mass Spectrometry Data
Denoising Tandem Mass Spectrometry Data
... preprocessing mass spectrometry data is ...of data by grouping adjacent m/z values of the data into small ...the data thus reducing the number of noise peaks present in the ...of ...
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Mass spectrometry data mining for cancer detection
... on mass spectrometry data, such as data acquired by MALDI or SELDI ...of mass spectra can be modeled by (unknown) Gibbs distributions to generate an optimal signature and an associated ...
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Statistical analysis of proteomic mass spectrometry data
... proteomic mass spectrometry ...exist. Mass spectrometry output is high-dimensional and so we firstly develop an algorithm to identify peaks in the spectra in order to reduce the dimensionality ...
183
Quantification and Simulation of Liquid Chromatography-Mass Spectrometry Data
... the data may even be impossible to annotate due to high levels of noise or other ...Public data sets with comprehensive manual annotation are usually not available for many levels of ground ...benchmark ...
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Clustering algorithms for disease classification using mass spectrometry data
... using mass spectrometry data Declaration I declare that this thesis is my own work and has not been submitted in any form for another degree or diploma at any university or other institute of ...
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Genetic Programming for Biomarker Detection in Classification of Mass Spectrometry Data
... of mass spectrometry technology, while the second part describes the background of machine learning, feature manipulation and classification algorithms used throughout the ...of mass ...
246
Comprehensive Methods of MALDI-TOF Mass Spectrometry Data Analysis
... One of the most accurate classifiers used for mass spectrometry data is the Support Vectors Machines (SVM). It was proposed by V.N.Vapnik [10,11,12]. The idea of this method is classification with ...
9
OplAnalyzer: A Toolbox for MALDI-TOF Mass Spectrometry Data Analysis
... Keywords: data analysis, differential analysis, bio-marker discovery, MALDI-TOF, mass spectrometry, OplAnalyzer, ...Introduction Mass spectrometry is an attractive method in proteomics ...
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MSSimulator: Simulation of Mass Spectrometry Data
... E data, for example, ETISEQ. 21 By providing simulated data, we hope to facilitate algorithm development, as the simulator provides an easy means to benchmark the ...E data is generated by ...
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Peaks detection and alignment for mass spectrometry data
... Microarray data has been successfully used to identify genes responsible for many diseases. However, although proteins are coded by genes, there is no one-to-one relationship between the protein and the mRNA due ...
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Challenges in Computational Analysis of Mass Spectrometry Data for Proteomics
... Keywords mass spectrometry, proteomics, bioinformatics 1 Introduction Proteins play the most important role in disease ...sample. Mass spectrometry is an analytical technique that reveals the ...
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Clustering algorithms for disease classification using mass spectrometry data
... electrophoresis, mass spectrometry, and micro ...of data require powerful tools to assist data ...MS data, it is clear that computational methods are needed to analyse the given ...
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MassNet: a functional annotation service for protein mass spectrometry data.
... In order to provide physico-chemical information without any time delay, we provide precalculated physico-chemical properties for all nonredundant protein sequences. Whole proteins’ physico-chemical properties are also ...
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A Bayesian network approach to feature selection in mass spectrometry data
... Resulting Bayesian network models are applied to three blood serum data sets: one artificially generated, one from a 2004 leukemia study, and another from a 2007 prostate ca[r] ...
195
A method for improving SELDI-TOF mass spectrometry data quality
... our data in diagnostic plots [28] (Figure ...determining data quality, for example peak resolution [18,19], however the software packages used in this analysis did not determine this ...
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Preprocessing, Management, and Analysis of Mass Spectrometry Proteomics Data
... introducing Mass Spectrometry, we survey different techniques for spectra pre- processing and we present a first design of a software tool that allows to manage efficient storing and preprocessing of ...
5
Visualization and Integration of Liquid Chromatography/Mass Spectrometry Proteomics Data
... proteomics mass spectrometry data sets with tools such as the ones described ...heterogeneous data sources with LC-MS/MS data and for integration of external software tools for combined ...
115
Data mining in proteomic mass spectrometry
... the mass spec- trum, estimating the average or minimum intensity within the window, and then moving the window across the spectrum to estimate the overall ...
20
Mass spectrometry based proteomics : data analysis and applications
... In data dependent acquisition (DDA) mode, a preset number of top intense peptides are selected for fragmentation, and an exclusion time period is set to avoid the instrument sampling the high abundant peptides ...
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Detection and visualization of communities in mass spectrometry imaging data.
... Conclusion In this paper we demonstrated the general applicability of community detection as an unsupervised clustering tech- nique for the analysis of MSI data from different types of samples. We have developed a ...
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