AIMC Topic: Tandem Mass Spectrometry

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A Machine Learning Based Approach to de novo Sequencing of Glycans from Tandem Mass Spectrometry Spectrum.

IEEE/ACM transactions on computational biology and bioinformatics Jan 1, 2015
Recently, glycomics has been actively studied and various technologies for glycomics have been rapidly developed. Currently, tandem mass spectrometry (MS/MS) is one of the key experimental tools for identification of structures of oligosaccharides. M...
Machine Learning Algorithms Reproducibility of Results Sensitivity and Specificity Polysaccharides Tandem Mass Spectrometry Pattern Recognition, Automated Carbohydrate Sequence Molecular Sequence Data Sequence Analysis Glycomics
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Optimizing artificial neural network models for metabolomics and systems biology: an example using HPLC retention index data.

Bioanalysis Jan 1, 2015
BACKGROUND: Artificial Neural Networks (ANN) are extensively used to model 'omics' data. Different modeling methodologies and combinations of adjustable parameters influence model performance and complicate model optimization.
Neural Networks, Computer Artificial Intelligence Databases, Factual Systems Biology Cluster Analysis Metabolomics Chromatography, High Pressure Liquid Tandem Mass Spectrometry
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