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Full-Text Articles in Bioinformatics
Atom Identifiers Generated By A Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization Across Metabolic Databases, Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley
Atom Identifiers Generated By A Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization Across Metabolic Databases, Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley
Molecular and Cellular Biochemistry Faculty Publications
Metabolic flux analysis requires both a reliable metabolic model and reliable metabolic profiles in characterizing metabolic reprogramming. Advances in analytic methodologies enable production of high-quality metabolomics datasets capturing isotopic flux. However, useful metabolic models can be difficult to derive due to the lack of relatively complete atom-resolved metabolic networks for a variety of organisms, including human. Here, we developed a neighborhood-specific graph coloring method that creates unique identifiers for each atom in a compound facilitating construction of an atom-resolved metabolic network. What is more, this method is guaranteed to generate the same identifier for symmetric atoms, enabling automatic identification of …
Differential Abundance And Clustering Analysis With Empirical Bayes Shrinkage Estimation Of Variance (Dasev) For Proteomics And Metabolomics Data, Zhengyan Huang
Theses and Dissertations--Epidemiology and Biostatistics
Mass spectrometry (MS) is widely used for proteomic and metabolomic profiling of biological samples. Data obtained by MS are often zero-inflated. Those zero values are called point mass values (PMVs). Zero values can be further grouped into biological PMVs and technical PMVs. The former type is caused by the absence of components and the latter type is caused by detection limit. There is no simple solution to separate those two types of PMVs. Mixture models were developed to separate the two types of zeros apart and to perform the differential abundance analysis. However, we notice that the mixture model can …