Using fragmentation trees and mass spectral trees for identifying unknown compounds in metabolomics.

Identification of unknown metabolites is the bottleneck in advancing metabolomics, leaving interpretation of metabolomics results ambiguous. The chemi...
NAN Sizes 5 Downloads 29 Views

Recommend Documents


Fragmentation trees reloaded.
Untargeted metabolomics commonly uses liquid chromatography mass spectrometry to measure abundances of metabolites; subsequent tandem mass spectrometry is used to derive information about individual compounds. One of the bottlenecks in this experimen

Metabolite identification through multiple kernel learning on fragmentation trees.
Metabolite identification from tandem mass spectrometric data is a key task in metabolomics. Various computational methods have been proposed for the identification of metabolites from tandem mass spectra. Fragmentation tree methods explore the space

Molecular Formula Identification Using Isotope Pattern Analysis and Calculation of Fragmentation Trees.
We present the results of a fully automated de novo approach for identification of molecular formulas in the CASMI 2013 contest. Only results for Category 1 (molecular formula identification) were submitted. Our approach combines isotope pattern anal

Computational analyses of spectral trees from electrospray multi-stage mass spectrometry to aid metabolite identification.
Mass spectrometry coupled with chromatography has become the major technical platform in metabolomics. Aided by peak detection algorithms, the detected signals are characterized by mass-over-charge ratio (m/z) and retention time. Chemical identities

Comparative study of biodegradability prediction of chemicals using decision trees, functional trees, and logistic regression.
Biodegradation is the principal environmental dissipation process of chemicals. As such, it is a dominant factor determining the persistence and fate of organic chemicals in the environment, and is therefore of critical importance to chemical managem

Spectral envelope and periodic component in classification trees for pathological voice diagnostic.
This work investigates the effectiveness of features from the spectral envelope such as the frequency and bandwidth of the first peak obtained from a 30(th) order Linear Predictive Coefficients (LPC) to identify pathological voices. Other spectral fe

On coalescence analysis using genealogy rooted trees.
DNA sequence data are now being used to study the ancestral history of human population. The existing methods for such coalescence inference use recursion formula to compute the data probabilities. These methods are useful in practical applications,

Ctenophore trees.
Comb jellies are remarkably different from other animals. Phylogenetic analyses of broadly sampled ctenophore transcriptome data provide additional evidence that they are the sister group to all other animals and reveal details of their evolutionary