Zobrazeno 1 - 10
of 109
pro vyhledávání: '"Dennis W, Hill"'
Autor:
David F. Grant, Dennis W. Hill, Stefan Grimme, Philipp Pracht, Erandika Karunaratne, José A. Gascón
Publikováno v:
Anal Chem
The high-throughput identification of unknown metabolites in biological samples remains challenging. Most current non-targeted metabolomics studies rely on mass spectrometry, followed by computational methods that rank thousands of candidate structur
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6b93524baf5766e2c96fd9941f5f3b8e
https://doi.org/10.1021/acs.analchem.1c02244
https://doi.org/10.1021/acs.analchem.1c02244
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 5, Iss 6, p e201302005 (2013)
The identification of compounds in complex mixtures remains challenging despite recent advances in analytical techniques. At present, no single method can detect and quantify the vast array of compounds that might be of potential interest in metabolo
Externí odkaz:
https://doaj.org/article/5276b9821813496194606add7c600c3d
Publikováno v:
Metabolites, Vol 6, Iss 2, p 17 (2016)
Metabolite structure identification remains a significant challenge in nontargeted metabolomics research. One commonly used strategy relies on searching biochemical databases using exact mass. However, this approach fails when the database does not c
Externí odkaz:
https://doaj.org/article/ffc439b59be541c7b6e797042d03640e
Publikováno v:
Anal Chem
Liquid chromatography coupled with electrospray ionization tandem mass spectrometry (LC-ESI-MS/MS) is a major analytical technique used for nontargeted identification of metabolites in biological fluids. Typically, in LC-ESI-MS/MS based database assi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2f06dac463451f12cdbcb6ea390399ba
https://doi.org/10.1021/acs.analchem.8b03118
https://doi.org/10.1021/acs.analchem.8b03118
Publikováno v:
Methods in Molecular Biology ISBN: 9781071600290
Structure elucidation of metabolites (
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cac8ee1f38da2864d42a8029e693e856
https://doi.org/10.1007/978-1-0716-0030-6_18
https://doi.org/10.1007/978-1-0716-0030-6_18
Publikováno v:
Methods in molecular biology (Clifton, N.J.). 2084
Structure elucidation of metabolites (1000 Da) in biofluids is extremely challenging due to the diversity and complexity of chemical structure space. Generally, due to lack of reference tandem mass data (MS
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::bda88daa86ad8c4938c637b28a6aa590
https://pubmed.ncbi.nlm.nih.gov/31729668
https://pubmed.ncbi.nlm.nih.gov/31729668
Autor:
Lowell H. Hall, Shannon Cawley, David F. Grant, Dennis W. Hill, Ming-Hui Chen, Kelly Bugden, L. Mark Hall
Publikováno v:
J Chem Inf Model
The MolFind application has been developed as a nontargeted metabolomics chemometric tool to facilitate structure identification when HPLC biofluids analysis reveals a feature of interest. Here synthetic compounds are selected and measured to form th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9583f106aac7b950af47f0b521c49611
https://europepmc.org/articles/PMC8404481/
https://europepmc.org/articles/PMC8404481/
Autor:
Dennis W. Hill, David F. Grant, Lowell H. Hall, Ming-Hui Chen, Douglas M. Hawkins, L. Mark Hall
Publikováno v:
Current Computer Aided-Drug Design. 10:374-382
A novel approach is developed for modeling situations in which the modeled property is an algebraically transformed version of the original experimental data. In many cases such a transformation results in a data set with a significantly smaller data
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::831c64f865ad9aec5ca2c0aba4b3f44f
https://doi.org/10.2174/1573409911666141231113516
https://doi.org/10.2174/1573409911666141231113516
Autor:
Dennis W. Hill, Lochana C. Menikarachchi, David F. Grant, Lowell H. Hall, L. Mark Hall, Ming-Hui Chen
Publikováno v:
Bioanalysis. 7:939-955
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. Methodology: We eva
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6be82c309fc2f42196a50b62db9d784a
https://doi.org/10.4155/bio.15.1
https://doi.org/10.4155/bio.15.1
Publikováno v:
Identification and Data Processing Methods in Metabolomics. :6-18
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6df75279843b6a9b990a295e31f3d470
https://doi.org/10.4155/fseb2013.14.157
https://doi.org/10.4155/fseb2013.14.157