Cargando…
LiPydomics: A Python Package for Comprehensive Prediction of Lipid Collision Cross Sections and Retention Times and Analysis of Ion Mobility-Mass Spectrometry-Based Lipidomics Data
[Image: see text] Comprehensive profiling of lipid species in a biological sample, or lipidomics, is a valuable approach to elucidating disease pathogenesis and identifying biomarkers. Currently, a typical lipidomics experiment may track hundreds to thousands of individual lipid species. However, dr...
Autores principales: | Ross, Dylan H., Cho, Jang Ho, Zhang, Rutan, Hines, Kelly M., Xu, Libin |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American
Chemical
Society
2020
|
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7816765/ https://www.ncbi.nlm.nih.gov/pubmed/33119270 http://dx.doi.org/10.1021/acs.analchem.0c02560 |
Ejemplares similares
-
Evaluating Software Tools for Lipid Identification from Ion Mobility Spectrometry–Mass Spectrometry Lipidomics Data
por: Ross, Dylan H., et al.
Publicado: (2023) -
Large-Scale Structural Characterization of Drug and
Drug-Like Compounds by High-Throughput Ion Mobility-Mass Spectrometry
por: Hines, Kelly M., et al.
Publicado: (2017) -
Evaluation of Collision Cross Section Calibrants for
Structural Analysis of Lipids
by Traveling Wave Ion Mobility-Mass Spectrometry
por: Hines, Kelly M., et al.
Publicado: (2016) -
MSPypeline: a python package for streamlined data analysis of mass spectrometry-based proteomics
por: Heming, Simon, et al.
Publicado: (2022) -
massPix: an R package for annotation and interpretation of mass spectrometry imaging data for lipidomics
por: Bond, Nicholas J., et al.
Publicado: (2017)