The rapid evolution of mass spectrometry (MS)-based lipidomics has enabled the simultaneous measurement of numerous lipid classes. With lipidomics datasets becoming increasingly available, lipidomic-focused software tools are required to facilitate data analysis as well as mining of public datasets, integrating lipidomics-unique molecular information, such as lipid class, chain length and unsaturation. To address this need, we developed lipidr, an open-source R/Bioconductor package for data mining and analysis of lipidomics datasets. lipidr implements a comprehensive lipidomic-focused analysis workflow for targeted and untargeted lipidomics. lipidr imports numerical matrices, Skyline exports and Metabolomics Workbench files directly into R,...
Lipids are highly diverse metabolites of pronounced importance in health and disease. While metabolo...
Lipids are natural substances found in all living organisms and involved in many biological function...
Global lipidomics analysis across large sample sizes produces high-content datasets that require ded...
Lipidomics is a newly emerged discipline involving the identification and quantification of thousand...
Lipid analysis gained significant importance due to the enormous range of lipid functions, e.g., ene...
Abstract Background Lipids are ubiquitous and serve numerous biological functions; thus lipids have ...
The potential impact of lipid research has been increasingly realised both in disease treatment and ...
Lipids are dynamic constituents of biological systems, rapidly responding to any changes in physiolo...
In the last ten years, lipidomics has attracted increasing attention as a research tool in a wide ra...
Lipids are ubiquitous in the human organism and play essential roles as components of cell membranes...
Owing to their importance in cellular physiology and pathology as well as to recent technological ad...
Lipids are a broad group of biomolecules involved in diverse critical biological roles such as cellu...
Large amounts of lipidomics data are rapidly becoming available. However, there is a lack of tools c...
Progress in mass spectrometry lipidomics has led to a rapid proliferation of studies across biology ...
<div><p>Protein sequence databases are the pillar upon which modern proteomics is supported, represe...
Lipids are highly diverse metabolites of pronounced importance in health and disease. While metabolo...
Lipids are natural substances found in all living organisms and involved in many biological function...
Global lipidomics analysis across large sample sizes produces high-content datasets that require ded...
Lipidomics is a newly emerged discipline involving the identification and quantification of thousand...
Lipid analysis gained significant importance due to the enormous range of lipid functions, e.g., ene...
Abstract Background Lipids are ubiquitous and serve numerous biological functions; thus lipids have ...
The potential impact of lipid research has been increasingly realised both in disease treatment and ...
Lipids are dynamic constituents of biological systems, rapidly responding to any changes in physiolo...
In the last ten years, lipidomics has attracted increasing attention as a research tool in a wide ra...
Lipids are ubiquitous in the human organism and play essential roles as components of cell membranes...
Owing to their importance in cellular physiology and pathology as well as to recent technological ad...
Lipids are a broad group of biomolecules involved in diverse critical biological roles such as cellu...
Large amounts of lipidomics data are rapidly becoming available. However, there is a lack of tools c...
Progress in mass spectrometry lipidomics has led to a rapid proliferation of studies across biology ...
<div><p>Protein sequence databases are the pillar upon which modern proteomics is supported, represe...
Lipids are highly diverse metabolites of pronounced importance in health and disease. While metabolo...
Lipids are natural substances found in all living organisms and involved in many biological function...
Global lipidomics analysis across large sample sizes produces high-content datasets that require ded...