In the field of lipidomics, where the complexity of lipid structures and functions presents significant analytical challenges, LipidSig stands out as the first web-based platform providing integrated, comprehensive analysis for efficient data mining of lipidomic datasets. The upgraded LipidSig 2.0 (https://lipidsig.
View Article and Find Full Text PDFAdvancements in high-throughput technology offer researchers an extensive range of multi-omics data that provide deep insights into the complex landscape of cancer biology. However, traditional statistical models and databases are inadequate to interpret these high-dimensional data within a multi-omics framework. To address this limitation, we introduce DriverDBv4, an updated iteration of the DriverDB cancer driver gene database (http://driverdb.
View Article and Find Full Text PDFWith the continuing rise of lipidomic studies, there is an urgent need for a useful and comprehensive tool to facilitate lipidomic data analysis. The most important features making lipids different from general metabolites are their various characteristics, including their lipid classes, double bonds, chain lengths, etc. Based on these characteristics, lipid species can be classified into different categories and, more interestingly, exert specific biological functions in a group.
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