LipidOne 2.0: A Web Tool for Discovering Biological Meanings Hidden in Lipidomic Data
Husam B. R. Alabed, Dorotea Frongia Mancini, Sandra Buratta, Eleonora Calzoni, Danika Di Giacomo, Carla Emiliani, Sabata Martino, Lorena Urbanelli, Roberto Maria Pellegrino
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Abstract
LipidOne 2.0 (https://lipidone.eu) is a new web bioinformatic tool for the analysis of lipidomic data. It facilitates the exploration of the three structural levels of lipids: classes, molecular species, and lipid building blocks (acyl, alkyl, or alkenes chains). The tool's flexibility empowers users to seamlessly include or exclude experimental groups and lipid classes at any stage of the analysis. LipidOne 2.0 offers a range of mono- and multivariate statistical analyses, specifically tailored to each structural level. This includes a novel lipid biomarker identification function, integrating four diverse statistical parameters. LipidOne 2.0 incorporates Lipid Pathway analysis across all three structural levels of lipids. Users can identify lipid-involved reactions through case-control comparisons, generating lists of genes/enzymes and their activation states based on Z scores. Accessible without the need for registration, LipidOne 2.0 provides a user-friendly and efficient platform for exploring and analyzing lipidomic data. © 2024 The Author(s). Current Protocols published by Wiley Periodicals LLC.
Basic Protocol 1: Dataset preparation for LipidOne 2.0
Support Protocol: Lipid nomenclature from spectrometric experiments
Basic Protocol 2: Uploading a dataset into LipidOne 2.0
Basic Protocol 3: Data mining of lipidomic dataset by LipidOne 2.0
LipidOne 2.0:发现脂质体数据中隐藏的生物学意义的网络工具
LipidOne 2.0 (https://lipidone.eu) 是一种用于分析脂质体数据的新型网络生物信息学工具。它有助于探索脂质的三个结构层次:类、分子物种和脂质构件(酰基、烷基或烯链)。该工具的灵活性使用户能够在分析的任何阶段无缝地加入或排除实验组和脂质类别。LipidOne 2.0 提供一系列单变量和多变量统计分析,专门针对每个结构层次。其中包括一种新颖的脂质生物标记识别功能,整合了四种不同的统计参数。LipidOne 2.0 结合了所有三个结构层次的脂质途径分析。用户可以通过病例对照比较来识别涉及脂质的反应,根据 Z 分数生成基因/酶及其激活状态列表。LipidOne 2.0 无需注册即可访问,为探索和分析脂质体数据提供了一个用户友好的高效平台。© 2024 作者。基本协议 1:为 LipidOne 2.0 准备数据集支持协议:基本协议 2:将数据集上传到 LipidOne 2.0基本协议 3:通过 LipidOne 2.0 对脂质体数据集进行数据挖掘
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