Investigating Global Lipidome Alterations with the Lipid Network Explorer
Lipids play an important role in biological systems and have the potential to serve as biomarkers in medical applications. Advances in lipidomics allow identification of hundreds of lipid species from biological samples. However, a systems biological analysis of the lipidome, by incorporating pathwa...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-07-01
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| Series: | Metabolites |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2218-1989/11/8/488 |
| _version_ | 1797522896260694016 |
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| author | Nikolai Köhler Tim Daniel Rose Lisa Falk Josch Konstantin Pauling |
| author_facet | Nikolai Köhler Tim Daniel Rose Lisa Falk Josch Konstantin Pauling |
| author_sort | Nikolai Köhler |
| collection | DOAJ |
| description | Lipids play an important role in biological systems and have the potential to serve as biomarkers in medical applications. Advances in lipidomics allow identification of hundreds of lipid species from biological samples. However, a systems biological analysis of the lipidome, by incorporating pathway information remains challenging, leaving lipidomics behind compared to other omics disciplines. An especially uncharted territory is the integration of statistical and network-based approaches for studying global lipidome changes. Here we developed the Lipid Network Explorer (LINEX), a web-tool addressing this gap by providing a way to visualize and analyze functional lipid metabolic networks. It utilizes metabolic rules to match biochemically connected lipids on a species level and combine it with a statistical correlation and testing analysis. Researchers can customize the biochemical rules considered, to their tissue or organism specific analysis and easily share them. We demonstrate the benefits of combining network-based analyses with statistics using publicly available lipidomics data sets. LINEX facilitates a biochemical knowledge-based data analysis for lipidomics. It is availableas a web-application and as a publicly available docker container. |
| first_indexed | 2024-03-10T08:35:51Z |
| format | Article |
| id | doaj.art-10a0eaf7c1364be6b1b7f21bb7d0c6fa |
| institution | Directory Open Access Journal |
| issn | 2218-1989 |
| language | English |
| last_indexed | 2024-03-10T08:35:51Z |
| publishDate | 2021-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Metabolites |
| spelling | doaj.art-10a0eaf7c1364be6b1b7f21bb7d0c6fa2023-11-22T08:39:01ZengMDPI AGMetabolites2218-19892021-07-0111848810.3390/metabo11080488Investigating Global Lipidome Alterations with the Lipid Network ExplorerNikolai Köhler0Tim Daniel Rose1Lisa Falk2Josch Konstantin Pauling3LipiTUM, Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, 85354 Freising, GermanyLipiTUM, Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, 85354 Freising, GermanyLipiTUM, Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, 85354 Freising, GermanyLipiTUM, Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, 85354 Freising, GermanyLipids play an important role in biological systems and have the potential to serve as biomarkers in medical applications. Advances in lipidomics allow identification of hundreds of lipid species from biological samples. However, a systems biological analysis of the lipidome, by incorporating pathway information remains challenging, leaving lipidomics behind compared to other omics disciplines. An especially uncharted territory is the integration of statistical and network-based approaches for studying global lipidome changes. Here we developed the Lipid Network Explorer (LINEX), a web-tool addressing this gap by providing a way to visualize and analyze functional lipid metabolic networks. It utilizes metabolic rules to match biochemically connected lipids on a species level and combine it with a statistical correlation and testing analysis. Researchers can customize the biochemical rules considered, to their tissue or organism specific analysis and easily share them. We demonstrate the benefits of combining network-based analyses with statistics using publicly available lipidomics data sets. LINEX facilitates a biochemical knowledge-based data analysis for lipidomics. It is availableas a web-application and as a publicly available docker container.https://www.mdpi.com/2218-1989/11/8/488computational lipidomicscomputational systems biologynetwork biologybioinformaticslipidomicslipids |
| spellingShingle | Nikolai Köhler Tim Daniel Rose Lisa Falk Josch Konstantin Pauling Investigating Global Lipidome Alterations with the Lipid Network Explorer Metabolites computational lipidomics computational systems biology network biology bioinformatics lipidomics lipids |
| title | Investigating Global Lipidome Alterations with the Lipid Network Explorer |
| title_full | Investigating Global Lipidome Alterations with the Lipid Network Explorer |
| title_fullStr | Investigating Global Lipidome Alterations with the Lipid Network Explorer |
| title_full_unstemmed | Investigating Global Lipidome Alterations with the Lipid Network Explorer |
| title_short | Investigating Global Lipidome Alterations with the Lipid Network Explorer |
| title_sort | investigating global lipidome alterations with the lipid network explorer |
| topic | computational lipidomics computational systems biology network biology bioinformatics lipidomics lipids |
| url | https://www.mdpi.com/2218-1989/11/8/488 |
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