ArticleBioinformatics (Oxford, England)2015
The SwissLipids knowledgebase for lipid biology.
Article in Bioinformatics (Oxford, England), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 95 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
95 citing papers in PubMed, 154 citations in OpenAlex.
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- FatPlants 2.0: an AI-powered platform integrating plant lipid genes, pathways, and literature.The Plant journal : for cell and molecular biology · 2026Article
- LipiDecipher: A Structure-Oriented Analytical Framework for Interpretable Clinical Lipidomics.Metabolites · 2026Article
- A Step-by-Step Protocol From METASPACE to Biological Interpretation.Journal of mass spectrometry : JMS · 2026Article
- Navigating the lipid universe with LipidLibrarian: a cross-linked database for lipidomics data integration.Journal of lipid research · 2026Article
- Eigenlipids for exploring lipid biology.Journal of lipid research · 2026Review
- Predictive Algal Systems Biology: Integrating Omics, Genome-Scale Metabolic Models, and Machine Learning.Bioengineering (Basel, Switzerland) · 2026Review
- A lipidomics roadmap: from basic research to societal challenges.Nature communications · 2026Review
- Selecting methods for draft GEM generation in multicellular eukaryotes: a comparative analysis.BMC bioinformatics · 2026Article
- Assessing current capabilities for incorporating lipidomics in multiomics data integration.Briefings in bioinformatics · 2026Review
- Selective Editing and Functionalization of the Mammalian Lipidome.bioRxiv : the preprint server for biology · 2026Article
- Layer-by-layer decoding of contemporary and historic painting composition using MALDI mass spectrometry imaging and machine learning.Science advances · 2026Article
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- The contributions of lean muscle, intramuscular fat, and subcutaneous fat to lipids within the beef matrix.Journal of animal science · 2026Article
- MetaNetX: a bridge between metabolic resources for enhanced curation and multi-omics data harmonization.Nucleic acids research · 2026Article
- Multimodal landscape of atherosclerotic plaques: A spatial omics approach with mass spectrometry imaging.Analytica chimica acta · 2025Review
- Spatial lipidomics reveals demyelination and remyelination dynamics in the mouse brain.Journal of lipid research · 2025Article
- Current status and challenges of multi-omics research using animal models of atherosclerosis.Journal of molecular and cellular cardiology plus · 2025Review
- Article
35 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
motivationLipids are a large and diverse group of biological molecules with roles in membrane formation, energy storage and signaling. Cellular lipidomes may contain tens of thousands of structures, a staggering degree of complexity whose significance is not yet fully understood. High-throughput mass spectrometry-based platforms provide a means to study this complexity, but the interpretation of lipidomic data and its integration with prior knowledge of lipid biology suffers from a lack of appropriate tools to manage the data and extract knowledge from it.
resultsTo facilitate the description and exploration of lipidomic data and its integration with prior biological knowledge, we have developed a knowledge resource for lipids and their biology-SwissLipids. SwissLipids provides curated knowledge of lipid structures and metabolism which is used to generate an in silico library of feasible lipid structures. These are arranged in a hierarchical classification that links mass spectrometry analytical outputs to all possible lipid structures, metabolic reactions and enzymes. SwissLipids provides a reference namespace for lipidomic data publication, data exploration and hypothesis generation. The current version of SwissLipids includes over 244 000 known and theoretically possible lipid structures, over 800 proteins, and curated links to published knowledge from over 620 peer-reviewed publications. We are continually updating the SwissLipids hierarchy with new lipid categories and new expert curated knowledge. AVAILABILITY: SwissLipids is freely available at http://www.swisslipids.org/. CONTACT: alan.bridge@isb-sib.ch SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.