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Interpreting the li...
Interpreting the lipidome : bioinformatic approaches to embrace the complexity
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- Kyle, Jennifer E. (author)
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
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- Aimo, Lucila (author)
- Swiss-Prot Group, SIB Swiss Institute of Bioinformatics, Geneva, Switzerland
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- Bridge, Alan J. (author)
- Swiss-Prot Group, SIB Swiss Institute of Bioinformatics, Geneva, Switzerland
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- Clair, Geremy (author)
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
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- Fedorova, Maria (author)
- Institute of Bioanalytical Chemistry, Faculty of Chemistry and Mineralogy, Center for Biotechnology and Biomedicine, Universität Leipzig, Leipzig, Germany
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- Helms, J. Bernd (author)
- Department of Biomolecular Health Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands
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- Molenaar, Martijn R. (author)
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
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- Ni, Zhixu (author)
- Institute of Bioanalytical Chemistry, Faculty of Chemistry and Mineralogy, Center for Biotechnology and Biomedicine, Universität Leipzig, Leipzig, Germany
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- Oresic, Matej, 1967- (author)
- Örebro universitet,Institutionen för medicinska vetenskaper,Turku Bioscience Centre, University of Turku and Åbo Akademi University, Turku, Finland
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- Slenter, Denise (author)
- Department of Bioinformatics-BiGCaT, NUTRIM, Maastricht University, Maastricht, The Netherlands
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- Willighagen, Egon (author)
- Department of Bioinformatics-BiGCaT, NUTRIM, Maastricht University, Maastricht, The Netherlands
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- Webb-Robertson, Bobbie-Jo M. (author)
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
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(creator_code:org_t)
- 2021-06-06
- 2021
- English.
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In: Metabolomics. - : Springer-Verlag New York. - 1573-3882 .- 1573-3890. ; 17:6
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
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- BACKGROUND: Improvements in mass spectrometry (MS) technologies coupled with bioinformatics developments have allowed considerable advancement in the measurement and interpretation of lipidomics data in recent years. Since research areas employing lipidomics are rapidly increasing, there is a great need for bioinformatic tools that capture and utilize the complexity of the data. Currently, the diversity and complexity within the lipidome is often concealed by summing over or averaging individual lipids up to (sub)class-based descriptors, losing valuable information about biological function and interactions with other distinct lipids molecules, proteins and/or metabolites.AIM OF REVIEW: To address this gap in knowledge, novel bioinformatics methods are needed to improve identification, quantification, integration and interpretation of lipidomics data. The purpose of this mini-review is to summarize exemplary methods to explore the complexity of the lipidome.KEY SCIENTIFIC CONCEPTS OF REVIEW: Here we describe six approaches that capture three core focus areas for lipidomics: (1) lipidome annotation including a resolvable database identifier, (2) interpretation via pathway- and enrichment-based methods, and (3) understanding complex interactions to emphasize specific steps in the analytical process and highlight challenges in analyses associated with the complexity of lipidome data.
Subject headings
- NATURVETENSKAP -- Biologi -- Bioinformatik och systembiologi (hsv//swe)
- NATURAL SCIENCES -- Biological Sciences -- Bioinformatics and Systems Biology (hsv//eng)
Keyword
- Bioinformatics
- Data integration
- Lipid Identification
- Lipidomics
- Ontologies
- Pathway enrichment
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- By the author/editor
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Kyle, Jennifer E ...
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Aimo, Lucila
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Bridge, Alan J.
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Clair, Geremy
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Fedorova, Maria
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Helms, J. Bernd
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show more...
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Molenaar, Martij ...
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Ni, Zhixu
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Oresic, Matej, 1 ...
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Slenter, Denise
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Willighagen, Ego ...
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Webb-Robertson, ...
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- About the subject
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- NATURAL SCIENCES
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NATURAL SCIENCES
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and Biological Scien ...
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and Bioinformatics a ...
- Articles in the publication
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Metabolomics
- By the university
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Örebro University