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Towards a systems-level understanding of mitochondrial biology.

Cell Calcium 95:102364 (2021)
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Human mitochondria are complex and highly dynamic biological systems, comprised of over a thousand parts and evolved to fully integrate into the specialized intracellular signaling networks and metabolic requirements of each cell and organ. Over the last two decades, several complementary, top-down computational and experimental approaches have been developed to identify, characterize and modulate the human mitochondrial system, demonstrating the power of integrating classical reductionist and discovery-driven analyses in order to de-orphanize hitherto unknown molecular components of mitochondrial machineries and pathways. To this goal, systematic, multiomics-based surveys of proteome composition, protein networks, and phenotype-to-pathway associations at the tissue, cell and organellar level have been largely exploited to predict the full complement of mitochondrial proteins and their functional interactions, therefore catalyzing data-driven hypotheses. Collectively, these multidisciplinary and integrative research approaches hold the potential to propel our understanding of mitochondrial biology and provide a systems-level framework to unraveling mitochondria-mediated and disease-spanning pathomechanisms.
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Publication type Article: Journal article
Document type Scientific Article
Keywords Functional Associations ; Integrative Analyses ; Mitochondrial System ; Multiomics Approaches
Language english
Publication Year 2021
HGF-reported in Year 2021
ISSN (print) / ISBN 0143-4160
e-ISSN 1532-1991
Journal Cell calcium
Quellenangaben Volume: 95, Issue: , Pages: , Article Number: 102364 Supplement: ,
Publisher Elsevier
Publishing Place Amsterdam
Reviewing status Peer reviewed
POF-Topic(s) 30201 - Metabolic Health
Research field(s) Helmholtz Diabetes Center
PSP Element(s) G-502295-001
G-502200-001
Grants ExNet-0041-Phase2-3 ("SyNergy-HMGU") through the Initiative and Network Fund of the Helmholtz Association
Munich Center for Systems Neurology (SyNergy EXC 2145)
Scopus ID 85100789022
PubMed ID 33601101
Erfassungsdatum 2021-04-21