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Year Number of Results
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65 results

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Page 1
Insights into Dynamic Network States Using Metabolomic Data.
Mostolizadeh R, Dräger A, Jamshidi N. Mostolizadeh R, et al. Methods Mol Biol. 2019;1978:243-258. doi: 10.1007/978-1-4939-9236-2_15. Methods Mol Biol. 2019. PMID: 31119667
Metabolomic data is the youngest of the high-throughput data types; however, it is potentially one of the most informative, as it provides a direct, quantitative biochemical phenotype. ...Genome-scale metabolic network reconstructions provide a natural …
Metabolomic data is the youngest of the high-throughput data types; however, it is potentially one of the most informat …
Global Burden of Cardiovascular Diseases and Risks, 1990-2022.
Mensah GA, Fuster V, Murray CJL, Roth GA; Global Burden of Cardiovascular Diseases and Risks Collaborators. Mensah GA, et al. J Am Coll Cardiol. 2023 Dec 19;82(25):2350-2473. doi: 10.1016/j.jacc.2023.11.007. J Am Coll Cardiol. 2023. PMID: 38092509 Free PMC article. No abstract available.
Omics-Based Investigations of Breast Cancer.
Neagu AN, Whitham D, Bruno P, Morrissiey H, Darie CA, Darie CC. Neagu AN, et al. Molecules. 2023 Jun 14;28(12):4768. doi: 10.3390/molecules28124768. Molecules. 2023. PMID: 37375323 Free PMC article. Review.
Rapid and recent advances in molecular profiling strategies and analytical techniques based on high-throughput sequencing and mass spectrometry (MS) development have generated large-scale multi-omics datasets, mainly emerging from the three "big omics", based on the central dogma …
Rapid and recent advances in molecular profiling strategies and analytical techniques based on high-throughput sequencing and mass spectrome …
Cardiac Fibrosis in the Multi-Omics Era: Implications for Heart Failure.
Ghazal R, Wang M, Liu D, Tschumperlin DJ, Pereira NL. Ghazal R, et al. Circ Res. 2025 Mar 28;136(7):773-802. doi: 10.1161/CIRCRESAHA.124.325402. Epub 2025 Mar 27. Circ Res. 2025. PMID: 40146800 Free PMC article. Review.
High-throughput omics technologies have begun revolutionizing our understanding of the molecular mechanisms driving cardiac fibrosis and are providing unprecedented insights into its heterogeneity and progression. This review provides a comprehensive analysis of how techni …
High-throughput omics technologies have begun revolutionizing our understanding of the molecular mechanisms driving cardiac fibrosis and are …
AI-driven multi-omics modeling of myalgic encephalomyelitis/chronic fatigue syndrome.
Xiong R, Aiken E, Caldwell R, Vernon SD, Kozhaya L, Gunter C, Bateman L, Unutmaz D, Oh J. Xiong R, et al. Nat Med. 2025 Sep;31(9):2991-3001. doi: 10.1038/s41591-025-03788-3. Epub 2025 Jul 25. Nat Med. 2025. PMID: 40715814 Free PMC article.
Here we present BioMapAI, a supervised deep neural network trained on a 4-year, longitudinal, multi-omics dataset from 249 participants, which integrates gut metagenomics, plasma metabolomics, immune cell profiling, blood laboratory data and detailed clinical …
Here we present BioMapAI, a supervised deep neural network trained on a 4-year, longitudinal, multi-omics dataset from 249 participan …
Plant engineering: advances, bottlenecks, and promise.
Brandizzi F, Mortimer J, Denby K. Brandizzi F, et al. Plant J. 2025 Apr;122(2):e70117. doi: 10.1111/tpj.70117. Plant J. 2025. PMID: 40275776
New tools revealed rich interconnectivity in the exponentially growing and dynamic "big 'omics data" of metabolomes, transcriptomes and genomes at previously inaccessible magnitude (global, cross-species, meta-) and resolution (single-cell). Insights e …
New tools revealed rich interconnectivity in the exponentially growing and dynamic "big 'omics data" of metabolomes, tr …
Systems biology for crop improvement.
Pazhamala LT, Kudapa H, Weckwerth W, Millar AH, Varshney RK. Pazhamala LT, et al. Plant Genome. 2021 Jul;14(2):e20098. doi: 10.1002/tpg2.20098. Epub 2021 May 5. Plant Genome. 2021. PMID: 33949787 Free article. Review.
In recent years, generation of large-scale data from genome, transcriptome, proteome, metabolome, epigenome, and others, has become routine in several plant species. Most of these datasets in different crop species, however, were studied independently and as a resul …
In recent years, generation of large-scale data from genome, transcriptome, proteome, metabolome, epigenome, and others, has b …
Dynamic functional network connectivity and its association with lipid metabolism in Alzheimer's disease.
Zang F, Liu X, Fan D, He C, Zhang Z, Xie C; Alzheimer's Disease Neuroimaging Initiative; Alzheimer's Disease Metabolomics Consortium. Zang F, et al. CNS Neurosci Ther. 2024 Sep;30(9):e70029. doi: 10.1111/cns.70029. CNS Neurosci Ther. 2024. PMID: 39302036 Free PMC article.
METHODS: Data from 242 AD spectrum subjects, including biological, neuroimaging, and general cognition, were obtained from the Alzheimer's Disease Neuroimaging Initiative for this cross-sectional study. ...CONCLUSION: The dysfunction of dFNC temporal-spatial pattern …
METHODS: Data from 242 AD spectrum subjects, including biological, neuroimaging, and general cognition, were obtained from the …
Multiomic profiling of chronically activated CD4+ T cells identifies drivers of exhaustion and metabolic reprogramming.
Lawton ML, Inge MM, Blum BC, Smith-Mahoney EL, Bolzan D, Lin W, McConney C, Porter J, Moore J, Youssef A, Tharani Y, Varelas X, Denis GV, Wong WW, Padhorny D, Kozakov D, Siggers T, Wuchty S, Snyder-Cappione J, Emili A. Lawton ML, et al. PLoS Biol. 2024 Dec 17;22(12):e3002943. doi: 10.1371/journal.pbio.3002943. eCollection 2024 Dec. PLoS Biol. 2024. PMID: 39689157 Free PMC article.
Here, we utilize quantitative proteomic, phosphoproteomic, and metabolomic analyses to characterize the molecular basis of the dysfunctional cell state induced by chronic stimulation of CD4+ memory T cells. ...Integrated causal network analysis of our combine …
Here, we utilize quantitative proteomic, phosphoproteomic, and metabolomic analyses to characterize the molecular basis of the dysfun …
65 results