Skip to main page content
Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation

Search Page

My NCBI Filters
Results by year

Table representation of search results timeline featuring number of search results per year.

Year Number of Results
2009 1
2010 1
2011 2
2014 1
2015 2
2016 4
2017 3
2018 4
2019 5
2020 3
2021 5
2022 4
Text availability
Article attribute
Article type
Publication date

Search Results

31 results
Results by year
Filters applied: . Clear all
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
Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases.
Sun YV, Hu YJ. Sun YV, et al. Adv Genet. 2016;93:147-90. doi: 10.1016/bs.adgen.2015.11.004. Epub 2016 Jan 25. Adv Genet. 2016. PMID: 26915271 Free PMC article. Review.
Complex and dynamic networks of molecules are involved in human diseases. High-throughput technologies enable omics studies interrogating thousands to millions of makers with similar biochemical properties (eg, transcriptomics for RNA transcripts). ...We seek to pro …
Complex and dynamic networks of molecules are involved in human diseases. High-throughput technologies enable omics studies in …
High Throughput Multi-Omics Approaches for Clinical Trial Evaluation and Drug Discovery.
Zielinski JM, Luke JJ, Guglietta S, Krieg C. Zielinski JM, et al. Front Immunol. 2021 Mar 31;12:590742. doi: 10.3389/fimmu.2021.590742. eCollection 2021. Front Immunol. 2021. PMID: 33868223 Free PMC article. Review.
These atlases build an ideal scientific discovery environment for reference and data mining approaches, which often times reveals new cellular disease networks. In this review we will discuss how combinations and fusions of different -omic workflows on a single cell …
These atlases build an ideal scientific discovery environment for reference and data mining approaches, which often times reveals new …
A large-scale analysis of targeted metabolomics data from heterogeneous biological samples provides insights into metabolite dynamics.
Lee HJ, Kremer DM, Sajjakulnukit P, Zhang L, Lyssiotis CA. Lee HJ, et al. Metabolomics. 2019 Jul 9;15(7):103. doi: 10.1007/s11306-019-1564-8. Metabolomics. 2019. PMID: 31289941 Free PMC article.
INTRODUCTION: We previously developed a tandem mass spectrometry-based label-free targeted metabolomics analysis framework coupled to two distinct chromatographic methods, reversed-phase liquid chromatography (RPLC) and hydrophilic interaction liquid chromatography (HILIC) …
INTRODUCTION: We previously developed a tandem mass spectrometry-based label-free targeted metabolomics analysis framework coupled to …
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 …
Age-Related Neurometabolomic Signature of Mouse Brain.
Chen S, Lee J, Truong TM, Alhassen S, Baldi P, Alachkar A. Chen S, et al. ACS Chem Neurosci. 2021 Aug 4;12(15):2887-2902. doi: 10.1021/acschemneuro.1c00259. Epub 2021 Jul 20. ACS Chem Neurosci. 2021. PMID: 34283556
Therefore, this study aimed to identify mouse brain metabolic profiles in neonatal and adult stages and reconstruct both the active metabolic network and the metabolic pathway functioning. Using high-throughput metabolomics and bioinformatics analyses, we show that …
Therefore, this study aimed to identify mouse brain metabolic profiles in neonatal and adult stages and reconstruct both the active metaboli …
Visualizing metabolic network dynamics through time-series metabolomic data.
Buchweitz LF, Yurkovich JT, Blessing C, Kohler V, Schwarzkopf F, King ZA, Yang L, Jóhannsson F, Sigurjónsson ÓE, Rolfsson Ó, Heinrich J, Dräger A. Buchweitz LF, et al. BMC Bioinformatics. 2020 Apr 3;21(1):130. doi: 10.1186/s12859-020-3415-z. BMC Bioinformatics. 2020. PMID: 32245365 Free PMC article.
BACKGROUND: New technologies have given rise to an abundance of -omics data, particularly metabolomic data. The scale of these data introduces new challenges for the interpretation and extraction of knowledge, requiring the development of innovative co …
BACKGROUND: New technologies have given rise to an abundance of -omics data, particularly metabolomic data. The scale o …
CANTARE: finding and visualizing network-based multi-omic predictive models.
Siebert JC, Saint-Cyr M, Borengasser SJ, Wagner BD, Lozupone CA, Görg C. Siebert JC, et al. BMC Bioinformatics. 2021 Feb 19;22(1):80. doi: 10.1186/s12859-021-04016-8. BMC Bioinformatics. 2021. PMID: 33607938 Free PMC article.
METHODS: We present a novel workflow for building predictive regression models from network neighborhoods in multi-omic networks. First, we generate pairwise regression models across all pairs of analytes from all omes, encoding the resulting "top table" of relation …
METHODS: We present a novel workflow for building predictive regression models from network neighborhoods in multi-omic networks
First plant cell atlas workshop report.
Rice S, Fryer E, Ghosh Jha S, Malkovskiy A, Meyer H, Thomas J, Weizbauer R, Zhao K, Birnbaum K, Ehrhardt D, Wang Z, Rhee SY; Plant Cell Atlas Consortium. Rice S, et al. Plant Direct. 2020 Oct 15;4(10):e00271. doi: 10.1002/pld3.271. eCollection 2020 Oct. Plant Direct. 2020. PMID: 33083684 Free PMC article.
A long-term goal is to delineate all molecules within the cell at high spatio-temporal resolution, obtain information about interacting molecular networks, and identify the contribution of these networks to development of the organism as a whole. As a first step, we …
A long-term goal is to delineate all molecules within the cell at high spatio-temporal resolution, obtain information about interacting mole …
Quantification of molecular heterogeneity in kidney tissue by targeted proteomics.
Hoyer KJR, Dittrich S, Bartram MP, Rinschen MM. Hoyer KJR, et al. J Proteomics. 2019 Feb 20;193:85-92. doi: 10.1016/j.jprot.2018.03.001. Epub 2018 Mar 6. J Proteomics. 2019. PMID: 29522878 Review.
Mass-spectrometry based proteomics provides a unique opportunity to interrogate heterogeneity and dynamics of various proteome layers within the kidney to better understand physiology and pathophysiology, and to translate signaling networks into therapies. Yet, the …
Mass-spectrometry based proteomics provides a unique opportunity to interrogate heterogeneity and dynamics of various proteome layers …
31 results