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MetabolomicsUnraveling the Heterogeneity of Hyperuricemia Using Untargeted Metabolomics and Statistical Modeling

Background. Hyperuricemia is the second most prevalent metabolic disorder globally and exhibits pronounced heterogeneity in clinical practice. Only about 10% of individuals with asymptomatic hyperuricemia (HUA) progress to gout, yet the lack of specific biomarkers and precise therapeutic targets ...

2025-10-05 | MTBLS13094 | MetaboLights
MetabolomicsClinacanthus nutans fractions exert anti-nasopharyngeal carcinoma effects: integrating untargeted metabolomics, network pharmacology, molecular docking and experimental validation

Background: Clinacanthus nutans (C. nutans), a Southeast Asian medicinal herb, has ethnopharmacological potential against nasopharyngeal carcinoma (NPC). This study aimed to elucidate the bioactive compounds, potential molecular targets, and regulatory pathways responsible for the anticancer acti...

2026-01-05 | MTBLS13610 | MetaboLights
TranscriptomicsModeling regulatory relationships in Arabidopsis immune signaling network.
Expression profiles of 22 reference Arabidopsis immunity mutants were collected using the Arabidopsis Pathoarray 464_001 (GPL3638) in order to build a network model predicting the Arabidopsis immune signaling network. Biological signaling processes may be mediated by complex networks in which netwo...
ORGANISM(S): Arabidopsis thaliana 
2010-07-22 | E-GEOD-19663 | biostudies-arrayexpress
MetabolomicsMicrobiome network remodeling drives soil lipid metabolism under safflower cropping systems at different sites: An omics-based dissection
This study investigated the effects of three planting pattern–location combinations (PLMEs) on safflower rhizosphere soil microbiota and metabolic functions: soybean-safflower rotation at Chenghai (CH), tobacco–safflower rotation at Longpan (ZYHY), and apple orchard intercropping at Lijiang(LJ). Eac...
2026-07-22 | MTBLS15129 | MetaboLights
TranscriptomicsModeling Inducible Human Tissue Neoplasia Identifies an ECM Interaction Network Involved in Cancer Progression
To elucidate mechanisms of cancer progression, we generated inducible human neoplasia in 3-dimensionally intact epithelial tissue. Gene expression profiling of both epithelia and stroma at specific time points during tumor progression revealed sequential enrichment of genes mediating discrete biolog...
ORGANISM(S): Mus musculus 
2009-06-02 | E-GEOD-15299 | biostudies-arrayexpress
TranscriptomicsModeling Familial Cancer with iPSC Approaches
In vitro modeling of human disease has recently become feasible with the adoption of induced pluripotent stem cell (iPSC) technology. Here, we established patient-derived iPSCs from an Li-Fraumeni Syndrome (LFS) family and investigated the role of mutant p53 in the development of osteosarcoma (OS). ...
ORGANISM(S): Homo sapiens 
2015-04-10 | E-GEOD-58123 | biostudies-arrayexpress
TranscriptomicsSystems Modeling of the Rho Signaling Network
Describing the architecture of robust, nonlinear cell signaling networks is essential to gain a predictive understanding of cellular behavior. The structure of the Drosophila Rho-signaling network, comprised of Rho-family GTPases, RhoGTP Exchange Factors (RhoGEFs), and RhoGTPase Activating Proteins...
ORGANISM(S): Drosophila melanogaster 
2012-12-31 | E-GEOD-18307 | biostudies-arrayexpress
MetabolomicsModel-driven multi-omic data analysis elucidates metabolic immunomodulators of macrophage activation
Macrophages are central players in immune response, manifesting divergent phenotypes to control inflammation and innate immunity through release of cytokines and other signaling factors. Recently, the focus on metabolism has been reemphasized as critical signaling and regulatory pathways of human pa...
2012-09-05 | MTBLS23 | MetaboLights
ModelsLiX2019 - macrophage polarization and tumor cell plasticity
This model is based on: Computational Modeling of the Crosstalk Between Macrophage Polarization and Tumor Cell Plasticity in the Tumor Microenvironment. Abstract: Tumor microenvironments contain multiple cell types interacting among one another via different signaling pathways. Furthermore, both ca...
2019-09-23 | MODEL1909230002 | BioModels
Immuno-oncology 
TranscriptomicsNatural Cubic Spline Regression Modeling Followed by Dynamic Network Reconstruction for the Identification of Radiation-Sensitivity Gene Association Networks from Time-course Transcriptome data.
Time course gene-expression profiling was conducted in human lymphoblastoid cell lines (LUCY) after exposure with 1Gy and 10Gy gamma irradiation. Differentially expressed genes were identified using natural cubic spline regression modeling (NCSRM) and subsequently subjected to gene regulatory networ...
ORGANISM(S): Homo sapiens 
2016-06-11 | E-MTAB-4829 | biostudies-arrayexpress
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