{"database":"bioimages","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"submitter":[null],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-BIAD1415"],"repository":["bioimages"],"additional_accession":[" E-MTAB-14521"],"figure_sub":["Specimen","Image analysis","Annotations","Study Component","organisation","Biosample","Associations","Image acquisition"],"pubmed_authors":["Christian Tischer","Manuel Gunkel","Muzamil Majid Khan","Beate Neumann","Mira Burtscher","Sarah Kaspar","Rainer Pepperkok","Isabel Kemmer","Nadine Tüchler","Aliaksandr Halavatyi","Denes Türei"]},"is_claimable":false,"name":"Dynamic multi-omics and mechanistic modeling approach uncovers novel mechanisms of kidney fibrosis progression","description":"Kidney fibrosis, characterized by excessive extracellular matrix (ECM) deposition, affects 10% of the population but lacks specific treatments. This study uses a multi-omics approach with human kidney PDGFRβ+ mesenchymal cells to analyze ECM changes. Through network modeling integrating various -omics data with ECM imaging, we tracked biomolecule changes across seven time points after TGF-β stimulation. The analysis revealed temporal patterns in ECM-related markers and modulators. Through validation experiments, we identified transcription factors like FLI1 and E2F1 as negative regulators of collagen deposition, providing insights into ECM regulation in kidney fibrosis progression.","dates":{"release":"2024-10-15T00:00:00Z","modification":"2024-10-14T17:24:01.754Z","creation":"2024-10-13T08:00:18.682Z"},"accession":"S-BIAD1415","cross_references":{}}