A deep generative model for deciphering cellular dynamics and in silico drug discovery in complex diseases
Zheng Y, Schupp J, Adams T, Clair G, Justet A, Ahangari F, Yan X, Hansen P, Carlon M, Cortesi E, Vermant M, Vos R, De Sadeleer L, Rosas I, Pineda R, Sembrat J, Königshoff M, McDonough J, Vanaudenaerde B, Wuyts W, Kaminski N, Ding J. A deep generative model for deciphering cellular dynamics and in silico drug discovery in complex diseases. Nature Biomedical Engineering 2025, 1-26. PMID: 40542107, DOI: 10.1038/s41551-025-01423-7.Peer-Reviewed Original ResearchComplex cellular dynamicsCellular dynamicsSingle-cell transcriptomic dataIn silico drug discoverySingle-cell transcriptomicsTranscriptome dataPotential therapeutic drug candidateComplex diseasesHuman diseasesIdiopathic pulmonary fibrosisTherapeutic drug candidateCell embeddingDrug discoveryPulmonary fibrosisDrug candidatesDisease progressionHuman tissuesHuman precision-cut lung slicesDynamic analysisPrecision-cut lung slicesPathological landscapeComputational toolsAnti-fibrotic effectsUnagiTranscriptome
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