Article

Morphological fingerprints enable machine learning based inference of neuroblastoma cell states without transcriptomics

2026-05-13

Abstract excerpt

Inference of cancer cell states is essential for understanding oncogenic mechanisms and predicting clinical outcomes, yet current reliance on transcriptomic profiling limits scalability and real-time monitoring. Here, we show that cell morphology provides a low-dimensional, observable representation of cellular identity and its dynamics. Using neuroblastoma (NB) as a model system, we establish a machine learning-...

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Literature Corpus work: 5e7f926d-0eb9-5b10-b81b-db2c974017ae
DOI: 10.64898/2026.05.12.724731

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