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- W4379095497 abstract "Acquisition of omics data advances at a formidable pace. Yet, our ability to utilize these data to control cell phenotypes and design interventions that reverse pathological states lags behind. Here, we posit that cell states are determined by core networks that control cell-wide networks. To steer cell fate decisions, core networks connecting genotype to phenotype must be reconstructed and understood. A recent method, cell state transition assessment and regulation (cSTAR), applies perturbation biology to quantify causal connections and mechanistically models how core networks influence cell phenotypes. cSTAR models are akin to digital cell twins enabling us to purposefully convert pathological states back to physiologically normal states. While this capability has a range of applications, here we discuss reverting oncogenic transformation." @default.
- W4379095497 created "2023-06-03" @default.
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- W4379095497 date "2023-11-01" @default.
- W4379095497 modified "2023-10-15" @default.
- W4379095497 title "Reversing pathological cell states: the road less travelled can extend the therapeutic horizon" @default.
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- W4379095497 doi "https://doi.org/10.1016/j.tcb.2023.04.004" @default.
- W4379095497 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37263821" @default.
- W4379095497 hasPublicationYear "2023" @default.
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