Integrating In silico perturbation with multilayer omics to decode regulatory networks in cancer immunity: a new frontier in precision oncology

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In silico knockout is a computational approach that predicts system-wide responses to genetic perturbations in cancer research.
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Multilayer regulatory networks integrate genomic, transcriptomic, proteomic, and metabolomic data to understand tumor microenvironment complexity.
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Advanced methodologies like deep learning and spatial transcriptomics enhance the modeling of cell interactions within the tumor microenvironment.
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In cancer immunology, these approaches help identify immune regulatory genes and mechanisms of immune evasion for therapeutic targeting.
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Despite challenges in multi-omics integration, in silico knockout offers a promising framework for advancing precision immunotherapy.

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