NeST-VNN is an interpretable neural network-based model that predicts cell response to a drug. the first explainable data-driven method for cancer therapeutic response prediction, in which …

2024年3月5日 · NeST-VNN is based on NeST, a whole-cell map of cancer protein complexes derived from systematic proteomics data (see the ‘Structural architecture of the NeST-VNN …

NeST-VNN is an interpretable neural network-based model that predicts cell response to a drug. This framework integrates information across multiple levels of cancer cell biology to …

NeST VNN 1. Park, S., Silva, E., Singhal, A. et al. A deep learning model of tumor cell architecture elucidates response and resistance to CDK4/6 inhibitors. Nat Cancer (2024). …

NeST-VNN is an interpretable neural network-based model that predicts cell response to a drug. The first explainable data-driven method for cancer therapeutic response prediction, in which …

为了更清晰的将机器学习模型的结构与细胞的功能联系起来，文章开发了DrugCell方法，基于可视神经网络（visible neural network，VNN）将神经网络里的神经元与细胞的基因组学数据相关 …

We constructed NeST-VNN drug response models for palbociclib and separately for each of the 50 benchmark drugs, using standard neural network learning procedures based on …

The Cell Maps VNN Tool enables the creation, training, and usage of an interpretable neural network-based models that predict cell response to a drug. A hierarchy in HCX format (for …

NeST-VNN repo. Contribute to idekerlab/nest_vnn development by creating an account on GitHub.

To elucidate the underlying mechanisms, we constructed an interpretable deep learning model of the response to palbociclib, a CDK4/6i, based on a reference map of multiprotein assemblies …