来自杂志 Trends in cell biology 的文献。
当前共找到 1 篇文献分享。
1.
小W
(2023-12-31 18:12):
#paper doi：10.1016/j.tcb.2023.11.002 Mechanism-aware and multimodal AI: beyond model-agnostic interpretation 本文是一篇介绍通过多模态人工智能将多组学、临床数据和基因组规模代谢模型（GSMM 通量组学）结合起来，以生成更准确透明解释的生物标志物的综述文章。本文介绍了GSMM的构建方法、用于多模态数据集成的 AI 建模方法以及图神经网络方法。GSMM的构建来源于组学数据，其参考文章也验证使用转录组数据和GSMM的多模态模型对于酵母生长预测性能的提升，并揭示了仅从基因表达中无法直接推断的功能模式。
Abstract:
Artificial intelligence (AI) is widely used for exploiting multimodal biomedical data, with increasingly accurate predictions and model-agnostic interpretations, which are however also agnostic to biological mechanisms. Combining metabolic modelling, 'omics, …
>>>
Artificial intelligence (AI) is widely used for exploiting multimodal biomedical data, with increasingly accurate predictions and model-agnostic interpretations, which are however also agnostic to biological mechanisms. Combining metabolic modelling, 'omics, and imaging data via multimodal AI can generate predictions that can be interpreted mechanistically and transparently, therefore with significantly higher therapeutic potential.
<<<
翻译