Suppr超能文献

靶点识别的系统观点:对瓦伯格效应进行建模

A Systemic View of Target Identification: Modeling the Warburg Effect.

作者信息

Trosset Jean-Yves, Bernot Gilles

机构信息

Sup'Biotech, BIRL, Villejuif, France.

Université Côte d'Azur, CNRS, I3S, Sophia Antipolis, France.

出版信息

Methods Mol Biol. 2025;2905:1-16. doi: 10.1007/978-1-0716-4418-8_1.

Abstract

The dynamics of the cell signaling network is highly regulated to adapt to temporal fluctuations and spatial heterogeneity of the microenvironment. Formal modeling of biological regulatory networks is an approach to identify which key components of this biological network, sometimes individual therapeutic targets, have a long-term influence on a disease-related phenotype of interest. We present an in silico formal screening strategy in the context of cancer metabolism to identify key hot spots in the metabolic network that could induce a systemic change of pathological cell phenotype such as the reversal of the Warburg effect.

摘要

细胞信号网络的动态变化受到高度调控,以适应微环境的时间波动和空间异质性。生物调控网络的形式化建模是一种确定该生物网络哪些关键成分(有时是个别治疗靶点)对感兴趣的疾病相关表型具有长期影响的方法。我们在癌症代谢背景下提出一种计算机形式化筛选策略,以识别代谢网络中可能诱导病理细胞表型系统性变化(如瓦伯格效应逆转)的关键热点。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验