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Titlebook: Network Pharmacology; Shao Li Book 2021 Tsinghua University Press 2021 Network Pharmacology.artificial intelligence.modernization of Tradi

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樓主: 美麗動人
21#
發(fā)表于 2025-3-25 05:08:53 | 只看該作者
22#
發(fā)表于 2025-3-25 08:38:35 | 只看該作者
23#
發(fā)表于 2025-3-25 12:56:46 | 只看該作者
Shibing Su,Yuanjia Hu,Huali Zuo-norm of the unit normal to the surface; hence, the flatter said surface, the smaller the norm of the singular integral operators. Here we proceed in the opposite direction, and control geometry through analysis. We quantify flatness of a given “surface” by estimating the BMO semi-norm of its unit n
24#
發(fā)表于 2025-3-25 19:00:10 | 只看該作者
Weidong Zhang,Jing Zhao-norm of the unit normal to the surface; hence, the flatter said surface, the smaller the norm of the singular integral operators. Here we proceed in the opposite direction, and control geometry through analysis. We quantify flatness of a given “surface” by estimating the BMO semi-norm of its unit n
25#
發(fā)表于 2025-3-25 23:40:46 | 只看該作者
26#
發(fā)表于 2025-3-26 04:00:04 | 只看該作者
27#
發(fā)表于 2025-3-26 08:15:02 | 只看該作者
Application of Network Pharmacology Based on Artificial Intelligence Algorithms in Drug Developmentifficult to fully utilize large-scale data with simple statistical analysis methods. In order to improve data utilization, pharmaceutical research must be promoted using advanced information analysis. Artificial intelligence has experienced half a century of development since its inception and has b
28#
發(fā)表于 2025-3-26 11:41:13 | 只看該作者
Common Network Pharmacology Databases,M) involves ancient manuscripts, documents, and innumerable prescriptions belonging to various dynasties. Modern research implements many prescriptions or Chinese medicinal resources for ingredient separation method and analysis, especially in contemporary molecular pharmacological research. This im
29#
發(fā)表于 2025-3-26 14:33:53 | 只看該作者
30#
發(fā)表于 2025-3-26 19:05:11 | 只看該作者
Network Pharmacology and Modern Drug R&D Cases, entities that can specifically bind to one key target related to a specific disease [1]. Collateral pharmacology aims to develop drugs that earmark multiple proteins or networks connected to diseases. It also demonstrates the possibility of finding multi-target and multi-component drugs that earmar
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