Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Combined Effects of Drugs: Synergism01:27

Combined Effects of Drugs: Synergism

6.7K
Synergism is a useful mechanism where combining two or more drugs is more effective than each constituent used alone. Such combinations are also called supra-additive interactions. The drugs collectively enhance the final therapeutic effect by acting on different targets. Another advantage is that the low dose of each constituent drug is sufficient to achieve the desired effect. This helps reduce the duration of therapy and lower the adverse effects of these drugs.
Such synergistic combinations...
6.7K
MicroRNAs01:22

MicroRNAs

3.8K
MicroRNA (miRNA) are short, regulatory RNA transcribed from introns (non-coding regions of a gene) or intergenic regions (stretches of DNA present between genes). Several processing steps are required to form biologically active, mature miRNA. The initial transcript, called primary miRNA (pri-mRNA), base-pairs with itself, forming a stem-loop structure. Within the nucleus, an endonuclease enzyme, called Drosha, shortens the stem-loop structure into hairpin-shaped pre-miRNA. After the pre-miRNA...
3.8K
Drug-Receptor Interactions01:29

Drug-Receptor Interactions

7.3K
Drug-receptor interaction describes the binding of receptors by drugs, but not all drug-receptor interactions result in activation and tissue response. For instance, the binding of agonists activates the receptor to generate a cellular reaction, while antagonists bind to receptors without causing their activation.
Several parameters, such as the drug's affinity for its receptor and its efficacy, which is its ability to activate the receptor, determine the drug's effect on the tissue....
7.3K
Protein Networks02:26

Protein Networks

4.5K
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
4.5K
Combined Effects of Drugs: Antagonism01:30

Combined Effects of Drugs: Antagonism

11.5K
The combined effects of drugs can result in various interactions, of which an important type is antagonism. Antagonism is a mechanism where one drug inhibits or counteracts the effects of another drug. Antagonism can occur through various means, including receptor binding, allosteric modulation, functional interaction, chemical reactions, and pharmacokinetic processes.
The most common type is receptor antagonism, where one drug acts as an antagonist to block the effects of another drug by...
11.5K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Roles of NRXN1 in neuropsychiatric disorders: from genetic lesion to molecular mechanism.

Frontiers in neuroscience·2026
Same author

From Cell-Free Transcriptomes to Single-Cell Landscapes: Biomarker Discovery and Originating Cell Alteration Analysis via Graph Matrix Factorization.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026
Same author

Knowledge graph-based cognitive learning with multi-fact reasoning.

Neural networks : the official journal of the International Neural Network Society·2026
Same author

IIC-DTI: A Contrastive Learning Enhanced Inter-Intra Molecular Fusing Framework for Drug-Target Interaction Prediction.

Interdisciplinary sciences, computational life sciences·2026
Same author

RCVQA: Visual question answering model based on reading comprehension.

Neural networks : the official journal of the International Neural Network Society·2025
Same author

Graph convolution network based on meta-paths and mutual information for drug-target interaction prediction.

BMC bioinformatics·2025

相关实验视频

Updated: Jan 15, 2026

mirMachine: A One-Stop Shop for Plant miRNA Annotation
06:16

mirMachine: A One-Stop Shop for Plant miRNA Annotation

Published on: May 1, 2021

2.9K

基于异质网络的多源特征融合预测miRNA与药物相互作用

Chenyue Lei1, Xiujuan Lei2, Lian Liu1

  • 1School of Computer Science, Shaanxi Normal University, Xi'an, 710119, China.

Interdisciplinary sciences, computational life sciences
|October 14, 2025
PubMed
概括

预测miRNA与药物相互作用 (MDIs) 对癌症治疗至关重要. 我们的新型MSFFMDI方法使用双通道网络准确识别潜在的MDIs,有助于了解耐药性.

关键词:
卷积神经网络是一种卷积神经网络.图表注意力网络 图表注意力网络异质网络是异质的网络.多源功能融合功能是多源的miRNA与药物的相互作用

更多相关视频

Diagonal Method to Measure Synergy Among Any Number of Drugs
12:08

Diagonal Method to Measure Synergy Among Any Number of Drugs

Published on: June 21, 2018

19.5K
Biotin-based Pulldown Assay to Validate mRNA Targets of Cellular miRNAs
11:00

Biotin-based Pulldown Assay to Validate mRNA Targets of Cellular miRNAs

Published on: June 12, 2018

14.5K

相关实验视频

Last Updated: Jan 15, 2026

mirMachine: A One-Stop Shop for Plant miRNA Annotation
06:16

mirMachine: A One-Stop Shop for Plant miRNA Annotation

Published on: May 1, 2021

2.9K
Diagonal Method to Measure Synergy Among Any Number of Drugs
12:08

Diagonal Method to Measure Synergy Among Any Number of Drugs

Published on: June 21, 2018

19.5K
Biotin-based Pulldown Assay to Validate mRNA Targets of Cellular miRNAs
11:00

Biotin-based Pulldown Assay to Validate mRNA Targets of Cellular miRNAs

Published on: June 12, 2018

14.5K

科学领域:

  • 生物化学 生化学
  • 生物信息学是一种生物信息学.
  • 计算生物学 计算生物学

背景情况:

  • 抗癌治疗阻力是一个主要的治疗障碍.
  • 微RNA (miRNA) 表达显著影响药物敏感性和耐药性.
  • 准确预测miRNA与药物相互作用 (MDIs) 对理解药物耐药机制至关重要.

研究的目的:

  • 开发一种用于预测miRNA与药物相互作用 (MDIs) 的创新计算框架.
  • 提高对癌症治疗中药物耐药性机制的理解.

主要方法:

  • 拟议的MSFFMDI是一个双通道的多源功能融合框架,利用异质网络.
  • 道1:使用miRNAs的k-mer/word2vec和药物的图形同态网络/mol2vec提取属性特征.
  • 道2:通过异质网络,图表注意网络和多尺度卷积神经网络进行拓特征提取.

主要成果:

  • 在两个独立的数据集上,MSFFMDI表现出色的预测性能.
  • 实验结果证实了拟议方法的稳定性和有效性.
  • 案例研究进一步证实了该框架的实际适用性.

结论:

  • MSFFMDI为预测潜在的miRNA药物相互作用提供了一种强大且可解释的方法.
  • 该框架为癌症耐药性背后的复杂机制提供了宝贵的见解.
  • 这种方法可以帮助开发更有效的癌症治疗方法.