相关实验视频

Updated: Jun 7, 2025

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

Published on: October 13, 2023

SGTCDA:用可解释的图形转换器预测circRNA药物敏感性关联和有效评估

Hongwei Xia^1,2,3, Caiyue Dong^1,2,3, Xinxing Chen⁴

¹School of Information and Artificial Intelligence, Anhui Agricultural University, Hefei, Anhui, 230036, China.

|November 20, 2024

概括

这项研究介绍了SGTCDA,这是一种用于预测circRNA与药物敏感性关联的新型计算模型. SGTCDA使用先进的深度学习技术和独立验证,以提高识别潜在药物反应的准确性.

科学领域:

生物信息学是一种生物信息学.
计算生物学计算生物学
基因组学就是基因组学.

背景情况:

循环RNA (circRNAs) 与药物敏感性有关,但实验验证是昂贵的.
现有的circRNA药物敏感性预测计算方法经常使用过度乐观的交叉验证,并存在模型问题.
在这个领域需要强大的评估策略和准确的预测模型.

研究的目的:

提出一种可靠的评估策略,使用独立的测试集来预测circRNA-药物敏感性关联.
开发一个准确的计算模型,SGTCDA,用于预测circRNA-药物敏感性关联.
解释SGTCDA模型的预测,并确定关键的预测特征.

主要方法:

通过整合结构深度网络嵌入 (SDNE) 和图形变压器,开发了SGTCDA.
采用独立测试集评估策略来克服交叉验证的局限性.
使用EdgeSHAPer进行模型解释,以了解特征的重要性.

主要成果:

与最先进的模型相比,SGTCDA在培训和独立测试集上都表现出优越的性能.
该模型有效地捕获circRNA药物网络中的远程依赖和局部结构信息.
边缘SHAPer分析显示,药物边缘对SGTCDA的预测性能至关重要.

结论:

SGTCDA提供了一个准确可靠的方法来预测circRNA-药物敏感性关联.
拟议的独立测试集评估策略提高了预测模型的可靠性.
这些发现通过circRNA分析为药物开发和个性化医疗提供了宝贵的见解.

关键词:

循环RNA与药物敏感性相关联.在EdgeSHAPer上使用.图形变压器图形变压器独立的测试集独立的测试集 SDNE SDNE SDNE SDNE SDNE SDNE SDNE SDNE SDNE SDNE SDNE SDNE SDNE SDNE SDNE SDNE SDNE SDNE SDNE

更多相关视频

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

Published on: March 1, 2024

相关概念视频

Agonism and Antagonism: Quantification

Agonism and Antagonism: Quantification

When drugs are administered, they can elicit either an agonist or antagonist effect on the body. Agonism occurs when a drug activates a specific receptor, triggering a biological response. On the other hand, antagonism happens when a drug binds to the same receptors but blocks their activation, thereby preventing a biological response.
To quantify these effects, researchers use a dose-response curve, which provides valuable information about the potency and efficacy of a drug. Potency refers to...

Receiver Operating Characteristic Plot

Receiver Operating Characteristic Plot

A ROC (Receiver Operating Characteristic) plot is a graphical tool used to assess the performance of a binary classification model by illustrating the trade-off between sensitivity (true positive rate) and specificity (false positive rate). By plotting sensitivity against 1 - specificity across various threshold settings, the ROC curve shows how well the model distinguishes between classes, with a curve closer to the top-left corner indicating a more accurate model. The area under the ROC curve...