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相关概念视频

Aggregates Classification01:29

Aggregates Classification

387
Aggregate classification is generally based on its size, petrographic characteristics, weight, and source. Size classification ranges from coarse to fine aggregates, defined by the size of the particles. Coarse aggregates are particles that do not pass through ASTM sieve No. 4, and aggregates that pass through the sieve are fine aggregates.
Petrographic classification groups aggregates based on common mineralogical characteristics. Some of the common mineral groups found in aggregates are...
387
Classification of Neurotransmitters01:30

Classification of Neurotransmitters

3.6K
Neurotransmitters play a crucial role in the communication between neurons in the autonomic nervous system. Neurons in the autonomic nervous system can be cholinergic or adrenergic depending on the neurotransmitters synthesized. Cholinergic neurons use acetylcholine as their primary neurotransmitter. This includes all the preganglionic fibers of the sympathetic and pre- and postganglionic fibers of the parasympathetic nervous systems. In addition, neurons of the somatic nervous system also use...
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Drug Classes and Categories01:25

Drug Classes and Categories

2.2K
Drugs can be classified according to their chemical composition or their intended therapeutic application. For instance, anti-infective agents that possess the ability to eliminate pathogens or suppress their growth and reproduction can be grouped based on the organisms they target or their chemical structure. Furthermore, drugs can be divided into prescription, nonprescription, or controlled substances. Prescription medications, such as antibiotics, require oversight from a licensed healthcare...
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Cardiovascular Drugs: Classification based on Therapeutic Indications01:18

Cardiovascular Drugs: Classification based on Therapeutic Indications

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Cardiovascular diseases, encompassing a range of conditions, can significantly affect the heart's operations and the overall circulatory system. These conditions impair the heart's ability to pump blood, leading to a deficit in oxygen supply to crucial organs. Anomalies in the heart's electrical system, known as arrhythmias, can cause heartbeats to accelerate or slow down. Usually, heart rates increase during physical activity and decrease while resting or sleeping. However,...
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Drug Biotransformation: Overview01:16

Drug Biotransformation: Overview

2.9K
Pharmaceutical substances known as xenobiotics are predominantly lipophilic and nonionized. This enables them to permeate lipid bilayers, such as cell membranes, and interact with intracellular target receptors. Lipophilic drugs have an advantage in crossing biological barriers and reaching their intended sites of action. However, lipophilic drugs often have a restricted capacity for renal expulsion or elimination from the body. When these drugs enter the kidneys and undergo glomerular...
2.9K
Drug Discovery: Overview01:26

Drug Discovery: Overview

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Drug discovery is a multifaceted process involving extensive screening, testing, and optimization of lead compounds to identify potential new drugs for therapeutic use. It combines several approaches, including screening large numbers of natural products, chemical modification of known active molecules, identification of new drug targets, and rational design based on biological mechanisms and drug-receptor structure. These approaches are carried out in both academic research laboratories and...
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相关实验视频

Updated: Sep 15, 2025

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
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Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

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事实:特征聚合和卷积与变压器用于预测药物分类代码.

Gwang-Hyeon Yun1, Jong-Hoon Park1, Young-Rae Cho1,2

  • 1Division of Software, Yonsei University - Mirae Campus, Wonju-si, Gangwon-do 26493, Republic of Korea.

Bioinformatics (Oxford, England)
|July 15, 2025
PubMed
概括
此摘要是机器生成的。

我们开发了一种新的方法,FACT,用于预测用于药物重新定位的解剖治疗化学 (ATC) 代码. FACT显著提高了预测准确度,超过了以前的方法,加速了药物发现.

相关实验视频

Last Updated: Sep 15, 2025

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
04:09

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

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科学领域:

  • 药理学 药理学是指药理学的学科.
  • 计算化学计算化学
  • 生物信息学是一种生物信息学.

背景情况:

  • 药物重新定位通过为现有药物找到新的用途来加速药物开发.
  • 解剖治疗化学 (ATC) 代码为药物分类和预测提供了一个系统的框架.
  • 由于复杂的ATC层次结构和可扩展性问题,现有的ATC预测方法面临挑战.

研究的目的:

  • 开发一种新且准确的方法来预测用于药物重新定位的解剖治疗化学 (ATC) 代码.
  • 解决现有的ATC预测方法的局限性,特别是在更高层次的层次上.

主要方法:

  • 提出了一种名为特征聚合和卷积与变压器模型 (FACT) 的新方法.
  • 计算了三种类型的药物相似性,包括ATC代码相似性与等级权重和掩盖的药物-ATC代码关联.
  • 使用卷积变压器编码器生成嵌入式,用于预测药物-ATC代码关联.

主要成果:

  • 在ATC 4.级实现了0.9805的接收器操作特征曲线 (AUROC) 下的面积和0.9770的精度回调曲线 (AUPRC) 下的面积.
  • 在AUROC中表现比以前的方法高15.05%,在AUPRC中表现比以前的方法高18.42%.
  • 证明了整合各种药物特征和变压器模型用于ATC代码预测的有效性.

结论:

  • 该FACT模型显著提高了ATC代码预测的准确性.
  • 该研究强调了基于变压器的模型在药物重新定位和制药研究中的潜力.
  • 开发的方法为导航ATC分类系统的复杂性提供了一个可扩展和有效的解决方案.