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相关概念视频

Classification of Neurotransmitters01:30

Classification of Neurotransmitters

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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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Protein and Protein Structure02:15

Protein and Protein Structure

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Proteins are one of the most abundant organic molecules in living systems and have the most diverse range of functions of all macromolecules. Proteins may be structural, regulatory, contractile, or protective. They may serve in transport, storage, or membranes; or they may be toxins or enzymes. Their structures, like their functions, vary greatly. They are all, however, amino acid polymers arranged in a linear sequence.
A protein's shape is critical to its function. For example, an enzyme...
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Protein Networks02:26

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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.
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Tagging and Fusion Proteins01:24

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Proteins are involved in several cellular processes and biochemical reactions. Analyzing a specific protein of interest requires it to be isolated from the other proteins in the cell. This is achieved by overexpressing the specific gene in a suitable host to produce large quantities of the target protein. A tag or label is recombined with the gene to produce a fusion protein containing the target protein and the tag. The tags on these fusion proteins can then be used for easy detection and...
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Protein and Protein Structures

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Multi-pass Transmembrane Proteins and β-barrels01:09

Multi-pass Transmembrane Proteins and β-barrels

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In multi-pass transmembrane proteins, the polypeptide chain crosses the membrane more than once. The transmembrane polypeptide chain either forms an α-helix or β-strand structure. α-Helix containing multi-pass transmembrane proteins are ubiquitous, whereas β-strand containing ones are mainly found in gram-negative bacteria, mitochondria, and chloroplasts.
α-Helix containing multi-pass transmembrane proteins
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相关实验视频

Updated: Jun 6, 2025

A Protocol for Computer-Based Protein Structure and Function Prediction
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通过机器学习和蛋白质语言模型嵌入物进行离子通道分类.

Hamed Ghazikhani1, Gregory Butler1

  • 1Department of Computer Science and Software Engineering, Concordia University, Montreal, Canada.

Journal of integrative bioinformatics
|November 21, 2024
PubMed
概括
此摘要是机器生成的。

本研究介绍了TooT-BERT-CNN-C,这是一种使用蛋白质语言模型和深度学习识别离子通道的先进计算方法. 它显著提高了预测准确度,有助于离子通道生物学研究和药物发现.

关键词:
卷积神经网络是一个卷积神经网络.发现药物的发现.离子通道 离子通道膜蛋白质是一种膜蛋白质.蛋白质语言模型的模型跨膜蛋白质是一种跨膜蛋白质.

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相关实验视频

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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
  • 分子生物学分子生物学

背景情况:

  • 离子通道是重要的膜蛋白,调节离子运输和细胞功能.
  • 对于离子通道识别的传统实验方法是资源密集的.
  • 计算方法,特别是蛋白质语言模型,提供了高效的替代方案.

研究的目的:

  • 开发和评估用于准确的离子通道预测的先进计算方法.
  • 改进现有的基于蛋白质语言模型的离子通道分类技术.
  • 评估与蛋白质嵌入集成的新型深度学习架构的性能.

主要方法:

  • 使用了来自ProtBERT,ProtBERT-BFD和MembraneBERT的微调嵌入式.
  • 采用机器学习算法:k-最近邻居,随机森林,支持矢量机器,前神经网络.
  • 开发并测试了一种新的卷积神经网络 (CNN) 方法,TooT-BERT-CNN-C,集成ProtBERT-BFD功能.

主要成果:

  • 在离子通道预测方面,TooT-BERT-CNN-C显著超过了现有的基准标准.
  • 在原始数据集上实现了高精度 (98.35%) 和0.8584的马修斯相关系数 (MCC).
  • 在较大的数据集 (DS-Cv2) 上表现出卓越的性能,在独立测试集上MCC为0.9492和ROC AUC为0.9968.

结论:

  • 将蛋白质语言模型与深度学习,特别是CNN集成,提高了离子通道分类的准确性.
  • 这项研究强调了在生物信息学中使用全面和最新数据集的关键重要性.
  • 开发的TooT-BERT-CNN-C方法代表了计算离子通道识别的重大进步,对药物发现有影响.