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相关概念视频

Nucleic Acid Structure01:25

Nucleic Acid Structure

5.9K
The pentose sugar in DNA is deoxyribose, while in RNA the pentose sugar is ribose. The difference between the sugars is the presence of the hydroxyl group on the ribose's second carbon and a hydrogen on the deoxyribose's second carbon. The phosphate residue attaches to the hydroxyl group of the 5′ carbon of one sugar and the hydroxyl group of the 3′ carbon of the sugar of the next nucleotide, which forms  a 5′ to 3′ phosphodiester linkage.
DNA Structure
DNA...
5.9K
RNA Structure01:23

RNA Structure

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Overview
The basic structure of RNA consists of a five-carbon sugar and one of four nitrogenous bases. Although most RNA is single-stranded, it can form complex secondary and tertiary structures. Such structures play essential roles in the regulation of transcription and translation.
Different Types of RNA Have the Same Basic Structure
There are three main types of ribonucleic acid (RNA): messenger RNA (mRNA), transfer RNA (tRNA), and ribosomal RNA (rRNA). All three RNA types consist of a...
71.1K
Protein Organization01:13

Protein Organization

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Overview
136.6K
Molecular Models02:00

Molecular Models

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Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.
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相关实验视频

Updated: Jun 6, 2025

Analyzing and Building Nucleic Acid Structures with 3DNA
16:24

Analyzing and Building Nucleic Acid Structures with 3DNA

Published on: April 26, 2013

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准确的RNA3D结构预测使用基于语言模型的深度学习方法.

Tao Shen1,2,3, Zhihang Hu1, Siqi Sun4,5

  • 1Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China.

Nature methods
|November 21, 2024
PubMed
概括
此摘要是机器生成的。

使用深度学习方法,RhoFold+准确地预测RNA的3D结构. 计算生物学中的这一进步有助于RNA功能研究和药物开发.

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A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data
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A Protocol for Computer-Based Protein Structure and Function Prediction
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A Protocol for Computer-Based Protein Structure and Function Prediction

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相关实验视频

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科学领域:

  • 计算生物学 计算生物学
  • 结构生物学 结构生物学
  • 生物信息学是一种生物信息学.

背景情况:

  • 准确预测RNA三维 (3D) 结构是一个重大的挑战,因为RNA的固有灵活性和有限的实验数据.
  • 了解RNA3D结构对于阐明生物功能和推进RNA向治疗和合成生物学至关重要.

研究的目的:

  • 介绍RhoFold+,一种新的深度学习方法,用于从序列中准确,端到端地预测单链RNA3D结构.
  • 通过先进的计算技术来解决RNA结构预测数据稀缺的挑战.

主要方法:

  • 开发RhoFold+,一种基于RNA语言模型的深度学习方法.
  • 在大约2370万个RNA序列的大型数据集上预训练RNA语言模型.
  • 实施技术以减轻有限的实验数据的影响.

主要成果:

  • 与现有的方法相比,RhoFold+在预测RNA3D结构方面表现出卓越的性能,包括在RNA-Puzzles和CASP15数据集上验证的人类专家组.
  • 该方法在不同RNA家族和类型中显示出强大的通用性,通过跨家族,跨类型和时间审查的基准评估得到证实.
  • 此外,RhoFold+还可以准确地预测RNA的二次结构和螺旋间角,为RNA研究提供了有价值的功能.

结论:

  • RhoFold+代表了计算RNA结构预测的重大进步,提供了一个强大的和自动化的解决方案.
  • 该方法的准确性和通用性为RNA结构和功能研究,药物开发和合成生物学提供了强大的工具.
  • 二次结构和螺旋间角的预测增强了RhoFold+在经验验证和RNA生物学中的更广泛应用方面的实用性.