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

Nuclear Localization Signals and Import01:46

Nuclear Localization Signals and Import

5.5K
Proteins targeted to the nucleus carry short stretches of amino acid sequences called the nuclear localization signal or NLS. Classical nuclear localization signals are of two types: monopartite and bipartite NLS. Monopartite classical NLS (cNLS) consists of a single cluster of 4-8 amino acids. Bipartite cNLS consists of two clusters of  2-3 amino acids and a 9-12 residue long proline-rich linker bridging the two clusters. Signal clusters are rich in positively charged amino acids such as...
5.5K

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

Important progress in antimicrobial peptide prediction research in the past five years.

Analytical biochemistry·2026
Same author

EnsemGlyPred: Intelligent prediction system for lysine glycation sites integrating deep semantic features and sequence information.

Analytical biochemistry·2026
Same author

HyperACP: A cutting-edge hybrid framework for anticancer peptide classification via scalable feature extraction and adaptive neighbor-based synthesis.

PLoS computational biology·2025
Same author

MSlocPRED: deep transfer learning-based identification of multi-label mRNA subcellular localization.

Briefings in bioinformatics·2024
Same author

Glypred: Lysine Glycation Site Prediction via CCU-LightGBM-BiLSTM Framework with Multi-Head Attention Mechanism.

Journal of chemical information and modeling·2024
Same author

The Rejuvenation Effect of Bio-Oils on Long-Term Aged Asphalt.

Materials (Basel, Switzerland)·2024

相关实验视频

Updated: May 24, 2025

Multi-color Localization Microscopy of Single Membrane Proteins in Organelles of Live Mammalian Cells
11:06

Multi-color Localization Microscopy of Single Membrane Proteins in Organelles of Live Mammalian Cells

Published on: June 30, 2018

8.4K

MBSCLoc:基于集群平衡子空间分区方法和多类对比表示学习的多标签亚细胞定位预测.

Bangyi Zhang, Yun Zuo, Zhiqiang Dai

    IEEE journal of biomedical and health informatics
    |March 3, 2025
    PubMed
    概括

    这项研究介绍了MBSCLoc,这是一种用于多标签信使RNA (mRNA) 亚细胞定位的新型预测器. MBSCLoc准确地识别了mRNA的多个细胞区,克服了数据不平衡,提高了预测准确度.

    科学领域:

    • 分子生物学分子生物学
    • 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:

    • mRNA亚细胞局部化对于调节蛋白质翻译和细胞功能至关重要.
    • 现有的预测方法在不平衡的数据,不良性能和有限的概括性方面扎,特别是在多标签场景中.

    研究的目的:

    • 开发MBSCLoc,一个多标签mRNA亚细胞局部化的预测器.
    • 克服现有方法的局限性,包括单个位置预测和数据不平衡.

    主要方法:

    • 使用UTR-LM模型进行特征提取.
    • 多类对比表示学习和集群平衡子空间分区平衡子空间的分区.
    • 优化样本分布和XGBoost分类器组合,以提高准确性和概括性.

    主要成果:

    • 在五倍交叉验证和独立测试方面,MBSCLoc显著优于现有方法.
    • 展示了卓越的像素级解读能力,支持多标签mRNA本地化研究.
    • 证实了5' UTR和3' UTR区域的重要性,其中3' UTR在80%的地点显示出高峰意义.

    结论:

    • MBSCLoc有效地解决了多标签mRNA亚细胞局部化的挑战.

    更多相关视频

    Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
    07:35

    Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

    Published on: October 11, 2018

    7.4K
    Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
    03:31

    Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

    Published on: December 15, 2023

    451

    相关实验视频

    Last Updated: May 24, 2025

    Multi-color Localization Microscopy of Single Membrane Proteins in Organelles of Live Mammalian Cells
    11:06

    Multi-color Localization Microscopy of Single Membrane Proteins in Organelles of Live Mammalian Cells

    Published on: June 30, 2018

    8.4K
    Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
    07:35

    Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

    Published on: October 11, 2018

    7.4K
    Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
    03:31

    Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

    Published on: December 15, 2023

    451

  • 该工具为研究人员提供了有价值的资源,提供了一个公开可访问的Web服务器.
  • 突出了UTR区域在确定mRNA亚细胞局部化中的关键作用.