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

Conserved Binding Sites01:49

Conserved Binding Sites

4.2K
Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally...
4.2K
Leaky Scanning02:28

Leaky Scanning

5.1K
During most eukaryotic translation processes, the small 40S ribosome subunit scans an mRNA from its 5' end until it encounters the first start AUG codon. The large 60S ribosomal subunit then joins the smaller one to initiate protein synthesis. The location of the translation initiation is largely determined by the nucleotides near the start codon as there may be multiple translation initiation sites present on the mRNA.  Marilyn Kozak discovered that the sequence RCCAUGG (where R...
5.1K

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

HodgeRankWeight: An Integration Algorithm for Feature Ranking Based on Weight Quantization.

IEEE transactions on computational biology and bioinformatics·2025
Same author

Trans-MoRFs: A Disordered Protein Predictor Based on the Transformer Architecture.

IEEE journal of biomedical and health informatics·2025
Same author

Rore: robust and efficient antioxidant protein classification via a novel dimensionality reduction strategy based on learning of fewer features.

Genomics & informatics·2024
Same author

IIFS: An improved incremental feature selection method for protein sequence processing.

Computers in biology and medicine·2023
Same author

Machine learning-based antioxidant protein identification model: Progress and evaluation.

Journal of cellular biochemistry·2023
Same author

DP-AOP: A novel SVM-based antioxidant proteins identifier.

International journal of biological macromolecules·2023
Same journal

BindRNAgen: Protein-binding RNA sequence generation using latent diffusion models.

Journal of molecular biology·2026
Same journal

Structural basis of HSP90C, a highly active chloroplastic HSP90 chaperone from Arabidopsis thaliana.

Journal of molecular biology·2026
Same journal

Clinical inflammasome biomarkers: Progress and prospects.

Journal of molecular biology·2026
Same journal

Biologically Relevant, Cationic Residues in Human Rhinovirus Stabilize Capsid-Bound RNA Duplexes, and Restrict Capsid Flexibility.

Journal of molecular biology·2026
Same journal

Cryo-EM structures of phage T4 infection intermediate.

Journal of molecular biology·2026
Same journal

A classic fold with a twist: Structural architecture of Dhillonvirus phage Bas18.

Journal of molecular biology·2026
查看所有相关文章

相关实验视频

Updated: Jun 17, 2025

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

7.3K

IIFS2.0:基于缓存策略的蛋白质序列处理的改进增量特征选择方法.

Chaolu Meng1, Yue Pei2, Yongbo Bu1

  • 1College of Computer and Information Engineering, Inner Mongolia Agricultural University, Hohhot, China; Inner Mongolia Autonomous Region Key Laboratory of Big Data Research and Application of Agriculture and Animal Husbandry, China.

Journal of molecular biology
|August 9, 2024
PubMed
概括
此摘要是机器生成的。

这项研究介绍了IIFS2.0,这是一种用于蛋白序列识别的新算法,可以增强特征选择. IIFS2.0有效地减少了特征尺寸,并提高了分类器的性能,以识别关键蛋白质特征.

关键词:
功能选择 功能选择蛋白质识别 蛋白质识别蛋白质序列的蛋白质序列是什么排序功能 排序功能 排序功能

更多相关视频

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
06:50

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

Published on: January 26, 2024

1.8K
An Integrated Approach for Microprotein Identification and Sequence Analysis
09:37

An Integrated Approach for Microprotein Identification and Sequence Analysis

Published on: July 12, 2022

3.4K

相关实验视频

Last Updated: Jun 17, 2025

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

7.3K
Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
06:50

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

Published on: January 26, 2024

1.8K
An Integrated Approach for Microprotein Identification and Sequence Analysis
09:37

An Integrated Approach for Microprotein Identification and Sequence Analysis

Published on: July 12, 2022

3.4K

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
  • 机器学习在基因组学中的应用

背景情况:

  • 有效的特征选择对于蛋白质序列识别和确定关键蛋白质特征至关重要.
  • 传统方法往往依赖于人为因素或特征排序,导致不理想的结果.
  • 目标是实现更小的特征尺寸,具有更高的性能指标.

研究的目的:

  • 提出一种新的特征选择算法,IIFS2.0,用于蛋白序列识别.
  • 为了提高蛋白质分类的最佳特征集识别的效率和准确性.
  • 通过避免人类偏见和过度依赖特征排序来克服现有方法的局限性.

主要方法:

  • 开发使用缓存消除策略的IIFS2.0算法.
  • 利用缓存特征子集的本地最佳组合来进行特征选择.
  • 对蛋白质数据集的算法性能进行系统验证和分析.

主要成果:

  • IIFS2.0显著降低了蛋白质序列数据中特征组合的维度.
  • 该算法在各种绩效评估指标中显示出了显著的改进.
  • 缓存消除策略在发现新的功能组合方面被证明是有效的.

结论:

  • IIFS2.0提供了一种强大而有效的方法,用于蛋白序列识别中的特征选择.
  • 该方法提高了分类器的性能,并有助于发现关键序列特征.
  • IIFS2.0可供研究人员在蛋白质分析中使用.