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

Genetics of Speciation02:16

Genetics of Speciation

19.0K
Speciation is the evolutionary process resulting in the formation of new, distinct species—groups of reproductively isolated populations.
19.0K
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

5.7K
Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
5.7K
Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

7.0K
The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
In contrast, regions which code...
7.0K
Hybrid Zones02:29

Hybrid Zones

16.8K
Hybrid zones are narrow regions where two closely related species interact, mate, and produce hybrids. Relative to either parent species, hybrids may possess distinct phenotypic or genetic differences that impact their survival and reproductive success. The genetic variances introduced by hybridization influence species diversity and speciation processes within the hybrid zone.
16.8K
DNA Microarrays02:34

DNA Microarrays

17.2K
Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...
17.2K

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

Cross-Center Vision-Language Transformer for Robust Mammography-Based Breast Cancer Diagnosis.

Bioengineering (Basel, Switzerland)·2026
Same author

Foundation-Model-Driven Skin Lesion Segmentation and Classification Using SAM-Adapters and Vision Transformers.

Diagnostics (Basel, Switzerland)·2026
Same author

AI-Enabled Crop Management Framework for Pest Detection Using Visual Sensor Data.

Plants (Basel, Switzerland)·2024
Same author

Machine Learning-Based Anomaly Detection in NFV: A Comprehensive Survey.

Sensors (Basel, Switzerland)·2023
Same author

An Effective Multifactor Authentication Mechanism Based on Combiners of Hash Function over Internet of Things.

Sensors (Basel, Switzerland)·2019
Same journal

RETRACTED: Sabir et al. DNA Based and Stimuli-Responsive Smart Nanocarrier for Diagnosis and Treatment of Cancer: Applications and Challenges. <i>Cancers</i> 2021, <i>13</i>, 3396.

Cancers·2026
Same journal

Correction: Adeluola et al. Chemoprevention of 4-NQO-Induced Oral Cancer by the Combination of Resveratrol and EGCG: In Vivo, In Silico and In Vitro Studies. <i>Cancers</i> 2026, <i>18</i>, 1098.

Cancers·2026
Same journal

Correction: Peñalver et al. Guidelines for Diagnosis, Treatment, and Follow-Up of Patients with Follicular Lymphoma-Spanish Lymphoma Group (GELTAMO) 2026. <i>Cancers</i> 2026, <i>18</i>, 395.

Cancers·2026
Same journal

Correction: Accorsi Buttini et al. Development of a Simplified Geriatric Score-4 (SGS-4) to Predict Outcomes After Allogeneic Hematopoietic Stem Cell Transplantation in Patients Aged over 50. <i>Cancers</i> 2025, <i>17</i>, 3278.

Cancers·2026
Same journal

Age-Stratified Long-Term Outcomes of Immune Checkpoint Inhibitors for Stage IV Melanoma and NSCLC in The Netherlands: A Population-Based Study.

Cancers·2026
Same journal

Targeting Ferroptosis in Glioblastoma: Molecular Mechanisms, Tumor Microenvironment, and Therapeutic Opportunities.

Cancers·2026
查看所有相关文章

相关实验视频

Updated: Jun 5, 2025

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

增强癌症基因选择和分类用于高维微阵列数据,使用新的混合过器和差异进化特征选择.

Arshad Hashmi1, Waleed Ali2, Anas Abulfaraj1

  • 1Department of Information Systems, Faculty of Computing and Information Technology, King Abdulaziz University, P.O. Box 344, Rabigh 21911, Saudi Arabia.

Cancers
|December 17, 2024
PubMed
概括
此摘要是机器生成的。

这项研究引入了使用差异进化 (DE) 的混合特征选择方法,以从高维微阵列数据中改进癌症诊断. 该方法通过识别最有影响力的基因,显著提高了分类准确性.

关键词:
大脑癌症 脑癌 脑癌乳腺癌 乳腺癌 乳腺癌癌症分类 癌症分类 癌症分类中枢神经系统的癌症 中枢神经系统的癌症不同进化算法差异进化算法过器的功能选择的选择.基因选择 基因选择高维微阵列数据集肺癌是一种肺癌.

更多相关视频

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers
03:37

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

Published on: March 1, 2024

637
Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

6.7K

相关实验视频

Last Updated: Jun 5, 2025

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: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers
03:37

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

Published on: March 1, 2024

637
Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

6.7K

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
  • 基因组学就是基因组学.

背景情况:

  • 微阵列数据集对于早期癌症诊断至关重要,但往往含有杂和无关的基因.
  • 微阵列数据的高维度给机器学习算法带来了挑战.
  • 有效的特征选择对于准确的癌症分类至关重要.

研究的目的:

  • 为高维微阵列数据集开发混合特征选择方法.
  • 为了提高癌症诊断和分类准确度.
  • 为了确定对癌症预测最有影响力的基因.

主要方法:

  • 一个双相混合特征选择模型,结合了过方法和差异演变 (DE) 优化.
  • 使用流行的过方法选择排名最高的功能.
  • 通过使用DE算法进一步优化功能选择.
  • 训练机器学习模型对癌症分类所选的最佳特征进行训练.

主要成果:

  • 实现了100% (大脑,中枢神经系统),93% (乳房) 和98% (肺部) 的分类准确度.
  • 基于DE的特征选择与单独的过方法相比,减少了约50%的特征.
  • 与之前的工作相比,显示了显著的平均精度改进,高达57.45%.

结论:

  • 拟议的混合过-DE方法在提高癌症分类准确度方面表现出卓越的性能.
  • 该方法有效地减少了特征维度,同时保留了关键信息.
  • 这种方法提供了一个有前途的策略,用于利用基因组数据加强癌症诊断.