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

Depth Perception and Spatial Vision01:15

Depth Perception and Spatial Vision

653
Depth perception is the ability to perceive objects three-dimensionally. It relies on two types of cues: binocular and monocular. Binocular cues depend on the combination of images from both eyes and how the eyes work together. Since the eyes are in slightly different positions, each eye captures a slightly different image. This disparity between images, known as binocular disparity, helps the brain interpret depth. When the brain compares these images, it determines the distance to an object.
653
Vision01:24

Vision

53.4K
Vision is the result of light being detected and transduced into neural signals by the retina of the eye. This information is then further analyzed and interpreted by the brain. First, light enters the front of the eye and is focused by the cornea and lens onto the retina—a thin sheet of neural tissue lining the back of the eye. Because of refraction through the convex lens of the eye, images are projected onto the retina upside-down and reversed.
53.4K

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

Grand Challenges in Bioinformatics Data Visualization.

Frontiers in bioinformatics·2022
Same author

Increased core body temperature exacerbates defective protein prenylation in mouse models of mevalonate kinase deficiency.

The Journal of clinical investigation·2022
Same author

SARS-CoV-2 structural coverage map reveals viral protein assembly, mimicry, and hijacking mechanisms.

Molecular systems biology·2021
Same author

Author Correction: Human origins in a southern African palaeo-wetland and first migrations.

Nature·2021
Same author

Temporal ordering of omics and multiomic events inferred from time-series data.

NPJ systems biology and applications·2020
Same author

Human origins in a southern African palaeo-wetland and first migrations.

Nature·2019
Same journal

RNApedia: a database of structural protein-RNA interactions.

Frontiers in bioinformatics·2026
Same journal

Hydrogen sulfide modulates gene networks in hypoxia/reoxygenation-stressed trophoblasts: insights from transcriptome profiling.

Frontiers in bioinformatics·2026
Same journal

Molecular Dynamics-Based validation of a quinazoline-based KRAS inhibitor (C9) identified through QSAR-guided discovery.

Frontiers in bioinformatics·2026
Same journal

Real-world chronic recordings from implantable adaptive deep brain stimulation systems for Parkinson's disease motor state classification.

Frontiers in bioinformatics·2026
Same journal

A foundational quantum framework for multi-pattern string matching in k-mer detection.

Frontiers in bioinformatics·2026
Same journal

Explainable machine learning-based identification of transcriptomic biomarkers in CD1c+ dendritic cells for non-infectious uveitis: an integrative analysis of bulk RNA-seq data.

Frontiers in bioinformatics·2026
查看所有相关文章

相关实验视频

Updated: Jul 4, 2025

3D Scanning Technology Bridging Microcircuits and Macroscale Brain Images in 3D Novel Embedding Overlapping Protocol
10:14

3D Scanning Technology Bridging Microcircuits and Macroscale Brain Images in 3D Novel Embedding Overlapping Protocol

Published on: May 12, 2019

7.3K

评估3D空间连接的2D视觉编码的3D空间连接.

Benedetta F Baldi1, Jenny Vuong1,2, Seán I O'Donoghue1,2,3

  • 1The Garvan Institute of Medical Research, Darlinghurst, NSW, Australia.

Frontiers in bioinformatics
|February 7, 2024
PubMed
概括
此摘要是机器生成的。

对于可视化空间连接数据,循环布局对于较小的数据集是最准确的,而半矩阵布局对较大的数据集表现更好. 众包可以有效地评估生物信息学可视化方法.

关键词:
邻矩阵是一个邻矩阵.染色体组织组织 染色体组织圆形布局的布局是循环的这是一个半矩阵布局.空间连接性 空间连接性用户研究用户研究视觉分析 视觉分析视觉编码是指视觉编码.

更多相关视频

Measuring Connectivity in the Primary Visual Pathway in Human Albinism Using Diffusion Tensor Imaging and Tractography
13:26

Measuring Connectivity in the Primary Visual Pathway in Human Albinism Using Diffusion Tensor Imaging and Tractography

Published on: August 11, 2016

12.3K
A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells
12:49

A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells

Published on: September 28, 2019

12.8K

相关实验视频

Last Updated: Jul 4, 2025

3D Scanning Technology Bridging Microcircuits and Macroscale Brain Images in 3D Novel Embedding Overlapping Protocol
10:14

3D Scanning Technology Bridging Microcircuits and Macroscale Brain Images in 3D Novel Embedding Overlapping Protocol

Published on: May 12, 2019

7.3K
Measuring Connectivity in the Primary Visual Pathway in Human Albinism Using Diffusion Tensor Imaging and Tractography
13:26

Measuring Connectivity in the Primary Visual Pathway in Human Albinism Using Diffusion Tensor Imaging and Tractography

Published on: August 11, 2016

12.3K
A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells
12:49

A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells

Published on: September 28, 2019

12.8K

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
  • 数据可视化 数据可视化

背景情况:

  • 复杂的生物数据的有效可视化对于识别模式和传达发现至关重要.
  • 空间连接数据,例如来自染色体构造捕获 (3C) 实验的空间连接数据,提出了独特的可视化挑战.
  • 视觉布局的选择显著影响数据的解释和分析.

研究的目的:

  • 为了比较三个不同的视觉布局对空间连接数据的有效性.
  • 评估邻近矩阵,半矩阵和圆形布局的准确性和直观性.
  • 评估众包对确定最佳生物信息学可视化技术的有用性.

主要方法:

  • 通过使用三个视觉布局进行了比较研究:邻近矩阵,半矩阵和圆形矩阵.
  • 两组参与者参与其中:来自亚马逊机械土耳其人的150名个人和30名生物医学研究科学家.
  • 通过准确性和在解释空间连接数据时感知到的直观性来评估有效性.

主要成果:

  • 循环布局被确定为最准确和直观的一般机械土耳其参与者群体.
  • 生物医学研究科学家发现,圆形和半矩阵布局都比传统的矩阵布局更准确.
  • 众包被证明是评估生物信息学数据可视化工具的可行方法.

结论:

  • 对于较小的空间连接数据集,建议以循环布局为默认设置.
  • 半矩阵布局被认为是更适合更大,更复杂的数据集的选择.
  • 这项研究强调了众包评估的潜力,以指导开发有效的生物信息学数据可视化策略.