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

Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

5.8K
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...
5.8K
Phylogenetic Trees03:21

Phylogenetic Trees

45.4K
Phylogenetic trees come in many forms. It matters in which sequence the organisms are arranged from the bottom to the top of the tree, but the branches can rotate at their nodes without altering the information. The lines connecting individual nodes can be straight, angled, or even curved.
45.4K
Phylogeny01:23

Phylogeny

44.3K
Phylogeny is concerned with the evolutionary diversification of organisms or groups of organisms. A group of organisms with a name is called a taxon (singular). Taxa (plural) can span different levels of the evolutionary hierarchy. For instance, the group containing all birds is a taxon (comprising the class Aves), and the group of all species of daisies (the genus Bellis) is a taxon. Phylogenies can likewise include just one genus (i.e., depict species relationships) or span an entire kingdom.
44.3K
Sequence Networks of Rotating Machines01:24

Sequence Networks of Rotating Machines

123
A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
Zero-sequence current induces a voltage drop across the generator's neutral impedance and other...
123
Survival Tree01:19

Survival Tree

105
Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a...
105
Applications of Molecular Taxonomy01:20

Applications of Molecular Taxonomy

41
Molecular taxonomy has revolutionized the understanding and classification of bacteria, providing precise insights into their diversity, evolutionary relationships, and ecological roles. By utilizing molecular techniques such as DNA sequencing and fingerprinting, researchers have made significant strides in various fields related to bacterial studies.Resolving Taxonomic AmbiguitiesMolecular taxonomy has been instrumental in distinguishing closely related bacterial species initially thought to...
41

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

Pattern matching with Elastic-Degenerate strings and Elastic-Founder graphs.

Algorithms for molecular biology : AMB·2026
Same author

Correction: "Distinguishing Phylogenetic Level-2 Networks with Quartets and Inter-Taxon Quartet Distances".

Bulletin of mathematical biology·2026
Same author

Uncovering Proteomic and Biochemical Alterations in Plasma from Lesch-Nyhan Disease Patients.

Cellular and molecular neurobiology·2025
Same author

Characterizing semi-directed phylogenetic networks and their multi-rootable variants.

Theory in biosciences = Theorie in den Biowissenschaften·2025
Same author

Distinguishing Phylogenetic Level-2 Networks with Quartets and Inter-Taxon Quartet Distances.

Bulletin of mathematical biology·2025
Same author

Single-cell compendium of muscle microenvironment in peripheral artery disease reveals altered endothelial diversity and LYVE1<sup>+</sup> macrophage activation.

Nature cardiovascular research·2025

相关实验视频

Updated: Jul 16, 2025

A Practical Guide to Phylogenetics for Nonexperts
12:00

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

35.4K

通过桃采摘和机器学习构建家族遗传网络.

Giulia Bernardini1, Leo van Iersel2, Esther Julien2

  • 1University of Trieste, Trieste, Italy.

Algorithms for molecular biology : AMB
|September 16, 2023
PubMed
概括
此摘要是机器生成的。

我们开发了高效的启发方法,将家族遗传树结合成单一家族遗传网络. 我们的机器学习和随机化方法处理实用的数据集,提供准确的进化见解.

关键词:
采摘桃的时间启发式 启发式是一种启发式的启发式.杂交方式的混合化.机器学习是机器学习.人类遗传学 是一个学科.

更多相关视频

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
08:57

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

15.9K
Amplification of Near Full-length HIV-1 Proviruses for Next-Generation Sequencing
10:18

Amplification of Near Full-length HIV-1 Proviruses for Next-Generation Sequencing

Published on: October 16, 2018

12.2K

相关实验视频

Last Updated: Jul 16, 2025

A Practical Guide to Phylogenetics for Nonexperts
12:00

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

35.4K
Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
08:57

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

15.9K
Amplification of Near Full-length HIV-1 Proviruses for Next-Generation Sequencing
10:18

Amplification of Near Full-length HIV-1 Proviruses for Next-Generation Sequencing

Published on: October 16, 2018

12.2K

科学领域:

  • 进化生物学是进化的生物学.
  • 计算型的遗传学学.

背景情况:

  • 将家族遗传树调和成一个单一的网络是进化研究的一个核心挑战.
  • 目前的方法是计算密集型的,限制了小型数据集或特定网络类型的可扩展性.

研究的目的:

  • 从多个输入树构建族系网络的高效启发式.
  • 为了解决现有的遗传学网络推理方法的计算局限性.

主要方法:

  • 应用"桃采摘"理论框架,以开发高效的启发式.
  • 整合机器学习模型以捕捉树结构和指导启发式算法.
  • 开发快速的,随机的启发方法,用于实际的族系遗传网络构建.

主要成果:

  • 保证构建一个包含二进制树的所有输入树的系谱网络.
  • 启发式计算在实用大小的数据集上证明了效率,超过了计算上昂贵的精确方法.
  • 机器学习的启发式学习提供了一种新的和有前途的方法来进行遗传学分析.

结论:

  • 拟议的启发式可扩展到现实世界的数据集,提供高质量的遗传学网络.
  • 实验结果验证了开发方法的有效性和准确性.
  • 突出了机器学习应用在推进遗传学方面的潜力.