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

Genomics02:02

Genomics

36.2K
Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
36.2K
Hypothesis: Accept or Fail to Reject?01:17

Hypothesis: Accept or Fail to Reject?

27.6K
The outcome of any hypothesis testing leads to rejecting or not rejecting the null hypothesis. This decision is taken based on the analysis of the data, an appropriate test statistic, an appropriate confidence level, the critical values, and P-values. However, when the evidence suggests that the null hypothesis cannot be rejected, is it right to say, 'Accept' the null hypothesis?
There are two ways to indicate that the null hypothesis is not rejected. 'Accept' the null...
27.6K
Hindsight Biases01:12

Hindsight Biases

3.4K
Hindsight bias leads you to believe that the event you just experienced was predictable, even though it really wasn’t. In other words, you knew all along that things would turn out the way they did. Can you relate this to the phrase "Hindsight is 20/20" now? 
3.4K
Time-Series Graph00:54

Time-Series Graph

4.3K
A time-series graph is a line graph with repeated measurements taken at successive intervals of time. It is also called a time series chart. To construct a time-series graph, one must look at both pieces of a paired data set. The horizontal axis is used to plot the time increments, and the vertical axis is used to plot the values of the variable that one is measuring. By using the axes in this way, each point on the graph will correspond to time and a measured quantity. The points on the graph...
4.3K
What is a Hypothesis?01:14

What is a Hypothesis?

10.4K
A hypothesis can be a simple sentence or statement about a property or any phenomenon observed or predicted for a population. It is usually a claim about a  property of the population. It can be stated for any field observations or experiments. A hypothesis statement cannot be said to be right or wrong as it is merely a statement. It needs to be tested through an elaborate data collection process and an appropriate statistical test. A hypothesis should be a general but not a vague...
10.4K
Multiple Bar Graph01:07

Multiple Bar Graph

5.1K
As the name suggests, a multiple bar graph is the same as a bar graph but has multiple bars to depict relationships between different data values. One can include as many parameters as possible. However, each parameter must have the same unit of measurement.
Each bar or column in the multiple bar graph represents a data value. These graphs are used primarily in interrelating two or more sets of data. The categories of different kinds of data are listed along the horizontal or x-axis, whereas...
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

Phytohemical Profiling, Bioactivity and Toxicity Evaluation of <i>Elsholtzia cypriani</i>, a Potential Multifunctional Natural Feed Additive.

Molecules (Basel, Switzerland)·2026
Same author

Modeling temporal self and interactive evolution for biomedical hypothesis generation.

Journal of biomedical informatics·2025
Same author

Dietary supplementation with herbal powder of Elsholtzia cypriani improves immune function in Muscovy ducks by activating endogenous antioxidant system and modulating gut microbiota.

Poultry science·2025
Same author

Generating Biomedical Hypothesis With Spatiotemporal Transformers.

IEEE journal of biomedical and health informatics·2024
Same author

Effect of drying methods on aroma, taste and antioxidant activity of Dendrobium officinale flower tea: A sensomic and metabolomic study.

Food research international (Ottawa, Ont.)·2024
Same author

Temporal attention networks for biomedical hypothesis generation.

Journal of biomedical informatics·2024
Same journal

circ2DGNN: circRNA-Disease Association Prediction via Transformer-Based Graph Neural Network.

IEEE/ACM transactions on computational biology and bioinformatics·2024
Same journal

Hierarchical Hypergraph Learning in Association- Weighted Heterogeneous Network for miRNA- Disease Association Identification.

IEEE/ACM transactions on computational biology and bioinformatics·2024
Same journal

Discriminative Domain Adaption Network for Simultaneously Removing Batch Effects and Annotating Cell Types in Single-Cell RNA-Seq.

IEEE/ACM transactions on computational biology and bioinformatics·2024
Same journal

MLW-BFECF: A Multi-Weighted Dynamic Cascade Forest Based on Bilinear Feature Extraction for Predicting the Stage of Kidney Renal Clear Cell Carcinoma on Multi-Modal Gene Data.

IEEE/ACM transactions on computational biology and bioinformatics·2024
Same journal

An End-to-End Knowledge Graph Fused Graph Neural Network for Accurate Protein-Protein Interactions Prediction.

IEEE/ACM transactions on computational biology and bioinformatics·2024
Same journal

Generative Biomedical Event Extraction With Constrained Decoding Strategy.

IEEE/ACM transactions on computational biology and bioinformatics·2024
查看所有相关文章

相关实验视频

Updated: Jun 15, 2025

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
07:35

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

Published on: October 13, 2023

1.6K

对比多源时间知识图用于生物医学假设生成.

Huiwei Zhou, Wenchu Li, Weihong Yao

    IEEE/ACM transactions on computational biology and bioinformatics
    |August 28, 2024
    PubMed
    概括
    此摘要是机器生成的。

    本研究引入了时间对比学习 (TCL),通过模拟科学术语在多个时间知识库的共同演变来产生生物医学假设,从而改善了研究发现.

    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

    661
    A Data Integration Workflow to Identify Drug Combinations Targeting Synthetic Lethal Interactions
    07:40

    A Data Integration Workflow to Identify Drug Combinations Targeting Synthetic Lethal Interactions

    Published on: May 27, 2021

    4.1K

    相关实验视频

    Last Updated: Jun 15, 2025

    A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
    07:35

    A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

    Published on: October 13, 2023

    1.6K
    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

    661
    A Data Integration Workflow to Identify Drug Combinations Targeting Synthetic Lethal Interactions
    07:40

    A Data Integration Workflow to Identify Drug Combinations Targeting Synthetic Lethal Interactions

    Published on: May 27, 2021

    4.1K

    科学领域:

    • 生物医学信息学 生物医学信息学
    • 计算生物学 计算生物学
    • 人工智能在医学中的应用

    背景情况:

    • 假设生成 (HG) 通过从科学文献中提取新的见解来加速生物医学研究.
    • 现有的HG方法往往忽视了科学术语的时间动态,限制了它们捕捉不断发展的知识的能力.
    • 多源时间知识库 (KB) 包含关键的最新信息,这些信息在当前的HG方法中未得到充分利用.

    研究的目的:

    • 开发一个创新的时间对比学习 (TCL) 框架用于假设生成.
    • 为了有效地建模实体在多个时间KB的共同进化,以揭示潜在的关联.
    • 通过整合多个来源的时间信息来增强科学术语的时间进化嵌入.

    主要方法:

    • 使用PubMed论文和比较毒基因组学数据库 (CTD) 构建了一个时间关系图.
    • 使用来自医学科目标题 (MeSH) 的时间概念图,以及时间关系图.
    • 训练了两个基于图形卷积网络 (GCN) 的循环网络,以学习实体时间进化嵌入.
    • 实施了交叉视图时间预测任务,通过两种时间知识图 (TKG) 的对比嵌入来学习知识丰富的时间嵌入.

    主要成果:

    • 与单个基于TKG的方法相比,提议的TCL框架显示出更高的性能.
    • 在三个真实世界生物医学术语关系数据集上取得了最先进的结果.
    • 有效地捕捉和建模了科学术语及其关联的时间演变.

    结论:

    • 该TCL框架成功地整合了多个来源的时间KB信息,用于产生假设.
    • 在跨时间KB的实体共同进化的联合建模增强了生物医学关系的发现.
    • 这种方法在利用动态科学知识来产生假设方面取得了重大进展.