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

Language Development01:22

Language Development

449
Children master language quickly and with relative ease, supported by both biological predisposition and reinforcement. B. F. Skinner (1957) proposed that language is learned through reinforcement, while Noam Chomsky (1965) argued that language acquisition mechanisms are biologically determined.
The critical period for language acquisition suggests that the ability to acquire language is at its peak early in life. As people age, this proficiency decreases. Language development begins very...
449
Improving Translational Accuracy02:07

Improving Translational Accuracy

11.9K
Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
11.9K
Language and Cognition01:27

Language and Cognition

441
Language serves as a bridge between ideas and communication, influencing how individuals perceive and interact with the world. Psychologists have long debated whether language shapes thought or vice versa. This discussion gained grip with Edward Sapir and Benjamin Lee Whorf in the 1940s, who proposed that language determines thought, a concept known as linguistic determinism. They suggested that the vocabulary and structure of a language influence how its speakers think and perceive reality.
441
Genome Annotation and Assembly03:36

Genome Annotation and Assembly

19.3K
The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
19.3K

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

HES1 inhibition overcomes CDK4/6 inhibitor resistance by targeting cancer stemness in lung adenocarcinoma.

Journal of experimental & clinical cancer research : CR·2026
Same author

Development of a multimodal large language model for early warning and diagnosis of chronic ocular GVHD.

NPJ digital medicine·2026
Same author

The research progress of gastric cancer vaccines: a narrative review.

Translational cancer research·2026
Same author

Application of tandem mass spectrometry for blood acylcarnitine and amino acid profiling in differentiating etiologies of neonatal cholestasis.

Frontiers in pediatrics·2026
Same author

Revascularization of Transcortical Vessels Improves Tendon-to-Bone Healing for Rotator Cuff Repair.

The American journal of sports medicine·2026
Same author

Network pharmacology and experimental validation reveal inhibition of the JAK2/STAT3 pathway by hydrogen sulfide in diabetic cardiomyopathy.

International immunopharmacology·2026

相关实验视频

Updated: Sep 12, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

681

从使用大型语言模型的文献中开发生物医学知识库的基础 - - 一个系统的评估.

Chen Miao1, Zhenghao Zhang2, Jiamin Chen2

  • 1School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong.

Computational and structural biotechnology journal
|August 8, 2025
PubMed
概括

评估大型语言模型 (LLM) 对于生物医学知识提取至关重要. 我们的基准显示了显著的性能差异,突出了需要仔细及时的工程和源验证的需要.

关键词:
生物医学知识库 生物医学知识库大型语言模型.快递工程是指快递的工程.

更多相关视频

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

578
Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

652

相关实验视频

Last Updated: Sep 12, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

681
Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

578
Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

652

科学领域:

  • 生物医学信息学 生物医学信息学
  • 自然语言处理自然语言处理.
  • 人工智能的人工智能

背景情况:

  • 大型语言模型 (LLM) 显示了生物医学应用的潜力.
  • 从生物医学文献中提取可靠的知识,对于知识基础的发展至关重要.
  • 目前在这个领域评估LLM可靠性的方法是不够的.

研究的目的:

  • 开发和利用一个基准来比较生物医学知识提取中的LLM绩效.
  • 在11个不同的知识提取任务中评估LLM能力.
  • 调查特定任务示例对LLM绩效的影响.

主要方法:

  • 为11个文学知识提取任务创建一个基准套件.
  • 对这些任务进行多个LLM的比较,有或没有上下文示例.
  • 基于任务复杂性,数据特征和输出要求,对LLM绩效的分析.

主要成果:

  • 在不同的LLM和任务中观察到显著的性能变化.
  • 士学位的表现受技术专业化,任务难度,信息分散和标准化需求的影响.
  • 要求LLM引用源文本可以提高可靠性,但也带来了即时的工程挑战.

结论:

  • 生物医学知识提取的LLM绩效是高度可变和任务依赖的.
  • 谨慎的提示设计,包括引用源文本,对于可靠的LLM应用程序是必要的.
  • 需要进一步的研究来优化LLM提示,以获得强大的生物医学知识提取.