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

Genome Size and the Evolution of New Genes03:21

Genome Size and the Evolution of New Genes

2.5K
2.5K
lncRNA - Long Non-coding RNAs02:39

lncRNA - Long Non-coding RNAs

2.9K
2.9K
Gene Families01:57

Gene Families

2.6K
2.6K
Language01:16

Language

250
Language is a unique communication system that uses words and systematic rules to organize and transmit information. Unlike other forms of communication, which may involve postures, movements, odors, or vocalizations, language relies on symbols and grammar. This makes human communication distinct from that of other species, who also communicate but do not use language in the same way humans do.
Corballis and Suddendorf (2007) and Tomasello and Rakoczy (2003) highlight the role of language in...
250
mRNA Stability and Gene Expression02:51

mRNA Stability and Gene Expression

2.9K
2.9K
Improving Translational Accuracy02:07

Improving Translational Accuracy

2.6K
2.6K

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

A pragmatist approach to bridging tables and ontologies through LinkML and punning.

Journal of biomedical semantics·2026
Same author

VO: The Vaccine Ontology.

Scientific data·2026
Same author

The Cell Ontology in the age of single-cell omics.

Scientific data·2026
Same author

Representing dental caries and dysbiosis within the oral microbiome in the Oral Health and Disease Ontology.

Journal of biomedical semantics·2026
Same author

OpenScientist: evaluating an open agentic AI co-scientist to accelerate biomedical discovery.

medRxiv : the preprint server for health sciences·2026
Same author

Systematic benchmarking demonstrates large language models have not reached the diagnostic accuracy of traditional rare-disease decision support tools.

European journal of human genetics : EJHG·2026
Same journal

Poisoning the Genome: Targeted Backdoor Attacks on DNA Foundation Models.

ArXiv·2026
Same journal

Mechanistic mathematical model of the in vitro infection dynamics of Bunyamwera and Batai viruses including MOI-dependent shortening of the eclipse phase.

ArXiv·2026
Same journal

AI-Driven Lumped-Element Modeling of Human Respiratory System for Studying Voice Mechanics.

ArXiv·2026
Same journal

Beyond Algorithms: Conceptual Innovation in Medical Imaging AI.

ArXiv·2026
Same journal

Feynman Kac Reweighted Schrödinger Bridge Matching for Surface-Based Tau PET Harmonization.

ArXiv·2026
Same journal

Agentic Discovery of Non-Canonical Antimicrobial Peptides with AMPGAN v3.

ArXiv·2026
查看所有相关文章

相关实验视频

Updated: Jul 27, 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

632

使用大型语言模型进行基因组总结.

Marcin P Joachimiak1, J Harry Caufield1, Nomi L Harris1

  • 1Biosystems Data Science Department, Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA.

ArXiv
|June 9, 2023
PubMed
概括
此摘要是机器生成的。

大型语言模型 (LLM) 可以总结基因功能,但不能取代基因列表的统计丰富分析. 新的LLM模型对未来的生物数据解释有希望.

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

348
A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research
09:35

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research

Published on: August 16, 2017

17.9K

相关实验视频

Last Updated: Jul 27, 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

632
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

348
A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research
09:35

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research

Published on: August 16, 2017

17.9K

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:

  • 分子生物学家使用统计丰富分析分析高通量实验的基因列表.
  • 基因本体学 (GO) 是一个关键的知识库,用于注释基因功能.
  • 解释基因列表可以作为文本总结任务来处理.

研究的目的:

  • 评估大型语言模型 (LLM) 的基因组功能总结作为标准丰富分析的补充.
  • 用策划注释,叙事摘要或直接模型检索来评估LLM绩效.
  • 为了比较基于LLM的总结与基因列表解释的传统统计方法.

主要方法:

  • 塔利斯曼 (术语人工智能,注释和叙述的总结) 是使用生成性AI开发的.
  • 用不同的数据源来测试LLM:本体注释,叙事摘要和直接检索.
  • 绩效是根据生成的GO术语列表的可信性,生物有效性,精度和回忆来评估的.

主要成果:

  • 基于LLM的方法产生了可信和生物有效的GO术语列表.
  • 实际上,LLM无法提供可靠的统计分数 (p值),并且经常返回不显著的术语.
  • 法律法规很少总结标准丰富分析发现的最精确的术语.
  • 新的LLM模型在统计学上显示了比较旧的模型显著的改进.
  • 快速变化导致了非决定性和截然不同的术语列表.

结论:

  • 基于LLM的方法目前不适合作为标准基因丰富分析的替代品.
  • 在整合隐含知识和处理大型,复杂的基因组方面,LLM可能会提供总结的好处.
  • 未来LLM技术的进步可能会提高它们在生物学数据解释中的实用性.