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

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
Genomics02:02

Genomics

37.5K
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...
37.5K
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
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

130
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
130

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

CD22 is upregulated and displays suppressive properties on CD4+ T cells upon a persistent virus infection.

Journal of immunology (Baltimore, Md. : 1950)·2026
Same author

<i>Cordyceps cicadae</i> polysaccharide and plant extract as a potential antibiotic-free feed additive: effects on growth performance, antioxidant capacity, and cecal microbiota of Yandang chickens.

Frontiers in veterinary science·2026
Same author

Sphingosine 1-phosphate lyase expressed in pulmonary epithelial cells potentiates host innate defenses and alleviates influenza pathogenicity in mice.

bioRxiv : the preprint server for biology·2026
Same author

The clinical and molecular landscape of thalamic glioma.

Neuro-oncology·2026
Same author

Defective cuticle-derived signals enhance extracellular ATP response and plant immunity.

The New phytologist·2026
Same author

High-Quality Genome Assembly of the White King Pigeon for Genetic Reference of Chinese Market Pigeon Breeds.

Scientific data·2026

相关实验视频

Updated: Sep 17, 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

692

spaLLM:通过大型语言模型集成来增强多学科数据中的空间域分析.

Longyi Li1, Liyan Dong1, Hao Zhang1

  • 1Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, College of Computer Science and Technology, Jilin University, 2699 Qianjin Street, Changchun 130012, Jilin, China.

Briefings in bioinformatics
|July 3, 2025
PubMed
概括
此摘要是机器生成的。

我们介绍了 spaLLM,这是一种使用大型语言模型进行空间多omics分析的新方法. 它增强了基因表达数据,以准确识别空间域,优于现有方法.

关键词:
图表神经网络的神经网络大型语言模型空间域是一个空间域.空间多主题空间多主题空间分辨率的转录学

更多相关视频

Author Spotlight: Advancing Alzheimer's Research &#8211; Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.3K
Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts
08:51

Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts

Published on: September 20, 2024

1.5K

相关实验视频

Last Updated: Sep 17, 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

692
Author Spotlight: Advancing Alzheimer's Research &#8211; Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.3K
Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts
08:51

Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts

Published on: September 20, 2024

1.5K

科学领域:

  • 计算生物学 计算生物学
  • 基因组学就是基因组学.
  • 生物信息学是一种生物信息学.

背景情况:

  • 空间多组学技术通过将基因表达数据与空间信息相结合,为组织组织提供了洞察力.
  • 由于这些技术中基因表达数据的固有稀疏性,在组织中破译不同的空间域受到阻碍.

研究的目的:

  • 开发一种新的计算方法,spaLLM,用于在多omics数据中增强空间域分析.
  • 利用大型语言模型来改善数据表示,克服稀疏基因表达数据的局限性.

主要方法:

  • spaLLM集成了一个预训练的单细胞语言模型 (scGPT) 与图形神经网络和多视图注意力.
  • 该方法弥补了稀疏的基因表达数据,提高了不同奥米克模式的灵敏度和分辨率.
  • 该方法旨在处理多种空间模式,包括RNA,染色质和蛋白质数据,并适应新技术.

主要成果:

  • 与四个数据集和平台的八种最先进的方法进行基准测试,证明了spaLLM的卓越性能.
  • 在多个监督评估指标中,spaLLM的表现始终优于现有方法.
  • 该模型有效地改善了用于空间域识别的数据表示.

结论:

  • spaLLM代表了空间多学科数据分析的重大进步,特别是用于识别空间领域.
  • 大型语言模型的集成提供了一种强大的方法来解决数据稀疏性和提高分析分辨率.
  • 该方法的灵活性和表现出卓越的性能使其成为生物研究中的一个有价值的工具.