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

9.4K
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...
9.4K
Distribution Reliability and Automation01:25

Distribution Reliability and Automation

107
Distribution reliability in electrical power systems is critical for ensuring an uninterrupted power supply to consumers at minimal cost. According to IEEE Standard Terms, reliability is the probability that a device will function without failure over a specified time period or amount of usage. For electric power distribution, this translates to maintaining continuous power supply and addressing customer concerns over power outages. Several indices, as defined by IEEE Standard 1366-2012, are...
107
Regulation of Expression Occurs at Multiple Steps02:24

Regulation of Expression Occurs at Multiple Steps

3.0K
3.0K
Stereotype Content Model02:16

Stereotype Content Model

14.0K
The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
14.0K
Regulation of Expression at Multiple Steps01:23

Regulation of Expression at Multiple Steps

875
The gene expression in cells is regulated at different stages: (i) transcription, (ii) RNA processing, (iii) RNA localization, and (iv) translation. Transcriptional regulation is mediated by regulatory proteins such as transcription factors, activators, or repressors—these control gene expression by initiating or inhibiting the transcription of genes. Once a precursor or pre-mRNA is produced, it undergoes post-transcriptional modification, including 5' capping, splicing, and the...
875
Three-Compartment Open Model01:06

Three-Compartment Open Model

166
The three-compartment open model is a pharmacokinetic model used to describe the distribution and elimination of drugs following extravascular administration. It comprises a central compartment representing the plasma and two peripheral compartments. The highly perfused peripheral compartment represents organs and tissues with a rich blood supply, such as the liver, kidneys, and lungs. The scarcely perfused peripheral compartment represents tissues with lower blood supply, such as adipose...
166

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

Vision Foundry: A System for Training Foundational Vision AI Models.

AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science·2026
Same author

A Secure Sandbox Environment for Orchestrating Medical AI Agents Using Model Context Protocols and Role-Based Access Control.

AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science·2026
Same author

A Framework for Cross-Domain Generalization in Coronary Artery Calcium Scoring Across Gated and Non-Gated Computed Tomography.

AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science·2026
Same author

Logit Fingerprinting: A Novel, Accuracy-Independent Method for Validating Large Language Model Stability in High-Stakes Clinical Applications.

AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science·2026
Same author

Systematic contextual biases in SegmentNT potentially relevant to other nucleotide transformer models.

bioRxiv : the preprint server for biology·2026
Same author

Data-driven thresholds for standardized classification of severe Alzheimer's disease neuropathology using digital neuropathology.

Brain pathology (Zurich, Switzerland)·2026

相关实验视频

Updated: Jun 14, 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

519

安全自助服务的机构平台 大型语言模型探索

V K Cody Bumgardner1, Mitchell A Klusty1, W Vaiden Logan1

  • 1University of Kentucky, Lexington, KY, USA.

AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science
|June 12, 2025
PubMed
概括

本研究提出了一个新的平台,用于使用多LoRA推理创建定制的大型语言模型 (LLM). 它为科学发现和生物医学信息学提供安全,负担得起的AI服务.

更多相关视频

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved Non-model Organisms
10:41

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved Non-model Organisms

Published on: May 9, 2017

9.2K
The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm
06:18

The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm

Published on: October 20, 2022

2.0K

相关实验视频

Last Updated: Jun 14, 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

519
Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved Non-model Organisms
10:41

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved Non-model Organisms

Published on: May 9, 2017

9.2K
The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm
06:18

The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm

Published on: October 20, 2022

2.0K

科学领域:

  • 人工智能的人工智能
  • 生物医学信息学 生物医学信息学
  • 计算机科学 计算机科学

背景情况:

  • 大型语言模型 (LLM) 为科学发现和生物医学信息学提供了重大潜力.
  • 目前的LLM可访问性受到复杂性和成本的限制.
  • 在专门的研究应用中,LLM的定制是至关重要的.

研究的目的:

  • 引入一个用户友好的平台,用于创建定制的大型语言模型 (LLM).
  • 提高研究人员对先进的人工智能模型的可访问性.
  • 提供安全和负担得起的LLM服务.

主要方法:

  • 开发一个利用多个LoRA推理的平台,以实现高效的定制适配器.
  • 使用基于代理的方法实现租户意识的计算网络.
  • 集成数据集策划,模型培训,安全推理和基于文本的特征提取.
  • 强调过程和数据隔离,端到端加密和基于角色的资源身份验证以确保安全.

主要成果:

  • 一个系统架构,使LLMs的高效定制.
  • 为LLM服务提供安全和孤立的计算资源.
  • 从孤立的资源中展示一个统一的系统.
  • 促进安全,负担得起的LLM服务.

结论:

  • 开发的平台简化了对尖端人工智能,特别是大型语言模型的访问.
  • 它通过可访问的人工智能支持科学发现和生物医学信息学的进步.
  • 该系统为定制的LLM部署提供了安全和经济有效的解决方案.