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

Termination of Translation01:44

Termination of Translation

27.8K
The large ribosomal subunit has several important structures essential to translation. These include the peptidyl transferase center (PTC) - which is the site where the peptide bond is formed - and a large, internal, water-filled tube through which the nascent polypeptide moves. This latter structure is called the Peptide Exit Tunnel, and it begins at the PTC and spans the body of the large ribosomal subunit. During translation, as the nascent polypeptide chain is synthesized, it passes through...
27.8K
Improving Translational Accuracy02:07

Improving Translational Accuracy

15.0K
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...
15.0K
Language01:16

Language

919
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...
919
Translation01:31

Translation

157.1K
Lesson: Translation
Translation is the process of synthesizing proteins from the genetic information carried by messenger RNA (mRNA). Following transcription, it constitutes the final step in the expression of genes. This process is carried out by ribosomes, complexes of protein and specialized RNA molecules. Ribosomes, transfer RNA (tRNA), and other proteins produce a chain of amino acids—the polypeptide—as the end product of translation.
Translation Produces the Building Blocks of...
157.1K
Translation01:31

Translation

17.9K
Translation is the process of synthesizing proteins from the genetic information carried by messenger RNA (mRNA). Following transcription, it constitutes the final step in the expression of genes. This process is carried out by ribosomes, complexes of protein and specialized RNA molecules. Ribosomes, transfer RNA (tRNA), and other proteins produce a chain of amino acids—the polypeptide—as the end product of translation.
Translation Produces the Building Blocks of Life
Proteins are...
17.9K
Initiation of Translation02:33

Initiation of Translation

39.1K
Initiating translation is complex because it involves multiple molecules. Initiator tRNA, ribosomal subunits, and eukaryotic initiation factors (eIFs) are all required to assemble on the initiation codon of mRNA. This process consists of several steps that are mediated by different eIFs.
First, the initiator tRNA must be selected from the pool of elongator tRNAs by eukaryotic initiation factor 2 (eIF2). The initiator tRNA (Met-tRNAi) has conserved sequence elements including modified bases at...
39.1K

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

Two-dimensional fluorescence in-gel electrophoresis of coronary restenosis tissues in minipigs: increased adipocyte fatty acid binding protein induces reactive oxygen species-mediated growth and migration in smooth muscle cells.

Arteriosclerosis, thrombosis, and vascular biology·2013
Same author

Purification and characterization of mutant miniPlasmin for thrombolytic therapy.

Thrombosis journal·2013
Same author

[Mechanisms of resistance to EML4-ALK inhibitors in non-small cell lung cancer].

Zhongguo fei ai za zhi = Chinese journal of lung cancer·2013
Same author

NK4 gene therapy inhibits HGF/Met-induced growth of human cholangiocarcinoma cells.

Digestive diseases and sciences·2013
Same author

[Low-grade extraskeletal osteosarcoma of mediastinum: report of a case].

Zhonghua bing li xue za zhi = Chinese journal of pathology·2013
Same author

MedTxting: learning based and knowledge rich SMS-style medical text contraction.

AMIA ... Annual Symposium proceedings. AMIA Symposium·2013
Same journal

Visual Self-Refinement for Autoregressive Models.

Findings of ACL. EMNLP. Conference on Empirical Methods in Natural Language Processing·2026
Same journal

README: Bridging Medical Jargon and Lay Understanding for Patient Education through Data-Centric NLP.

Findings of ACL. EMNLP. Conference on Empirical Methods in Natural Language Processing·2026
Same journal

Large Language Models are In-context Teachers for Knowledge Reasoning.

Findings of ACL. EMNLP. Conference on Empirical Methods in Natural Language Processing·2026
Same journal

Using tournaments to calculate AUROC for zero-shot classification with LLMs.

Findings of ACL. EMNLP. Conference on Empirical Methods in Natural Language Processing·2026
Same journal

Large Language Models for Controllable Multi-property Multi-objective Molecule Optimization.

Findings of ACL. EMNLP. Conference on Empirical Methods in Natural Language Processing·2026
Same journal

Multi-label Sequential Sentence Classification via Large Language Model.

Findings of ACL. EMNLP. Conference on Empirical Methods in Natural Language Processing·2026
查看所有相关文章

相关实验视频

Updated: Feb 10, 2026

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

18.3K

MedCOD:使用丰富的字典链框架改进大型语言模型的英语到西班牙语医学翻译.

Md Shahidul Salim1,2, Lian Fu3, Arav Adikesh Ramakrishnan3

  • 1Center for Healthcare Organization and Implementation Research, VA Bedford Health Care.

Findings of ACL. EMNLP. Conference on Empirical Methods in Natural Language Processing
|February 9, 2026
PubMed
概括
此摘要是机器生成的。

我们开发了MedCOD,这是一个框架,通过将结构化的医学知识整合到大型语言模型 (LLM) 中来增强英语到西班牙语的医学翻译. 这种方法显著提高了各种模型的翻译质量.

更多相关视频

Universal Screening for Prevention of Reading, Writing, and Math Disabilities in Spanish
14:43

Universal Screening for Prevention of Reading, Writing, and Math Disabilities in Spanish

Published on: July 18, 2020

8.6K
Translational Brain Mapping at the University of Rochester Medical Center: Preserving the Mind Through Personalized Brain Mapping
13:12

Translational Brain Mapping at the University of Rochester Medical Center: Preserving the Mind Through Personalized Brain Mapping

Published on: August 12, 2019

46.5K

相关实验视频

Last Updated: Feb 10, 2026

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

18.3K
Universal Screening for Prevention of Reading, Writing, and Math Disabilities in Spanish
14:43

Universal Screening for Prevention of Reading, Writing, and Math Disabilities in Spanish

Published on: July 18, 2020

8.6K
Translational Brain Mapping at the University of Rochester Medical Center: Preserving the Mind Through Personalized Brain Mapping
13:12

Translational Brain Mapping at the University of Rochester Medical Center: Preserving the Mind Through Personalized Brain Mapping

Published on: August 12, 2019

46.5K

科学领域:

  • 医疗信息学 医疗信息学
  • 自然语言处理自然语言处理.
  • 计算语言学 计算语言学

背景情况:

  • 准确的医学翻译对于全球医疗保健的准入至关重要.
  • 大型语言模型 (LLM) 是有前途的,但在特定领域的医学术语方面存在困难.
  • 现有的翻译方法缺乏对结构化医学知识的强有力的整合.

研究的目的:

  • 引入MedCOD (医学字典链),这是一个新的混合框架,用于改进英语到西班牙语的医学翻译.
  • 通过整合UMLS和LLM-KB范式的结构化领域知识来增强LLM.
  • 评估MedCOD在提高多个开源LLMs的翻译质量的有效性.

主要方法:

  • 构建了2999个英语-西班牙语MedlinePlus文章的并行库.
  • 开发了一套具有结构化的医疗背景的100句话测试集.
  • 采用结构化提示,多语言变体,同义词和UMLS定义.
  • 在四个开源LLM (Phi-4,Qwen2.5-14B,Qwen2.5-7B,LLaMA-3.1-8B) 上使用了基于LoRA的微调.

主要成果:

  • 在所有评估的LLMs中,MedCOD显著提高了翻译质量.
  • 使用MedCOD和微调的Phi-4获得了优异的BLEU (44.23),chrF++ (28.91) 和COMET (0.863) 分数.
  • 无论是MedCOD提示还是模型调整,都独立地提高了性能,联合使用带来了最大的收益.
  • 性能超过了强大的基线模型,如GPT-4o和GPT-4o-mini.

结论:

  • 通过MedCOD进行结构化的知识整合,大大提高了医学翻译的LLM性能.
  • MedCOD框架提供了一种可行的策略,可以提高医学语言翻译的准确性和可靠性.
  • 这种方法对推进全球卫生沟通中人工智能应用具有重大潜力.