Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Improving Translational Accuracy02:07

Improving Translational Accuracy

3.3K
3.3K
Improving Translational Accuracy02:07

Improving Translational Accuracy

12.8K
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...
12.8K
Translation01:31

Translation

153.2K
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...
153.2K
Translation01:31

Translation

17.0K
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...
17.0K
Termination of Translation01:44

Termination of Translation

6.2K
6.2K
Termination of Translation01:44

Termination of Translation

26.7K
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...
26.7K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Best-first search-based approach for mining top-k closed frequent itemsets from uncertain databases.

PloS one·2026
Same author

Using transformer-based models for Vietnamese language detection.

PloS one·2026
Same author

Propensity Score Matching Analysis of Extracorporeal Versus Intracorporeal Anastomosis in Laparoscopic Colectomy for Right Colon Cancer.

Cureus·2025
Same author

COVID-19 Infection Rates in Vaccinated and Unvaccinated Inmates: A Retrospective Cohort Study.

Cureus·2023
Same author

Heavyweight Statistical Alignment to Guide Neural Translation.

Computational intelligence and neuroscience·2022
Same journal

RETRACTION: Multidimensional Heterogeneous Network Link Adaptation Based on Mobile Environment.

Computational intelligence and neuroscience·2026
Same journal

RETRACTION: Framework to Segment and Evaluate Multiple Sclerosis Lesion in MRI Slices Using VGG-UNet.

Computational intelligence and neuroscience·2026
Same journal

RETRACTION: Facial Emotion Recognition Using a Novel Fusion of Convolutional Neural Network and Local Binary Pattern in Crime Investigation.

Computational intelligence and neuroscience·2026
Same journal

RETRACTION: Automatic Intelligent System Using Medical of Things for Multiple Sclerosis Detection.

Computational intelligence and neuroscience·2026
Same journal

RETRACTION: Intangible Cultural Heritage Reproduction and Revitalization: Value Feedback, Practice, and Exploration Based on the IPA Model.

Computational intelligence and neuroscience·2026
Same journal

RETRACTION: CNN Based Multiclass Brain Tumor Detection Using Medical Imaging.

Computational intelligence and neuroscience·2025
See all related articles

Related Experiment Video

Updated: Nov 25, 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

853

Mixed-Level Neural Machine Translation.

Thien Nguyen1, Huu Nguyen2, Phuoc Tran3

  • 1Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City, Vietnam.

Computational Intelligence and Neuroscience
|December 18, 2020
PubMed
Summary
This summary is machine-generated.

This study introduces a novel heterogeneous translation unit system for Russian-Vietnamese neural machine translation. The new system enhances translation quality by adapting to linguistic differences between the languages, outperforming existing homogeneous systems.

More Related Videos

Decoding Natural Behavior from Neuroethological Embedding
08:00

Decoding Natural Behavior from Neuroethological Embedding

Published on: October 3, 2025

326
Analysis of Translation in the Developing Mouse Brain using Polysome Profiling
08:38

Analysis of Translation in the Developing Mouse Brain using Polysome Profiling

Published on: May 22, 2021

5.5K

Related Experiment Videos

Last Updated: Nov 25, 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

853
Decoding Natural Behavior from Neuroethological Embedding
08:00

Decoding Natural Behavior from Neuroethological Embedding

Published on: October 3, 2025

326
Analysis of Translation in the Developing Mouse Brain using Polysome Profiling
08:38

Analysis of Translation in the Developing Mouse Brain using Polysome Profiling

Published on: May 22, 2021

5.5K

Area of Science:

  • Computational Linguistics
  • Natural Language Processing
  • Machine Translation

Background:

  • Neural machine translation (NMT) systems require effective translation unit systems for source and target embeddings.
  • Homogeneous translation unit systems, using identical units for both languages, are insufficient for linguistically diverse pairs like Russian and Vietnamese.

Purpose of the Study:

  • To propose a novel heterogeneous translation unit system tailored for the Russian-Vietnamese language pair.
  • To address the limitations of homogeneous systems by considering the distinct linguistic properties of synthetic (Russian) and analytic (Vietnamese) languages.

Main Methods:

  • Developed a heterogeneous translation unit system by adjusting embedding levels.
  • Decreased embedding level on the Russian (source) side by splitting tokens into subtokens.
  • Increased embedding level on the Vietnamese (target) side by merging neighboring tokens into supertokens.

Main Results:

  • The proposed heterogeneous system achieved a 1.17 BLEU score improvement over the best existing homogeneous Russian-Vietnamese translation system.
  • Demonstrated the effectiveness of adapting translation units to specific language pair characteristics.

Conclusions:

  • The novel heterogeneous translation unit system offers a superior approach for Russian-Vietnamese NMT.
  • This methodology can be extended to develop effective translation bots for other language pairs with differing linguistic structures.