Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Improving Translational Accuracy

Improving Translational Accuracy

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...

Genetic Lingo

Genetic Lingo

pre-mRNA Processing

pre-mRNA Processing

In eukaryotic cells, transcripts made by RNA polymerase are modified and processed before exiting the nucleus. Unprocessed RNA is called precursor mRNA or pre-mRNA to distinguish it from mature mRNA.
Once about 20-40 ribonucleotides have been joined together by RNA polymerase, a group of enzymes adds a “cap” to the 5’ end of the growing transcript. In this process, a 5’ phosphate is replaced by modified guanosine that has a methyl group attached to it (7-Methyl...

lncRNA - Long Non-coding RNAs

lncRNA - Long Non-coding RNAs

Translation

Translation

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...

MicroRNAs

MicroRNAs

MicroRNA (miRNA) are short, regulatory RNA transcribed from introns—non-coding regions of a gene—or intergenic regions—stretches of DNA present between genes. Several processing steps are required to form biologically active, mature miRNA. The initial transcript, called primary miRNA (pri-mRNA), base-pairs with itself forming a stem-loop structure. Within the nucleus, an endonuclease enzyme, called Drosha, shortens the stem-loop structure into hairpin-shaped pre-miRNA. After...

You might also read

Related Articles

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

Sort by

Same author

Enhancing the quality and trustworthiness of large language model-generated summaries of clinical oncology literature.

JAMIA open·2026

Same author

Supporting the working life exposome: Annotating occupational exposure for enhanced literature search.

PloS one·2024

Same author

Knowledge-enhanced Graph Topic Transformer for Explainable Biomedical Text Summarization.

IEEE journal of biomedical and health informatics·2023

Same author

Large-scale neural biomedical entity linking with layer overwriting.

Journal of biomedical informatics·2023

Same author

Contextualized medication event extraction with striding NER and multi-turn QA.

Journal of biomedical informatics·2023

Same author

A novel corpus of molecular to higher-order events that facilitates the understanding of the pathogenic mechanisms of idiopathic pulmonary fibrosis.

Scientific reports·2023

Search research articles

Related Experiment Video

Updated: Oct 17, 2025

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Published on: February 23, 2019

BioVAE: a pre-trained latent variable language model for biomedical text mining.

Hai-Long Trieu^1,2, Makoto Miwa^1,3, Sophia Ananiadou^2,4

¹Artificial Intelligence Research Center (AIRC), National Institute of Advanced Industrial Science and Technology (AIST), Tokyo 135-0064, Japan.

Bioinformatics (Oxford, England)

|October 12, 2021

Summary

This summary is machine-generated.

BioVAE is the first large-scale pre-trained latent variable language model for biomedical text mining. It achieves state-of-the-art performance and generates more accurate biomedical sentences than existing models.

More Related Videos

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

Related Experiment Videos

Last Updated: Oct 17, 2025

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Published on: February 23, 2019

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

Area of Science:

Natural Language Processing
Bioinformatics
Artificial Intelligence

Background:

Large-scale pre-trained language models (PLMs) have improved biomedical text mining.
Combining PLMs with deep generative models shows promise.
A gap exists for biomedical-specific pre-trained models.

Purpose of the Study:

Introduce BioVAE, the first large-scale pre-trained latent variable language model for the biomedical domain.
Leverage the OPTIMUS framework for training on extensive biomedical text data.
Enhance performance on biomedical text mining tasks and improve sentence generation.

Main Methods:

Developed BioVAE using the OPTIMUS framework.
Trained the model on a large corpus of biomedical text.
Evaluated performance on various biomedical text mining tasks.

Main Results:

BioVAE achieved state-of-the-art (SOTA) performance on several biomedical text mining tasks.
Outperformed existing publicly available biomedical PLMs.
Demonstrated superior accuracy in generating biomedical sentences compared to the original OPTIMUS output.

Conclusions:

BioVAE represents a significant advancement in biomedical natural language processing.
The model offers improved capabilities for text mining and sentence generation in the biomedical field.
BioVAE provides a valuable, freely available resource for the research community.