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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 the pre-miRNA...

Regulation of Expression Occurs at Multiple Steps

Regulation of Expression Occurs at Multiple Steps

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The Upf proteins that carry out nonsense-mediated decay (NMD) are found in all eukaryotic organisms, including humans. Each protein has an individual role, but they need to work in collaboration. Upf1 is an ATP-dependent RNA helicase that unwinds the RNA helix. Because Upf1 can unwind any RNA, Upf2 and Upf3 are required to help Upf1 discriminate between nonsense and normal mRNAs.
Usually, Upf3 binds to an Exon Junction Complex (EJC) at mRNA splice sites. If a ribosome fully translates the mRNA,...

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Ribosome Profiling

Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
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Related Experiment Video

Updated: Jan 11, 2026

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization

Published on: October 3, 2025

Patent analysis of mRNA therapy using deep learning.

Yuanqi Cai^1,2,3, Xuejing Zhang^1,2,3, Xiaoming Zhang⁴

¹Center for Medical Artificial Intelligence, Shandong University of Traditional Chinese Medicine, Qingdao, 266112, China.

Naunyn-Schmiedeberg'S Archives of Pharmacology

|November 19, 2025

Summary

This summary is machine-generated.

Messenger RNA (mRNA) technology, recognized with a Nobel Prize, is rapidly advancing. Patent analysis reveals infectious diseases and cancer as key applications, with delivery and vector technologies driving future innovation.

Keywords:

Bibliometric analysis Deep learning Drug delivery MRNA therapy Patent landscape Patent quality

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Published on: January 21, 2020

Area of Science:

Biotechnology and Pharmaceutical Sciences
Molecular Biology and Genetics
Intellectual Property and Innovation Management

Background:

Messenger RNA (mRNA) technology has shown significant potential, particularly highlighted by its role during the COVID-19 pandemic and the 2023 Nobel Prize.
Accelerated global research and development in mRNA technology necessitates a clear understanding of the competitive patent landscape to guide innovation and industrial growth.

Purpose of the Study:

To conduct a quantitative patent analysis of mRNA therapeutics over the last 27 years.
To identify current technological trends, predict future core technologies and key patentees using advanced analytical methods.
To map the intellectual property landscape and understand the competitive dynamics in mRNA therapy development.

Main Methods:

Utilized the Derwent patent database for comprehensive data collection.
Employed social network analysis and patent quality assessment for quantitative analysis.
Applied deep learning and machine learning algorithms for predictive analysis of future technologies and patentees.

Main Results:

Current mRNA drug development predominantly focuses on infectious diseases and cancer.
Delivery technology remains a critical challenge, while targeted drug research and vector technology are identified as key future directions.
Emerging organizations are innovating novel delivery systems, challenging established patent thickets held by major companies, indicating a diversifying and competitive landscape.

Conclusions:

The global mRNA therapy landscape is dynamic and multifaceted, with a shift in power away from monopolies held by giant corporations.
The patent landscape analysis, enhanced by deep learning, serves as a valuable knowledge tool for researchers and industry.
This study provides insights to inspire the development of efficient production methods and strategic innovation in mRNA therapies.