Beijing, China

Mingjing Gao

This inventor holds 1 USPTO granted patent and 1 published patent application. Top assignees: Beijing Gigaceuticals Tech. Co. Ltd, Peking University. Active years: 2024.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Mingjing Gao. Retrieved from https://idiyas.com/inventor/mingjing-gao

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

USPTO Granted Patents = 1 

% Patents Active = 100.0

Average Co-Inventor Count = 5.0

ph-index = 1


Company Filing History:


Years Active: 2024

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1 patent (USPTO):Explore Patents

Title: Innovations of Mingjing Gao in Compound Function Prediction

Introduction

Mingjing Gao is a prominent inventor based in Beijing, China. He has made significant contributions to the field of compound function prediction through his innovative methods. His work focuses on utilizing neural networks and connectivity map algorithms to enhance the efficacy prediction of compounds.

Latest Patents

Mingjing Gao holds a patent for a "Compound function prediction method based on neural network and connectivity map algorithm." This method is designed to predict the efficacy of a compound by constructing a compound molecule-encoding vector neural network. The process involves training various neural networks to evaluate the correlation between compounds and specific diseases or phenotypes.

Career Highlights

Throughout his career, Mingjing Gao has worked with notable organizations, including Beijing Gigaceuticals Tech Co. Ltd and Peking University. His experience in these institutions has allowed him to develop and refine his innovative approaches to compound function prediction.

Collaborations

Mingjing Gao has collaborated with esteemed colleagues such as Zhengwei Xie and Jie Zhu. Their joint efforts have contributed to advancements in the field of compound function prediction.

Conclusion

Mingjing Gao's innovative work in compound function prediction showcases the potential of neural networks in enhancing drug efficacy assessments. His contributions are paving the way for future advancements in the field.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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