MiPRIME


38954836	MiPRIME: An integrated and intelligent platform for mining primer and probe sequences of microbial species. [PMID: 38954836] Zhiming Zhang, Jing Ren, Lili Ren, Lanying Zhang, Qubo Ai, Haixin Long, Yi Ren, Kun Yang, Huiying Feng, Sabrina Li, Xu Li Abstract MOTIVATION: Accurately detecting pathogenic microorganisms requires effective primers and probe designs. Literature-derived primers are a valuable resource as they have been tested and proven effective in previous research. However, manually mining primers from published texts is time-consuming and limited in species scop. RESULTS: To address these challenges, we have developed MiPRIME, a real-time Microbial Primer Mining platform for primer/probe sequences extraction of pathogenic microorganisms with three highlights: i) Comprehensive integration. Covering more than 40 million articles and 548,942 organisms, the platform enables high-frequency microbial gene discovery from a global perspective, facilitating user-defined primer design and advancing microbial research. ii) Employing a BioBERT-based text mining model with 98.02% accuracy, greatly reducing information processing time. iii) using a primer ranking score, PRscore, for intelligent recommendation of species-specific primers. Overall, MiPRIME is a practical tool for primer mining in the pan-microbial field, saving time and cost of trial-and-error experiments. AVAILABILITY: The web is available at {{https://www.ai-bt.com}}. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Bioinformatics. 2024:() \| 0 Citations (from Europe PMC, 2025-03-22)

MiPRIME: An integrated and intelligent platform for mining primer and probe sequences of microbial species. [PMID: 38954836]

Zhiming Zhang, Jing Ren, Lili Ren, Lanying Zhang, Qubo Ai, Haixin Long, Yi Ren, Kun Yang, Huiying Feng, Sabrina Li, Xu Li

Abstract

MOTIVATION: Accurately detecting pathogenic microorganisms requires effective primers and probe designs. Literature-derived primers are a valuable resource as they have been tested and proven effective in previous research. However, manually mining primers from published texts is time-consuming and limited in species scop.
RESULTS: To address these challenges, we have developed MiPRIME, a real-time Microbial Primer Mining platform for primer/probe sequences extraction of pathogenic microorganisms with three highlights: i) Comprehensive integration. Covering more than 40 million articles and 548,942 organisms, the platform enables high-frequency microbial gene discovery from a global perspective, facilitating user-defined primer design and advancing microbial research. ii) Employing a BioBERT-based text mining model with 98.02% accuracy, greatly reducing information processing time. iii) using a primer ranking score, PRscore, for intelligent recommendation of species-specific primers. Overall, MiPRIME is a practical tool for primer mining in the pan-microbial field, saving time and cost of trial-and-error experiments.
AVAILABILITY: The web is available at {{https://www.ai-bt.com}}.
SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Bioinformatics. 2024:() | 0 Citations (from Europe PMC, 2025-03-22)

URL:	https://www.ai-bt.com
Full name:	MiPRIME
Description:	MiPRIME is a real-time platform for mining primer/probe sequences of pathogenic microorganisms, integrating over 40 million articles and 548,942 organisms using a BioBERT-based model with 98.02% accuracy. It features intelligent primer recommendations with PRscore, enhancing efficiency in microbial research.
Year founded:	2024
Last update:	2024-07-02
Version:	v1.0
Accessibility:	Accessible
Country/Region:	China

Data type:	DNA
Data object:	Archaea Bacteria Fungi Virus
Database category:	Gene genome and annotation Health and medicine Interaction
Major species:	NA
Keywords:	primer mining probe design pathogenic microorganisms BioBERT

University/Institution:	Research and Development Department
Address:	Research and Development Department, Coyote Bioscience (Beijing) Co., Ltd., Building 22, Zone 3, Gaolizhang Road, Haidian District, Beijing, 10095, China
City:	Beijing
Province/State:	Beijing
Country/Region:	China
Contact name (PI/Team):	Xu Li
Contact email (PI/Helpdesk):	tclxcccc@126.com

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Database Commons a catalog of worldwide biological databases