MBORS: Mosquito vector Biocontrol Ontology and Recommendation System.

IF 0.8 4区 医学 Q4 INFECTIOUS DISEASES Journal of Vector Borne Diseases Pub Date : 2024-01-01 Epub Date: 2024-03-23 DOI:10.4103/0972-9062.383640
G Jeyakodi, P Shanthi Bala, O T Sruthi, K Swathi
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引用次数: 0

Abstract

Background objectives: Mosquito vectors are disease-causing insects, responsible for various life-threatening vector-borne diseases such as dengue, Zika, malaria, chikungunya, and lymphatic filariasis. In practice, synthetic insecticides are used to control the mosquito vector, but, the continuous usage of synthetic insecticides is toxic to human health resulting in communicable diseases. Non-toxic biocontrol agents such as bacteria, fungus, plants, and mosquito densoviruses play a vital role in controlling mosquitoes. Community awareness of mosquito biocontrol agents is required to control vector-borne diseases. Mosquito vector-based ontology facilitates mosquito biocontrol by providing information such as species names, pathogen-associated diseases, and biological controlling agents. It helps to explore the associations among the mosquitoes and their biocontrol agents in the form of rules. The Mosquito vector-based Biocontrol Ontology Recommendation System (MBORS) provides the knowledge on mosquito-associated biocontrol agents to control the vector at the early stage of the mosquitoes such as eggs, larvae, pupae, and adults. This paper proposes MBORS for the prevention and effective control of vector-borne diseases. The Mosquito Vector Association ontology (MVAont) suggests the appropriate mosquito vector biocontrol agents (MosqVecRS) for related diseases.

Methods: Natural Language Processing and Data mining are employed to develop the MBORS. While Tokenization, Part-of-speech Tagging (POS), Named Entity Recognition (NER), and rule-based text mining techniques are used to identify the mosquito ontology concepts, the data mining apriori algorithm is used to predict the associations among them.

Results: The outcome of the MBORS results in MVAont as Web Ontology Language (OWL) representation and MosqVecRS as an Android application. The developed ontology and recommendation system are freely available on the web portal.

Interpretation conclusion: The MVAont predicts harmless biocontrol agents which help to diminish the rate of vector-borne diseases. On the other hand, the MosqVecRS system raises awareness of vectors and vector-borne diseases by recommending suitable biocontrol agents to the vector control community and researchers.

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MBORS:蚊媒生物控制本体论和推荐系统。
背景目标:蚊子病媒是致病昆虫,是登革热、寨卡、疟疾、基孔肯雅病和淋巴丝虫病等各种威胁生命的病媒传播疾病的罪魁祸首。在实践中,人们使用合成杀虫剂来控制蚊媒,但持续使用合成杀虫剂对人类健康有毒,会导致传染病。无毒的生物控制剂,如细菌、真菌、植物和蚊虫致病病毒,在控制蚊虫方面发挥着重要作用。要控制病媒传播的疾病,就需要提高社区对蚊子生物控制剂的认识。基于蚊媒的本体论通过提供物种名称、病原体相关疾病和生物控制剂等信息来促进蚊子生物控制。它有助于以规则的形式探索蚊子及其生物控制剂之间的关联。基于蚊子病媒的生物控制本体推荐系统(MBORS)提供了与蚊子相关的生物控制剂知识,可在蚊子的卵、幼虫、蛹和成虫等早期阶段控制病媒。本文提出了用于预防和有效控制病媒传播疾病的 MBORS。蚊媒关联本体(MVAont)为相关疾病提出了合适的蚊媒生物控制剂(MosqVecRS):方法:采用自然语言处理和数据挖掘技术开发蚊媒关联本体。方法:采用自然语言处理和数据挖掘来开发 MBORS。在使用标记化、语音部分标记(POS)、命名实体识别(NER)和基于规则的文本挖掘技术来识别蚊子本体概念的同时,使用数据挖掘 apriori 算法来预测这些概念之间的关联:结果:MBORS 的成果是 MVAont 作为网络本体语言(OWL)表示法和 MosqVecRS 作为安卓应用程序。开发的本体和推荐系统可在门户网站上免费获取:MVAont 预测了无害的生物控制剂,有助于降低病媒传播疾病的发生率。另一方面,MosqVecRS 系统通过向病媒控制界和研究人员推荐合适的生物控制剂,提高了人们对病媒和病媒传播疾病的认识。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Vector Borne Diseases
Journal of Vector Borne Diseases INFECTIOUS DISEASES-PARASITOLOGY
CiteScore
0.90
自引率
0.00%
发文量
89
审稿时长
>12 weeks
期刊介绍: National Institute of Malaria Research on behalf of Indian Council of Medical Research (ICMR) publishes the Journal of Vector Borne Diseases. This Journal was earlier published as the Indian Journal of Malariology, a peer reviewed and open access biomedical journal in the field of vector borne diseases. The Journal publishes review articles, original research articles, short research communications, case reports of prime importance, letters to the editor in the field of vector borne diseases and their control.
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