DMLS: an automated pipeline to extract the Drosophila modular transcription regulators and targets from massive literature articles

Author:

Yang Tzu-Hsien12ORCID,Yu Yu-Huai1,Wu Sheng-Hang3,Chang Fang-Yuan3,Tsai Hsiu-Chun3,Yang Ya-Chiao4

Affiliation:

1. Department of Biomedical Engineering, National Cheng Kung University , No.1, University Road, Tainan 701, Taiwan

2. Medical Device Innovation Center, National Cheng Kung University , No.1, University Road, Tainan 701, Taiwan

3. Department of Information Management, National Central University , No. 300, Zhongda RD., Zhongli District, Taoyuan 320, Taiwan

4. Institute of Information Management, National Yang Ming Chiao Tung University , No. 1001, Daxue Rd., East Dist., Hsinchu 300093, Taiwan

Abstract

Abstract Transcription regulation in multicellular species is mediated by modular transcription factor (TF) binding site combinations termed cis-regulatory modules (CRMs). Such CRM-mediated transcription regulation determines the gene expression patterns during development. Biologists frequently investigate CRM transcription regulation on gene expressions. However, the knowledge of the target genes and regulatory TFs participating in the CRMs under study is mostly fragmentary throughout the literature. Researchers need to afford tremendous human resources to fully surf through the articles deposited in biomedical literature databases in order to obtain the information. Although several novel text-mining systems are now available for literature triaging, these tools do not specifically focus on CRM-related literature prescreening, failing to correctly extract the information of the CRM target genes and regulatory TFs from the literature. For this reason, we constructed a supportive auto-literature prescreener called Drosophila Modular transcription-regulation Literature Screener (DMLS) that achieves the following: (i) prescreens articles describing experiments on modular transcription regulation, (ii) identifies the described target genes and TFs of the CRMs under study for each modular transcription-regulation-describing article and (iii) features an automated and extendable pipeline to perform the task. We demonstrated that the final performance of DMLS in extracting the described target gene and regulatory TF lists of CRMs under study for given articles achieved test macro area under the ROC curve (auROC) = 89.7% and area under the precision-recall curve (auPRC) = 77.6%, outperforming the intuitive gene name-occurrence-counting method by at least 19.9% in auROC and 30.5% in auPRC. The web service and the command line versions of DMLS are available at https://cobis.bme.ncku.edu.tw/DMLS/  and  https://github.com/cobisLab/DMLS/, respectively. Database Tool URL: https://cobis.bme.ncku.edu.tw/DMLS/

Funder

National Cheng Kung University

National Science and Technology Council

Ministry of Education, Taiwan

Publisher

Oxford University Press (OUP)

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