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Text mining and portal development for gene-specific publications on Alzheimer’s disease and other neurodegenerative diseases

Jiannan Liu, Huanmei Wu, View ORCID ProfileDaniel H. Robertson, Jie Zhang
doi: https://doi.org/10.1101/2022.06.28.497987
Jiannan Liu
1Dept of BioHealth Informatics, Indiana University School of Informatics & Computing, Indianapolis, IN 46202, USA
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Huanmei Wu
2Health Services Administration & Policy, Temple University College of Public Health, Philadelphia, PA 19122, USA
1Dept of BioHealth Informatics, Indiana University School of Informatics & Computing, Indianapolis, IN 46202, USA
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Daniel H. Robertson
3Integrated Data Sciences, Indiana Biosciences Research Institute, Indianapolis, IN 46202
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Jie Zhang
4Dept of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis IN 46202, USA
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  • For correspondence: jizhan@iu.edu
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Abstract

Background Tremendous research efforts have been made in the Alzheimer’s disease (AD) field to understand the disease etiology, progression and discover treatments for AD. Many mechanistic hypotheses, therapeutic targets and treatment strategies have been proposed in the last few decades. Reviewing previous work and staying current on this ever-growing body of AD publications is an essential yet difficult task for AD researchers.

Methods In this study, we designed and implemented a natural language processing (NLP) pipeline to extract gene-specific neurodegenerative disease (ND) -focused information from the PubMed database. The collected publication information was filtered and cleaned to construct AD-related gene-specific publication profiles. Six categories of AD-related information are extracted from the processed publication data: publication trend by year, dementia type occurrence, brain region occurrence, mouse model information, keywords occurrence, and co-occurring genes. A user-friendly web portal is then developed using Django framework to provide gene query functions and data visualizations for the generalized and summarized publication information.

Results By implementing the NLP pipeline, we extracted gene-specific ND-related publication information from the abstracts of the publications in the PubMed database. The results are summarized and visualized through an interactive web query portal. Multiple visualization windows display the ND publication trends, mouse models used, dementia types, involved brain regions, keywords to major AD-related biological processes, and co-occurring genes. Direct links to PubMed sites are provided for all recorded publications on the query result page of the web portal.

Conclusion The resulting portal is a valuable tool and data source for quick querying and displaying AD publications tailored to users’ interested research areas and gene targets, which is especially convenient for users without informatic mining skills. Our study will not only keep AD field researchers updated with the progress of AD research, assist them in conducting preliminary examinations efficiently, but also offers additional support for hypothesis generation and validation which will contribute significantly to the communication, dissimilation and progress of AD research.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • johliu{at}iu.edu, huanmei.wu{at}temple.edu, drobertson{at}indianabiosciences.org, jizhan{at}iu.edu

  • List of Abbreviations

    AD
    Alzheimer’s Disease
    ND
    neurodegenerative disease
    NLP
    natural language processing
    GSPP
    genespecific publication profile
  • Copyright 
    The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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    Posted July 02, 2022.
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    Text mining and portal development for gene-specific publications on Alzheimer’s disease and other neurodegenerative diseases
    Jiannan Liu, Huanmei Wu, Daniel H. Robertson, Jie Zhang
    bioRxiv 2022.06.28.497987; doi: https://doi.org/10.1101/2022.06.28.497987
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    Text mining and portal development for gene-specific publications on Alzheimer’s disease and other neurodegenerative diseases
    Jiannan Liu, Huanmei Wu, Daniel H. Robertson, Jie Zhang
    bioRxiv 2022.06.28.497987; doi: https://doi.org/10.1101/2022.06.28.497987

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