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Text mining and portal development for gene-specific publications on Alzheimer’s disease and other neurodegenerative diseases by Jiannan Liu; Huanmei Wu; Daniel H. Robertson; Jie Zhang is a Health Professions article available to read on EtoBox.

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## 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

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Author

Jiannan Liu; Huanmei Wu; Daniel H. Robertson; Jie Zhang

Publisher

BioMed Central

Published

2024

Language

EN

Field

Health Professions (Health Sciences)