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Environmental Screening of Aeromonas hydrophila, Mycobacterium spp., and Pseudocapillaria tomentosa in Zebrafish Systems
Published on: December 8, 2017
ZooPathWeb: a comprehensive web resource for zoonotic pathogens
Rui-Si Hu1,2, Xin Zhang1,2, Yanming Wei1,3
1Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou, Zhejiang 324003, China.
Motivation:
Zoonotic pathogens, such as viruses, bacteria, fungi and parasites, can be transmitted from animals to humans, causing a wide range of diseases that can vary from mild to life-threatening. These pathogens typically exhibit a broad host range, infecting domestic and/or wild animals, which serve as reservoirs of infection. Human infection can occur through direct contact with infected animals or their body fluids, consumption of contaminated food or water, or via bites from infected arthropod vectors. Understanding the epidemiological characteristics and population structure of zoonotic pathogens is of paramount importance for preventing and controlling the spread of zoonotic diseases.
Results:
Here, we present ZooPathWeb, a comprehensive online resource for zoonotic pathogens. ZooPathWeb provides essential information on pathogens that are particularly relevant to public health and includes a literature collection organized by pathogen classification, such as lineage, host, country or region and publication year. Moreover, we have developed four web-based utility tools for this release: SeqNHandle, PaPhy-ML, TreeView and BLAST. These tools are specifically designed to facilitate the identification of population structure and adaptive evolution in relation to zoonotic pathogens.
Availability And Implementation:
The ZooPathWeb website is accessed via http://lab.malab.cn/~hrs/zoopathweb/. The source code for AKINND, which is used for collecting pathogen-related literature, can be found at https://github.com/RuiSiHu/AKINND. Additionally, the source code for PaPhy-ML, utilized for phylogenetic analysis, can be found at https://github.com/RuiSiHu/PaPhy-ML.
Supplementary Information:
Supplementary data are available at Bioinformatics Advances online.
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