CO-19 PDB 2.0: A Comprehensive COVID-19 Database with Global Auto-Alerts, Statistical Analysis, and Cancer Correlations.

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Shahid Ullah, Yingmei Li, Wajeeha Rahman, Farhan Ullah, Muhammad Ijaz, Anees Ullah, Gulzar Ahmad, Hameed Ullah, Tianshun Gao
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引用次数: 0

Abstract

Biological databases serve as critical basics for modern research, and amid the dynamic landscape of biology, the COVID-19 database has emerged as an indispensable resource. The global outbreak of Covid-19, commencing in December 2019, necessitates comprehensive databases to unravel the intricate connections between this novel virus and cancer. Despite existing databases, a crucial need persists for a centralized and accessible method to acquire precise information within the research community. The main aim of the work is to develop a database which has all the COVID-19-related data available in just one click with auto global notifications. This gap is addressed by the meticulously designed COVID-19 Pandemic Database (CO-19 PDB 2.0), positioned as a comprehensive resource for researchers navigating the complexities of COVID-19 and cancer. Between December 2019 and June 2024, the CO-19 PDB 2.0 systematically collected and organized 120 datasets into six distinct categories, each catering to specific functionalities. These categories encompass a chemical structure database, a digital image database, a visualization tool database, a genomic database, a social science database, and a literature database. Functionalities range from image analysis and gene sequence information to data visualization and updates on environmental events. CO-19 PDB 2.0 has the option to choose either the search page for the database or the autonotification page, providing a seamless retrieval of information. The dedicated page introduces six predefined charts, providing insights into crucial criteria such as the number of cases and deaths', country-wise distribution, 'new cases and recovery', and rates of death and recovery. The global impact of COVID-19 on cancer patients has led to extensive collaboration among research institutions, producing numerous articles and computational studies published in international journals. A key feature of this initiative is auto daily notifications for standardized information updates. Users can easily navigate based on different categories or use a direct search option. The study offers up-to-date COVID-19 datasets and global statistics on COVID-19 and cancer, highlighting the top 10 cancers diagnosed in the USA in 2022. Breast and prostate cancers are the most common, representing 30% and 26% of new cases, respectively. The initiative also ensures the removal or replacement of dead links, providing a valuable resource for researchers, healthcare professionals, and individuals. The database has been implemented in PHP, HTML, CSS and MySQL and is available freely at https://www.co-19pdb.habdsk.org/. Database URL: https://www.co-19pdb.habdsk.org/.

CO-19 PDB 2.0:具有全局自动预警、统计分析和癌症相关性的 COVID-19 综合数据库。
生物数据库是现代研究的重要基础,在生物学的动态发展中,COVID-19 数据库已成为不可或缺的资源。Covid-19病毒将于2019年12月在全球爆发,因此有必要建立全面的数据库,以揭示这种新型病毒与癌症之间错综复杂的联系。尽管有了现有的数据库,但研究界仍然迫切需要一种集中、易用的方法来获取精确信息。这项工作的主要目的是开发一个数据库,只需点击一下,就能获得所有与 COVID-19 相关的数据,并自动发出全球通知。精心设计的 COVID-19 大流行数据库(COV-19 PDB 2.0)填补了这一空白,该数据库将成为研究人员了解 COVID-19 和癌症复杂性的综合资源。从 2019 年 12 月到 2024 年 6 月,COVID-19 PDB 2.0 系统收集并整理了 120 个数据集,分为六个不同的类别,每个类别都有特定的功能。这些类别包括化学结构数据库、数字图像数据库、可视化工具数据库、基因组数据库、社会科学数据库和文献数据库。功能范围从图像分析和基因序列信息到数据可视化和环境事件更新。CO-19 PDB 2.0 可选择数据库搜索页面或自动识别页面,提供无缝信息检索。专用页面引入了六个预定义图表,提供了对病例和死亡人数、国家分布、"新病例和康复 "以及死亡和康复率等关键标准的深入了解。COVID-19 对癌症患者的全球影响促成了研究机构之间的广泛合作,在国际期刊上发表了大量文章和计算研究。该计划的一个主要特点是每天自动通知标准化信息更新。用户可根据不同类别轻松浏览,或使用直接搜索选项。该研究提供了最新的COVID-19数据集以及有关COVID-19和癌症的全球统计数据,重点介绍了2022年美国诊断出的十大癌症。乳腺癌和前列腺癌最为常见,分别占新病例的30%和26%。该倡议还确保删除或替换死链接,为研究人员、医疗保健专业人员和个人提供宝贵的资源。该数据库采用 PHP、HTML、CSS 和 MySQL 实现,可在 https://www.co-19pdb.habdsk.org/ 免费获取。数据库网址:https://www.co-19pdb.habdsk.org/。
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
CiteScore
7.20
自引率
4.30%
发文量
567
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