CO-19 Pendemic DataBase (CO-19PDB 2.0)

The COVID-19 pandemic is a rapidly changing situation, numbers of databases have been published by computational scientists, each has its own particular issue, such as digital image databases have image info W.S.M. Wold at all: pp. 1732–1767 , genomic databases have genomic updates P. Simmonds at all 1193–1206, etc. In order to access the useful details, we have provided a larger detailed dataset containing only COVID-19 research databases, resources and auto daily notification and record that are nowadays the worldwide issue and have divide into 6 categories based on their internal or external structure, function and activities. Our methods aim to be as comprehensive, systematic and exhaustive how much as possible. The databases listed in this database are chosen to provide covid-19 knowledge to researchers on literature and resources on easy and friendly finding ways. Here, as we have provided access to 123 COVID-19 databases through many ways to search, the user can get the databases information through clicking on the name or by typing the appropriate name in the search query on home page. Further, by clicking on “auto daily updates page” will give global daily notification and record of COVID -19.

Highlights:

1. Development of CO-19 PDB 2.0: This comprehensive database integrates all Covid-19-related data, focusing on the intricate connections between Covid-19 and cancer, and is accessible with a single click and automatic global notifications.

2. Extensive Dataset Organization: CO-19 PDB 2.0 categorizes 120 datasets into six specific areas: chemical structures, digital images, visualization tools, genomics, social sciences, and literature, offering functionalities like image analysis, gene sequencing, and data visualization.

3. User-Friendly Features: The database includes a search page and an auto-notification page, with predefined charts providing insights on cases, deaths, recovery rates, and country-wise distributions, facilitating easy information retrieval.

4. Technological Framework and Up-to-Date Information: Developed using PHP, HTML, CSS, JavaScript, Python, and MySQL, the database ensures up-to-date Covid-19 datasets and global statistics, including the top 10 cancers diagnosed in the US in 2022.

5. Global Collaboration and Impact: Highlighting the extensive collaboration among research institutions, the manuscript notes the significant global impact of Covid-19 on cancer patients and the resulting numerous articles and studies.