CO-19 PDB 2.0

CO-19 PDB 2.0 integrates COVID-19 and cancer-related data into a centralized database with global auto-notifications and statistical analysis for research on COVID-19 and cancer correlations.

Key Features:

• Dataset Organization: Systematically collects and organizes 120 datasets into six distinct categories: chemical structure database, digital image database, visualization tool database, genomic database, social science database, and literature database.
• Global Auto-Notifications: Provides auto daily notifications for standardized information updates on COVID-19 data.
• Statistical Analysis and Visualization: Includes six predefined charts for criteria such as number of cases and deaths, country-wise distribution, new cases and recovery, and rates of death and recovery.
• Cancer Correlation Data: Offers global statistics on COVID-19 and cancer, including data on the top 10 cancers diagnosed in the USA in 2022, with breast cancer representing 30% and prostate cancer 26% of new cases.
• Data Retrieval: Supports category-based navigation and direct search options for seamless information retrieval.
• Link Maintenance: Ensures removal or replacement of dead links to maintain data accessibility.

Scientific Applications:

• COVID-19 and Cancer Research: Serves as a centralized resource for researchers investigating connections between COVID-19 and cancer.
• Chemical Structure Analysis: Provides access to chemical structure databases for COVID-19-related compounds.
• Genomic Research: Supplies gene sequence information through the genomic database category.
• Image Analysis: Supports digital image analysis for COVID-19-related research.
• Data Visualization: Enables visualization of COVID-19 and cancer statistics for research interpretation.
• Environmental and Social Science Research: Includes datasets on environmental events and social science aspects of the pandemic.
• Literature Review: Aggregates published articles and computational studies from international journals on COVID-19 and cancer.

Methodology:

Data were systematically collected and organized between December 2019 and June 2024. The database was implemented in PHP, HTML, CSS, and MySQL.