Initial Architecture: Building the System Blueprint
We studied outstanding past wiki examples from various institutions to determine the content for our homepage sections. Based on our project's specific characteristics and requirements, we selected the Flask framework to build the wiki's backend. Concurrently, we completed the requirement analysis and team role assignments, laying a solid foundation for development.
Core Development: Advancement and First-Round Testing
We completed the initial front-end web design according to established artistic guidelines and defined the development direction for our dedicated results display page. We split into front-end and back-end development groups to collaboratively build the web pages and debug the API integrations. Based on testing feedback, we iteratively optimized functional defects while enhancing the visual appeal of the content to ensure core functionalities were initially operational.
System Integration: Model Integration and Cloud Deployment
We completed the integration of the protein prediction model with the database, replacing the demo modules. We addressed core issues such as sequence processing efficiency and acquired knowledge about cloud servers. We then configured the server environment to achieve stable cloud-based operation of our website.
Functional Upgrades: Detail Optimization and Visualization
We iteratively fixed minor bugs and refined website details. We developed the core function for protein sequence alignment and added new features including a score comparison chart, a feature radar chart, and a scoring function distribution graph. This established a more comprehensive data visualization system to improve the efficiency of data interpretation.
Functional Deepening: Front-End Enhancement and Real Data Adaptation
While waiting for the modeling team to train the scoring function, we focused on front-end beautification. We then replaced the demo data in the visualization modules with real results calculated based on the weights of the scoring function. This achieved the full implementation and validation of all functionalities, successfully meeting all project objectives.