International Life Science Database – development & maintenance of a research focused system

Client Overview

Our client is an international research society in the field of life science. Their members include the leading Universities and life science companies in North America, Europe, and rest of the world. The society occupies a prominent position in the sector with a vast network of scientists and researchers who collaborate through it. They maintain various publications and organise several conferences throughout the year.

Problem / The Ask

The society is the custodian of information relating to specific types of proteins and responsible for maintaining reference information for each of the different categories. There is a vast amount of information including protein structures, chemical composition, 3D models and other associated parameters. This information is referenced regularly by hundreds of researchers throughout the world.

The society had developed a basic system for maintaining this information; however, with the demands of the modern working environment and collaboration, there was a need to modernise it and improve accessibility. iGen43 has been awarded the contract to maintain the existing bacterial protein database and enhance the system design for improved features and potential introduction of advanced capabilities including Artificial Intelligence.

Our Process

iGen43 put together a team of skilled software developers and architects to create a reliable development, testing, staging and release environment for the client to mature the development and deployment process. The team initially focused on replicating the as-is features of the application using the Python/Django framework whilst also creating a completely new deployment model that would introduce significantly better security and reliability. Technologies such as Digital Ocean and Docker were explored, and a future state deployment architecture was designed.

The team has since then taken the opportunity to refactor the original code and introduce significant improvements, including critical fixes to the previous codebase, that will enable better processing and visualisation of the database contents. With these improvements, the system is benefitting from improved availability and security.

The team is further engaged in experimental design to target potential improvements using artificial intelligence techniques.

Key Metrics

The open application accessible by general public is now running on a stable platform with significantly better stability and maintainability. The process and quality have improved substantially with the introduction of agile development. Further work is being undertaken to increase the performance and security of the system along with enhancements to the core protein database storage and visualisation capabilities.

Arnab Dutta, Director – Digital & AI at iGen43 said: “This is a prestigious project for igen43 as we have an opportunity to collaborate with some of the most advanced research work happening in the field of life sciences. There is a significant potential for AI and ML techniques to enhance the research process and we are excited to contribute to a global research society.”