Ivy League's Computational Biomedicine Center develops web app for protein data exploration.

Table of contents

Before:

Scientists working with protein data lacked specialized interactive tools and the knowledge to integrate advanced JavaScript or Python solutions, forcing them to manually switch between R and the browser for visualization.

After:

A custom interactive tool with integrated JavaScript, R, and Python replaced the manual process, saving 100+ hours annually, improving research efficiency, and increasing engagement through a 3D renderer.

Business Problem

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Exploratory research is easy with tools like R and Shiny, but lacks highly specialized tools that are domain specific. A group of scientists working with protein data wanted to build an interactive applications but lacked any JavaScript or Python knowledge to integrate state of the art solutions.

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Solution

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We integrated necessary components in JavaScript, R, and Python and released most of the code as open source. This closed the gap of what’s possible through web development and how scientists want to work interactively with R and Python. The solution empowered them to work independently and make their research process faster and easier.

We also created a 3D renderer to increase the attractiveness and attention that protein-related research gets. By creating visualizations that look great we increased how many people want to learn more and how much time they spend learning.

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Impact

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Innovative tool was created and replaced the manual visualization process which involved going back and forth from R to the browser. Removing the manual process saved 100+ hours every year.

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