February 2023 Summaries

Shiru, an Alameda-based company, uses machine learning, bioinformatics, and precision fermentation to create functional, sustainable ingredients for the plant-based industry. As demand grows, Shiru scales its operations to identify new proteins rapidly. The team evaluates thousands of proteins, requiring internal tooling for data analysis, visualization, and collaboration. Superblocks helps build applications to track high-throughput protein screening results across multiple dimensions. This enables lab scientists to quickly analyze protein expression and identify the best candidates for further testing. Shiru's Data Scientists use Superblocks to create user-friendly UIs with frontend drag and drop components connected to backend Snowflake and Postgres databases. The platform supports writing Python directly in the editor, allowing for data manipulation and visualization using libraries like Pandas and Plotly. As a result, Shiru has adopted a data-driven mindset, improving efficiency in understanding key results from screening experiments and moving protein candidates through the testing pipeline.

Superblocks is a programmable IDE that enables developers to create internal applications, workflows, and scheduled jobs in less time and cost. It supports both Python and JavaScript for backend APIs, Workflows, and Scheduled Jobs, as well as browser-based JavaScript functions for frontend Application UIs. Superblocks allows users to write code to query and transform data on the backend, conditionally format data and components displayed on the frontend, and use state variables for caching and re-use of intermediate state across different APIs/Components. It also supports common JavaScript and Python libraries in backend APIs. Applications and Workflows can be shared with individuals or groups via role-based access control, and Superblocks provides audit logs to quickly identify errors and troubleshoot API issues.