Intent Parser: A Tool for Codification and Sharing of Experimental Design

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Abstract

Communicating information about experimental design among a team of collaborators is challenging because different people tend to describe experiments in different ways and with different levels of detail. Sometimes, humans can interpret missing information by making assumptions and drawing inferences from information already provided. Doing so, however, is error-prone and typically requires a high level of interpersonal communication. In this paper, we present a tool that addresses this challenge by providing a simple interface for incremental formal codification of experiment designs. Users interact with a Google Docs word-processing interface with structured tables, backed by assisted linking to machine-readable definitions in a data repository (SynBioHub) and specification of available protocols and requests for execution in the Open Protocol Interface Language (OPIL). The result is an easy-to-use tool for generating machine-readable descriptions of experiment designs with which users in the DARPA SD2 program have collected data from 80 208 samples using a variety of protocols and instruments over the course of 181 experiment runs.

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Nguyen, T., Walczak, N., Sumorok, D., Weston, M., & Beal, J. (2022). Intent Parser: A Tool for Codification and Sharing of Experimental Design. ACS Synthetic Biology, 11(1), 502–507. https://doi.org/10.1021/acssynbio.1c00285

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