This repository contains curated RNA-MaP (RNA on massively parallel array) datasets from the Eterna project for design of sensors that respond to RNA inputs and also report output through binding RNA.
The data are in the form of a tab-delimited text file with over 600,000 rows.
These were the data used to develop the Ribonet software as described in the manuscript:
Michelle J Wu, Johan OL Andreasson, Wipapat Kladwang, William J Greenleaf, Eterna participants, Rhiju Das (2018), Prospects for recurrent neural network models to learn RNA biophysics from high-throughput data bioRxiv 227611
Further description of the experiments that produced these data are being made available in a manuscript:
Christian Choe, Johan O. L. Andreasson, Feriel Melaine, Wipapat Kladwang, Michelle J. Wu, Fernando Portela, Roger Wellington-Oguri, John J. Nicol, Hannah K. Wayment-Steele, Michael Gotrik, Eterna Participants, Purvesh Khatri, William J. Greenleaf, Rhiju Das (2023) Rationally designed RNA sensors that compute increasingly complex functions of multiple inputs.
with a different separation of the data available at the paper-data-rationally-designed-RNA-sensor repository associated with the paper figures.