Data and code for "A Thermodynamically Favoured Molecular Computer: Robust, Fast, Renewable, Scalable"

A Thermodynamically Favoured Molecular Computer: Robust, Fast, Renewable, Scalable Authors: Tristan Stérin, Abeer Eshra, Janet Adio, Constantine G. Evans, Damien Woods This archive contains all the data and code related to the manuscript *A Thermodynamically Favoured Molecular Computer: Robust, Fast, Renewable, Scalable*. This archive version (v1) is for the first Bioarxiv version of the manuscript. See each folder of the archive for detailed instructions. Note that, in general, code needs to be run on a Unix-like (Mac OS or Linux) system; for Windows, however, WSL2 may be usable. Folders contain: `0_DNA_sequence_design_code`: source code used to generate the DNA sequences for the DNA implementation of our SDC system. `1_thermodynamic_analysis_code`: source code used to analyse theoretical thermodynamic properties of the SDC system. `2_raw_qpcr_data`: all of the raw qPCR machine data of the project (only type of data that we use) acquired using several QuantStudio 5 machines (Applied Biosystems). `3_data_plotting_code`: code used to generate all plots shown in the paper. `4_data_analysis_code`: code used to generate all metrics reported in the paper. `5_scaleup_code_modelling_and_analysis`: code analysing the sequence energetics, kinetics, and sink structure (for ADDITION) of scaled-up systems (11-domain and 25-domain scaffold). `6_scaleup_data_and_code`: qPCR machine data, Echo picklists, and temperature protocols for scaled-up (length 11 and 25) systems, as well as code for data analysis and generation of main text Figure 6 and relevant SI plots. `experiments_database.xlsx`: Excel database giving an overview of the pre-scale-up dataset and computed statistics. The file links each experiment to a raw qpcr machine data file, also it contains fields with statistics that were computed using the above code from the data for convenience. Scale-up data and statistics are in `5_scaleup_data_and_code`. Licensing Unless otherwise noted, all code is licensed under the MIT License. Funding Research supported by the European Union’s European Research Council (ERC, Active-DNA, no 772766); European Innovation Council (EIC, DISCO, No 101115422); and Science Foundation Ireland (SFI) under grant numbers 18/ERCS/5746 and 20/FFP-P/8843. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union, European Research Council, European Innovation Council or Science Foundation Ireland. Neither the European Union nor the granting authority can be held responsible for them. The authors declare competing financial interest: listed as inventors on pending patents.