Characterizing the regulatory logic of transcriptional control at the DNA sequence level by ensembles of thermodynamic models
This work reports a toolset for automated production of ensembles of several thousand fits to data, filtering of fits lying within the uncertainty of Drosophila melanogaster even-skipped expression data, and visualization of regulatory mechanisms producing a given expression pattern down to individual binding sites accordingly to available transcription factors.
A pre-configured Docker image to run the application is available on Zenodo (DOI:10.5281/zenodo.16624325), along with the fits files (in the fits folder) used in this work. The main dependencies for the environment configuration are neoParSA, transcpp and Boost library 1.60. The use of the provided Docker image is encouraged.