Example using miR-125a maturation efficiency data

The data used in this guide along with the necessary Python scripts can be found in the dynasigml_mir125a_example GitHub repository. You can clone it with this command:

git clone https://github.com/gregorpatof/dynasigml_mir125a_example

The miR-125a maturation efficiency data come from Fang & Bartel (https://doi.org/10.1016/j.molcel.2015.08.015) and have been explored thoroughly in previous work (https://doi.org/10.1371/journal.pcbi.1010777). The maturation efficiencies of over 50k miR-125a sequence variants have been measured using an enzymatic assay.

Here are the necessary steps to run DynaSig-ML on the miR-125a data:

• Generating mutations
• Computing Dynamical Signatures
• Running and saving the machine learning models
• Performance analysis
• Mapping LASSO coefficients on the structure
• Making new predictions
• Running in parallel