D-LIM: Hypothesis-driven interpretable neural network for interactions between genes

D-LIM [1] enables the automatic modeling of phenotype-fitness maps from the data. This problem is then solved by training a neural network using a PyTorch backend. To learn more about this modeling, please see our manuscript.

[1]

Shuhui W, Alexandre A, Philippe N, Vaitea O. Hypothesis-driven interpretable neural network for interactions between genes (2024). https://doi.org/10.1101/2024.04.09.588719

D-LIM is is provided under an MIT open source license. The documentation provided here is meant to help users quickly get D-LIM working for their own research needs. Please do not hesitate to contact us with any questions or suggestions for improvements. For technical assistance or to report bugs, please contact Shuhui Wang (Email: shuhui.wang@espci.psl.fr).

Table of Contents

• Installation Instructions
• Modeling Tutorials

Links

• Laboratory of Biophysics and Evolution

• MILES (Machine Intelligence and Learning Systems) Lab