NetMedPy: a Python package for large-scale network medicine screening

Andres Aldana, Michael Sebek, Gordana Ispirova, Rodrigo Dorantes-Gilardi, Joseph Loscalzo, Albert László Barabási, Giulia Menichetti*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract (may include machine translation)

Summary: Network medicine leverages the quantification of information flow within sub-cellular networks to elucidate disease etiology and comorbidity, as well as to predict drug efficacy and identify potential therapeutic targets. However, current Network Medicine toolsets often lack computationally efficient data processing pipelines that support diverse scoring functions, network distance metrics, and null models. These limitations hamper their application in large-scale molecular screening, hypothesis testing, and ensemble modeling. To address these challenges, we introduce NetMedPy, a highly efficient and versatile computational package designed for comprehensive Network Medicine analyses. Availability and implementation: NetMedPy is an open-source Python package under an MIT license. Source code, documentation, and installation instructions can be downloaded from https://github.com/menicgiulia/NetMedPy and https://pypi.org/project/NetMedPy. The package can run on any standard desktop computer or computing cluster.

Original languageEnglish
Article numberbtaf338
Number of pages5
JournalBioinformatics
Volume41
Issue number9
DOIs
StatePublished - Sep 2025
Externally publishedYes

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