ArticleBioinformatics advances2025
GenePioneer: a comprehensive Python package for identification of essential genes and modules in cancer.
Article in Bioinformatics advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Authors and funding
2 authors.
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Abstract
Summary: We propose a network-based unsupervised learning model to identify essential cancer genes and modules for 12 different cancer types, supported by a Python package for practical application. The model constructs a gene network from frequently mutated genes and biological processes, ranks genes using topological features, and detects critical modules. Evaluation across cancer types confirms its effectiveness in prioritizing cancer-related genes and uncovering relevant modules. The Python package allows users to input gene lists, retrieve rankings, and identify associated modules. This work provides a robust method for gene prioritization and module detection, along with a user-friendly package to support research and clinical decision-making in cancer genomics. Availability and implementation: GenePioneer is released as an open-source software under the MIT license. The source code is available on GitHub at https://github.com/Golnazthr/ModuleDetection.
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Registered trials
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