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PyGenePlexus: a Python package for gene discovery using network-based machine learning

SUMMARY: PyGenePlexus is a Python package that enables a user to gain insight into any gene set of interest through a molecular interaction network informed supervised machine learning model. PyGenePlexus provides predictions of how associated every gene in the network is to the input gene set, offe...

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Detalles Bibliográficos
Autores principales: Mancuso, Christopher A, Liu, Renming, Krishnan, Arjun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9900208/
https://www.ncbi.nlm.nih.gov/pubmed/36721325
http://dx.doi.org/10.1093/bioinformatics/btad064
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author Mancuso, Christopher A
Liu, Renming
Krishnan, Arjun
author_facet Mancuso, Christopher A
Liu, Renming
Krishnan, Arjun
author_sort Mancuso, Christopher A
collection PubMed
description SUMMARY: PyGenePlexus is a Python package that enables a user to gain insight into any gene set of interest through a molecular interaction network informed supervised machine learning model. PyGenePlexus provides predictions of how associated every gene in the network is to the input gene set, offers interpretability by comparing the model trained on the input gene set to models trained on thousands of known gene sets, and returns the network connectivity of the top predicted genes. AVAILABILITY AND IMPLEMENTATION: https://pypi.org/project/geneplexus/ and https://github.com/krishnanlab/PyGenePlexus. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-99002082023-02-07 PyGenePlexus: a Python package for gene discovery using network-based machine learning Mancuso, Christopher A Liu, Renming Krishnan, Arjun Bioinformatics Applications Note SUMMARY: PyGenePlexus is a Python package that enables a user to gain insight into any gene set of interest through a molecular interaction network informed supervised machine learning model. PyGenePlexus provides predictions of how associated every gene in the network is to the input gene set, offers interpretability by comparing the model trained on the input gene set to models trained on thousands of known gene sets, and returns the network connectivity of the top predicted genes. AVAILABILITY AND IMPLEMENTATION: https://pypi.org/project/geneplexus/ and https://github.com/krishnanlab/PyGenePlexus. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2023-01-31 /pmc/articles/PMC9900208/ /pubmed/36721325 http://dx.doi.org/10.1093/bioinformatics/btad064 Text en © The Author(s) 2023. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Note
Mancuso, Christopher A
Liu, Renming
Krishnan, Arjun
PyGenePlexus: a Python package for gene discovery using network-based machine learning
title PyGenePlexus: a Python package for gene discovery using network-based machine learning
title_full PyGenePlexus: a Python package for gene discovery using network-based machine learning
title_fullStr PyGenePlexus: a Python package for gene discovery using network-based machine learning
title_full_unstemmed PyGenePlexus: a Python package for gene discovery using network-based machine learning
title_short PyGenePlexus: a Python package for gene discovery using network-based machine learning
title_sort pygeneplexus: a python package for gene discovery using network-based machine learning
topic Applications Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9900208/
https://www.ncbi.nlm.nih.gov/pubmed/36721325
http://dx.doi.org/10.1093/bioinformatics/btad064
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