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Title: GitHub - MLDataAnalytics/pNet: pNet is a Python package for computing personalized, sparse, non-negative large-scale functional networks from functional magnetic resonance imaging (fMRI) data, particularly resting state fMRI data.

Open Graph Title: GitHub - MLDataAnalytics/pNet: pNet is a Python package for computing personalized, sparse, non-negative large-scale functional networks from functional magnetic resonance imaging (fMRI) data, particularly resting state fMRI data.

X Title: GitHub - MLDataAnalytics/pNet: pNet is a Python package for computing personalized, sparse, non-negative large-scale functional networks from functional magnetic resonance imaging (fMRI) data, particularly resting state fMRI data.

Description: pNet is a Python package for computing personalized, sparse, non-negative large-scale functional networks from functional magnetic resonance imaging (fMRI) data, particularly resting state fMRI data. - MLDataAnalytics/pNet

Open Graph Description: pNet is a Python package for computing personalized, sparse, non-negative large-scale functional networks from functional magnetic resonance imaging (fMRI) data, particularly resting state fMRI dat...

X Description: pNet is a Python package for computing personalized, sparse, non-negative large-scale functional networks from functional magnetic resonance imaging (fMRI) data, particularly resting state fMRI dat...

Opengraph URL: https://github.com/MLDataAnalytics/pNet

X: @github

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https://patch-diff.githubusercontent.com/MLDataAnalytics/pNet#pnet-personalized-sparse-functional-network-estimation-for-fmri-data
https://github.com/MLDataAnalytics/pNet
https://pubmed.ncbi.nlm.nih.gov/28483721
https://pubmed.ncbi.nlm.nih.gov/32078800
https://pubmed.ncbi.nlm.nih.gov/36706636
https://www.biorxiv.org/content/10.1101/2025.04.07.647618v1.abstract
https://patch-diff.githubusercontent.com/MLDataAnalytics/pNet#-whats-new
individualized multi-scale hierarchical brain functional networkshttps://www.biorxiv.org/content/10.1101/2025.04.07.647618v1.abstract
https://patch-diff.githubusercontent.com/MLDataAnalytics/pNet#-docker-support
https://patch-diff.githubusercontent.com/MLDataAnalytics/pNet#-cpu-version
https://patch-diff.githubusercontent.com/MLDataAnalytics/pNet#-gpu-version-cuda-enabled
./Hierarchical-FNs/README.mdhttps://github.com/MLDataAnalytics/pNet/blob/main/Hierarchical-FNs/README.md
https://patch-diff.githubusercontent.com/MLDataAnalytics/pNet#-why-pnet-unveiling-individual-brain-topography
https://patch-diff.githubusercontent.com/MLDataAnalytics/pNet#️-key-features--quality-control
pNethttps://github.com/MLDataAnalytics/pNet
https://patch-diff.githubusercontent.com/MLDataAnalytics/pNet#pnet
algorithmhttps://pubmed.ncbi.nlm.nih.gov/28483721
functional topographyhttps://pubmed.ncbi.nlm.nih.gov/32078800
quality controlhttps://pubmed.ncbi.nlm.nih.gov/36706636
algorithmhttps://pubmed.ncbi.nlm.nih.gov/28483721
individual variation in functional topography of association networks in youthhttps://pubmed.ncbi.nlm.nih.gov/32078800
functional network topography of psychopathology in youthhttps://pubmed.ncbi.nlm.nih.gov/35927072
sex differences in the functional topography of association networks in youthhttps://pubmed.ncbi.nlm.nih.gov/35939696
Reproducible Sex Differences in Personalized Functional Network Topography in Youthhttps://www.biorxiv.org/content/10.1101/2024.09.26.615061v1
dissociable multi-scale patterns of development in personalized brain networkshttps://pubmed.ncbi.nlm.nih.gov/35551181
multiscale functional connectivity patterns of the aging brainhttps://pubmed.ncbi.nlm.nih.gov/36731813
personalized functional brain network topography in youth cognitionhttps://pubmed.ncbi.nlm.nih.gov/38110396
Polygenic Risk Underlies Youth Psychopathology and Personalized Functional Brain Network Topographyhttps://www.medrxiv.org/content/10.1101/2024.09.20.24314007v2
individualized multi-scale hierarchical brain functional networkshttps://www.biorxiv.org/content/10.1101/2025.04.07.647618v1.abstract
https://github.com/MLDataAnalytics/pNet/blob/main/assets/pNet.png
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Mapping individualized multi-scale hierarchical brain functional networks from fMRI by self-supervised deep learninghttps://doi.org/10.1101/2025.04.07.647618
Large-scale sparse functional networks from resting state fMRIhttps://pubmed.ncbi.nlm.nih.gov/28483721/
Identification of subject-specific brain functional networks using a collaborative sparse nonnegative matrix decomposition methodhttps://doi.org/10.1109/ISBI.2016.7493430
Identification of Multi-scale Hierarchical Brain Functional Networks Using Deep Matrix Factorizationhttps://doi.org/10.1007/978-3-030-00931-1_26
Individual Variation in Functional Topography of Association Networks in Youthhttps://pubmed.ncbi.nlm.nih.gov/32078800/
Dissociable multi-scale patterns of development in personalized brain networkshttps://pubmed.ncbi.nlm.nih.gov/35551181/
Linking Individual Differences in Personalized Functional Network Topography to Psychopathology in Youthhttps://pubmed.ncbi.nlm.nih.gov/35927072/
Sex differences in the functional topography of association networks in youthhttps://pubmed.ncbi.nlm.nih.gov/35939696/
Personalized functional brain network topography is associated with individual differences in youth cognitionhttps://pubmed.ncbi.nlm.nih.gov/38110396/
Multiscale functional connectivity patterns of the aging brain learned from harmonized rsfMRI data of the multi-cohort iSTAGING studyhttps://pubmed.ncbi.nlm.nih.gov/36731813/
Computing personalized brain functional networks from fMRI using self-supervised deep learninghttps://pubmed.ncbi.nlm.nih.gov/36706636/
Reproducible sex differences in personalised functional network topography in youthhttps://doi.org/10.1192/bjp.2025.135
Polygenic Risk, Psychopathology, and Personalized Functional Brain Network Topography in Adolescencehttps://doi.org/10.1001/jamapsychiatry.2025.1258
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