10.1038/s41598-019-48746-5 | Papers | Ecosyste.ms: Papers

Papers: 10.1038/s41598-019-48746-5

https://doi.org/10.1038/s41598-019-48746-5

Gene Expression Predicts Histological Severity and Reveals Distinct Molecular Profiles of Nonalcoholic Fatty Liver Disease

Cited by: 93
Author(s): Stephen A. Hoang, Abdul M. Oseini, Ryan E. Feaver, Banumathi K. Cole, Amon Asgharpour, Robert Vincent, Mohammad Shadab Siddiqui, Mark Lawson, Nathan Day, Justin M. Taylor, Brian R. Wamhoff, Faridoddin Mirshahi, Melissa J. Contos, Michael O. Idowu, Arun J. Sanyal
Published: about 7 years ago

Software Mentions 8

bioconductor: GSVA

Gene Set Variation Analysis for microarray and RNA-seq data
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Linear Models for Microarray Data
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bioconductor: STRINGdb

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cran: glmnet

Lasso and Elastic-Net Regularized Generalized Linear Models
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cran: igraph

Network Analysis and Visualization
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pypi: glmnet

Python wrapper for glmnet
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pypi: GSVA

Python CLI and module for running the GSVA R bioconductor package with Python Pandas inputs and outputs.
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pypi: igraph

High performance graph data structures and algorithms
Papers that mentioned: 1,555

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