Netrank: network-based approach for biomarker discovery.

Ali Al-FatlawiEka RusadzeAlexander ShmelkinNegin MalekianCigdem OzenChristian PilarskyMichael Schroeder

Published in: BMC bioinformatics (2023)

In this paper we provide a fast and efficient implementation of NetRank, with a case study from The Cancer Genome Atlas, to assess the performance. We incorporated complete functionality for pre and post-processing for RNA-seq gene expression data with functions for building protein-protein interaction networks. The source code of NetRank is freely available (at github.com/Alfatlawi/Omics-NetRank) with an installable R library. We also deliver a comprehensive practical user manual with examples and data attached to this paper.

Keyphrases

single cell
rna seq
protein protein
small molecule
gene expression
high throughput
electronic health record
big data
primary care
papillary thyroid
healthcare
machine learning
quality improvement
genome wide
young adults
artificial intelligence
lymph node metastasis