ANAT 3.0: a framework for elucidating functional protein subnetworks using graph-theoretic and machine learning approaches

L. F. Signorini, T. Almozlino, R. Sharan*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Background: ANAT is a Cytoscape plugin for the inference of functional protein–protein interaction networks in yeast and human. It is a flexible graphical tool for scientists to explore and elucidate the protein–protein interaction pathways of a process under study. Results: Here we present ANAT3.0, which comes with updated PPI network databases of 544,455 (human) and 155,504 (yeast) interactions, and a new machine-learning layer for refined network elucidation. Together they improve network reconstruction to more than twofold increase in the quality of reconstructing known signaling pathways from KEGG. Conclusions: ANAT3.0 includes improved network reconstruction algorithms and more comprehensive protein–protein interaction networks than previous versions. ANAT is available for download on the Cytoscape Appstore and at https://www.cs.tau.ac.il/~bnet/ANAT/.

Original languageEnglish
Article number526
JournalBMC Bioinformatics
Volume22
Issue number1
DOIs
StatePublished - Dec 2021

Keywords

  • Interactomics
  • Machine learning
  • Network biology
  • Network inference
  • Protein–protein interaction networks
  • Systems biology

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