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

BMC Bioinformatics. 2021 Oct 27;22(1):526. doi: 10.1186/s12859-021-04449-1.

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/ .

Keywords: Interactomics; Machine learning; Network biology; Network inference; Protein–protein interaction networks; Systems biology.

MeSH terms

  • Algorithms
  • Humans
  • Machine Learning
  • Protein Interaction Mapping
  • Protein Interaction Maps
  • Proteins* / genetics
  • Proteins* / metabolism
  • Software*

Substances

  • Proteins