Predicting protein-protein interactions using graph invariants and a neural network

DOI10.1016/J.COMPBIOLCHEM.2011.03.003zbMath1403.92072DBLPjournals/candc/KnisleyK11OpenAlexW1973634147WikidataQ46983448 ScholiaQ46983448MaRDI QIDQ1629378

Debra J. Knisley, Jeff Knisley

Publication date: 11 December 2018

Published in: Computational Biology and Chemistry (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.compbiolchem.2011.03.003

zbMATH Keywords

machine learninggraph-theoretic modelprotein-protein interactions

Mathematics Subject Classification ID

Applications of graph theory (05C90) Learning and adaptive systems in artificial intelligence (68T05) Biochemistry, molecular biology (92C40)

Related Items (1)

The \(\rho\)-moments of vertex-weighted graphs

Uses Software

• rattle
• AAindex

Cites Work

• ARTIFICIAL NEURAL NETWORKS FOR DATA MINING AND FEATURE EXTRACTION
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item

This page was built for publication: Predicting protein-protein interactions using graph invariants and a neural network