Protein Classification Based on Propagation of Unrooted Binary Trees

Andras      Kocsor; Robert      Busa-Fekete; Sandor      Pongor

doi:10.2174/092986608784567492

Abstract

We present two efficient network propagation algorithms that operate on a binary tree, i.e., a sparse-edged substitute of an entire similarity network. TreeProp-N is based on passing increments between nodes while TreeProp-E employs propagation to the edges of the tree. Both algorithms improve protein classification efficiency.

Keywords: Propagation algorithm, PageRank, protein classification, ROC analysis, phylogenomics

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Protein & Peptide Letters

Title: Protein Classification Based on Propagation of Unrooted Binary Trees

Volume: 15 Issue: 5

Author(s): Andras Kocsor, Robert Busa-Fekete and Sandor Pongor

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Keywords: Propagation algorithm, PageRank, protein classification, ROC analysis, phylogenomics

Abstract: We present two efficient network propagation algorithms that operate on a binary tree, i.e., a sparse-edged substitute of an entire similarity network. TreeProp-N is based on passing increments between nodes while TreeProp-E employs propagation to the edges of the tree. Both algorithms improve protein classification efficiency.

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Kocsor Andras, Busa-Fekete Robert and Pongor Sandor, Protein Classification Based on Propagation of Unrooted Binary Trees, Protein & Peptide Letters 2008; 15 (5) . https://dx.doi.org/10.2174/092986608784567492