A Novel Improved Algorithm for Protein Classification Through a Graph Similarity Approach

Hsin Hung Chou, Ching Tien Hsu, Hao Ching Wang, Sun Yuan Hsieh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The protein classification problem is considered in this paper. In the proposed algorithm, we use graphs to represent proteins, whereby every amino acid in a protein corresponds to every vertex in a graph, and the links between the amino acids correspond to the edges between the vertices in the graph. We then classify the proteins according to similarities in their corresponding graph structures.

Original languageEnglish
Title of host publicationIntelligent Computing Theories and Application - 16th International Conference, ICIC 2020, Proceedings
EditorsDe-Shuang Huang, Kang-Hyun Jo
PublisherSpringer Science and Business Media Deutschland GmbH
Pages251-261
Number of pages11
ISBN (Print)9783030608019
DOIs
Publication statusPublished - 2020
Event16th International Conference on Intelligent Computing, ICIC 2020 - Bari , Italy
Duration: Oct 2 2020Oct 5 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12464 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference16th International Conference on Intelligent Computing, ICIC 2020
Country/TerritoryItaly
CityBari
Period10/2/2010/5/20

Keywords

  • B-factor
  • Bioinformatic algorithms
  • Graph similarity
  • Protein classification
  • Protein structures

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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