THE DEVELOPMENT OF MODIFIED ALGORITHM BASED ON COOPERATIVE PARTICLE SWARM OPTIMIZATION, ARTIFICIAL IMMUNE SYSTEMS AND ONTOLOGICAL APPROACH

Authors

  • Г. А. Самигулина Institute of Information and Computational TechnologiesCS MES RK
  • Ж. А. Масимканова Al-Farabi Kazakh National University
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Keywords:

Smart-technology forforecasting, «structure-property/activity» relationship (QSAR), cooperative particle swarm optimization, artificial immune systems, OWLmodel, drugs

Abstract

The article is devoted to the development of modified algorithm based on coopera-
tive particle swarm optimization and artificial immune systems for forecastingquantitative «struc-
ture-property/activity» relationship (QSAR) of medicinal compounds. The construction of an opti-
mal set of descriptors has been performed on the basis of a cooperative particle swarm optimization
algorithm.Pattern recognition and prognosis of candidatemolecules of drugs has been carried out
using artificial immune systems (AIS).The developed modified algorithm allows to reduce learning
time of AIS and improve forecasting accuracy due to the constructed optimal data set. For systema-
tization data and simplification of creating softwarethe OWL model of cooperative particle swarm
optimizationhas been built in Protégé ontology editor. The simulation results using the sulfonamide
database are given.

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How to Cite

Самигулина, Г. А., & Масимканова, Ж. А. (2023). THE DEVELOPMENT OF MODIFIED ALGORITHM BASED ON COOPERATIVE PARTICLE SWARM OPTIMIZATION, ARTIFICIAL IMMUNE SYSTEMS AND ONTOLOGICAL APPROACH. THE JOURNAL OF THE OPEN SYSTEMS EVOLUTION PROBLEMS, 21(1-2), 77–83. Retrieved from https://peos.kaznu.kz/index.php/peos/article/view/260

Issue

Vol. 21 No. 1-2 (2019): ЖУРНАЛ ПРОБЛЕМ ЭВОЛЮЦИИ ОТКРЫТЫХ СИСТЕМ

Section

ФИЗИКА