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PARM: A genetic evolved algorithm to predict bioactivity
Alternative TitleJ. Chem. Inf. Comput. Sci.
Chen, HM; Zhou, JJ; Xie, GR
1998-03-01
Source PublicationJOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES
ISSN0095-2338
Volume38Issue:2Pages:243-250
AbstractBased on Waiters' GERM (Genetic Evolved Receptor Model) algorithm, an improved algorithm FARM (Pseudo Atomic Receptor Model) was put forward. PARM uses a combination of a genetic algorithm and a cross-validation technique to produce an atomic-level pseudoreceptor model, based on a set of known structure-activity relationships. During the genetic process, an artificial interfering method, which is based on a complementary principle of ligand-receptor interaction, was used to accelerate the search speed. The evolved models show a high correlation between intermolecular energy and bioactivity and can predict the bioactivity of an unknown molecule by interpolating in the regression equation of the structure-activity relationship. This algorithm was applied to two systems and produced reasonable results.; Based on Waiters' GERM (Genetic Evolved Receptor Model) algorithm, an improved algorithm FARM (Pseudo Atomic Receptor Model) was put forward. PARM uses a combination of a genetic algorithm and a cross-validation technique to produce an atomic-level pseudoreceptor model, based on a set of known structure-activity relationships. During the genetic process, an artificial interfering method, which is based on a complementary principle of ligand-receptor interaction, was used to accelerate the search speed. The evolved models show a high correlation between intermolecular energy and bioactivity and can predict the bioactivity of an unknown molecule by interpolating in the regression equation of the structure-activity relationship. This algorithm was applied to two systems and produced reasonable results.
KeywordConstruction Design Models
SubtypeArticle
WOS HeadingsScience & Technology ; Physical Sciences ; Technology
URL查看原文
Indexed BySCI
Language英语
WOS KeywordCONSTRUCTION ; DESIGN ; MODELS
WOS Research AreaChemistry ; Computer Science
WOS SubjectChemistry, Multidisciplinary ; Computer Science, Information Systems ; Computer Science, Interdisciplinary Applications
WOS IDWOS:000072740500017
Citation statistics
Cited Times:45[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Version出版稿
Identifierhttp://ir.ipe.ac.cn/handle/122111/6012
Collection研究所(批量导入)
AffiliationChinese Acad Sci, Lab Comp Chem, Inst Chem Met, Beijing 100080, Peoples R China
Recommended Citation
GB/T 7714
Chen, HM,Zhou, JJ,Xie, GR. PARM: A genetic evolved algorithm to predict bioactivity[J]. JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES,1998,38(2):243-250.
APA Chen, HM,Zhou, JJ,&Xie, GR.(1998).PARM: A genetic evolved algorithm to predict bioactivity.JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES,38(2),243-250.
MLA Chen, HM,et al."PARM: A genetic evolved algorithm to predict bioactivity".JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES 38.2(1998):243-250.
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