Freezing firefly algorithm for efficient planted (ℓ, d) motif search.
The detection of inimitable patterns (motif) occurring in a set of biological sequences could elevate new biological discoveries. Its application in recognition of transcription factors and their binding sites have demonstrated the necessity to attain knowledge of gene function, human diseases, and...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 60; no. 2; pp. 511 - 531 |
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| Autores principales: | , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Feb2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=154739090&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 154739090 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Feb2022 vid: 60 iid: 2 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 154739090 154633425 154739090 NLM35020123 10.1007/s11517-021-02468-x NLM35020123 154739090 ppf: 511 ppct: 20 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Freezing firefly algorithm for efficient planted (ℓ, d) motif search. aug: au: Theepalakshmi, P. Reddy, U. Srinivasulu affil: Department of Computer Applications, National Institute of Technology, Tiruchirappalli, Tamilnadu, India sug: subj: Algorithms Magnetic Resonance Imaging Freezing Binding Sites Bioinformatics Coping Health Inventory for Parents Clinical Assessment Tools Scales ab: The detection of inimitable patterns (motif) occurring in a set of biological sequences could elevate new biological discoveries. Its application in recognition of transcription factors and their binding sites have demonstrated the necessity to attain knowledge of gene function, human diseases, and drug design. The literature identifies (ℓ, d) motif search as the widely studied problem in PMS (Planted Motif Search). This paper proposes an efficient optimization algorithm named "Freezing FireFly (FFF)" to solve (ℓ, d) motif search problem. The new strategy freezing such as local and global was added to increase the performance of the basic Firefly algorithm. It freezes the best possible out coming positions even in the lesser brighter one. The performance of the proposed algorithm is experienced on simulated and real datasets. The experimental results show that the proposed algorithm resolves the instance (50, 21) within 1.47 min in the simulated dataset. For real (such as ChIP-seq (Chromatin Immunoprecipitation)) and synthetic datasets, the proposed algorithm runs much faster in comparison to existing state-of-the-art optimization algorithms, including Samselect, TraverStringRef, PMS8, qPMS9, AlignACE, FMGA, and GSGA. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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