SPrenylC-PseAAC: a sequence-based model developed via Chou's 5-steps rule and general PseAAC for identifying S-prenylation sites in proteins
type: Item
instance of: scholarly article
title: SPrenylC-PseAAC: a sequence-based model developed via Chou's 5-steps rule and general PseAAC for identifying S-prenylation sites in proteins
zbMATH Open document ID: 1411.92233
author: Waqar Hussain
author: Yaser Daanial Khan
author: Nouman Rasool
author: Sher Afzal Khan
author: Kuo-Chen Chou
published in: Journal of Theoretical Biology
publication date: 2019-03-27T00:00:00Z
Mathematics Subject Classification ID: 92D20
Mathematics Subject Classification ID: 68T05
Mathematics Subject Classification ID: 62P10
zbMATH DE Number: 7043030
zbMATH Keywords: S-prenylation
zbMATH Keywords: S-prenyl cysteine
zbMATH Keywords: PseAAC
zbMATH Keywords: 5-step rule
zbMATH Keywords: statistical moments
zbMATH Keywords: prediction
describes a project that uses: iPTM-mLys
describes a project that uses: iACP
describes a project that uses: iLoc-Plant
describes a project that uses: iHyd-PseAAC
describes a project that uses: Euk-PLoc
describes a project that uses: iDNA-Prot
describes a project that uses: iEnhancer-2L
describes a project that uses: iPro54-PseKNC
describes a project that uses: iRSpot-TNCPseAAC
describes a project that uses: iAMP-2L
describes a project that uses: iLoc-Virus
describes a project that uses: iMethyl-PseAAC
describes a project that uses: iOri-Human
describes a project that uses: iPhos-PseEvo
describes a project that uses: iPhos-PseEn
describes a project that uses: iRNA-AI
describes a project that uses: pLoc-mAnimal
describes a project that uses: iPreny-PseAAC
describes a project that uses: iRNA-2methyl
describes a project that uses: iRNAm5C-PseDNC
describes a project that uses: iPromoter-2L
describes a project that uses: iProt-Sub
describes a project that uses: iRNA-PseU
describes a project that uses: Fu-SulfPred
describes a project that uses: iHyd-PseCp
describes a project that uses: iROS-gPseKNC
describes a project that uses: PredLactamase
describes a project that uses: propy
describes a project that uses: Pse-in-One
describes a project that uses: iLoc-Hum
describes a project that uses: iLoc-Animal
describes a project that uses: iSNO-AAPair
describes a project that uses: iNitro-Tyr
describes a project that uses: pLoc-mEuk
describes a project that uses: iRNA-PseColl
describes a project that uses: pLoc-mVirus
describes a project that uses: iRSpot-EL
describes a project that uses: DPP-PseAAC
describes a project that uses: pLoc-mPlant
describes a project that uses: Signal-3L
describes a project that uses: iDNA6mA-PseKNC
describes a project that uses: iPPI-PseAAC
describes a project that uses: 2L-piRNA
describes a project that uses: iUbiq-Lys
describes a project that uses: pLoc_bal-mHum
describes a project that uses: BlaPred
describes a project that uses: pSuc-Lys
describes a project that uses: PREvaIL
Wikidata QID: Q91623056
MaRDI profile type: Publication
full work available at URL: j.jtbi.2019.02.007
OpenAlex ID: W2915008530
cites work: iMethyl-STTNC: identification of N\(^6\)-methyladenosine sites by extending the idea of SAAC into Chou's PseAAC to formulate RNA sequences
cites work: IMem-2LSAAC: a two-level model for discrimination of membrane proteins and their types by extending the notion of SAAC into Chou's pseudo amino acid composition
cites work: Some remarks on protein attribute prediction and pseudo amino acid composition
cites work: pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC
cites work: Predicting structural classes of proteins by incorporating their global and local physicochemical and conformational properties into general Chou's PseAAC
cites work: Gram-positive and Gram-negative protein subcellular localization by incorporating evolutionary-based descriptors into Chou's general PseAAC
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cites work: Identifying 5-methylcytosine sites in RNA sequence using composite encoding feature into Chou's PseKNC

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cites work: Predicting membrane protein types by incorporating a novel feature set into Chou's general PseAAC

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cites work: BlaPred: predicting and classifying \(\beta\)-lactamase using a 3-tier prediction system via Chou's general PseAAC

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cites work: Fu-SulfPred: identification of protein S-sulfenylation sites by fusing forests via Chou's general PseAAC

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cites work: \textbf{iLoc-Virus}: a multi-label learning classifier for identifying the subcellular localization of virus proteins with both single and multiple sites

SPrenylC-PseAAC: a sequence-based model developed via Chou's 5-steps rule and general PseAAC for identifying S-prenylation sites in proteins (cites work)
cites work: Predicting apoptosis protein subcellular localization by integrating auto-cross correlation and PSSM into Chou's PseAAC

SPrenylC-PseAAC: a sequence-based model developed via Chou's 5-steps rule and general PseAAC for identifying S-prenylation sites in proteins (cites work)
cites work: Prediction of protein subcellular localization with oversampling approach and Chou's general PseAAC

SPrenylC-PseAAC: a sequence-based model developed via Chou's 5-steps rule and general PseAAC for identifying S-prenylation sites in proteins (DOI)
DOI: 10.1016/J.JTBI.2019.02.007

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