SPrenylC-PseAAC: a sequence-based model developed via Chou's 5-steps rule and general PseAAC for identifying S-prenylation sites in proteins
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Publication:1734238
DOI10.1016/j.jtbi.2019.02.007zbMath1411.92233OpenAlexW2915008530WikidataQ91623056 ScholiaQ91623056MaRDI QIDQ1734238
Yaser Daanial Khan, Sher Afzal Khan, Kuo-Chen Chou, Nouman Rasool, Waqar Hussain
Publication date: 27 March 2019
Published in: Journal of Theoretical Biology (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jtbi.2019.02.007
Applications of statistics to biology and medical sciences; meta analysis (62P10) Learning and adaptive systems in artificial intelligence (68T05) Protein sequences, DNA sequences (92D20)
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Uses Software
- PredLactamase
- pSuc-Lys
- iEnhancer-2L
- propy
- Pse-in-One
- iDNA-Prot
- iPro54-PseKNC
- iRSpot-TNCPseAAC
- iAMP-2L
- iLoc-Virus
- iLoc-Plant
- Euk-PLoc
- iLoc-Animal
- iLoc-Hum
- iMethyl-PseAAC
- iSNO-AAPair
- iNitro-Tyr
- iPTM-mLys
- iACP
- iHyd-PseCp
- iPhos-PseEvo
- iPhos-PseEn
- iOri-Human
- iRNA-AI
- pLoc-mAnimal
- pLoc-mVirus
- pLoc-mEuk
- iRNA-PseColl
- iRNA-2methyl
- iRNAm5C-PseDNC
- iPreny-PseAAC
- DPP-PseAAC
- iRSpot-EL
- iPromoter-2L
- PREvaIL
- pLoc-mPlant
- iROS-gPseKNC
- Signal-3L
- iProt-Sub
- iRNA-PseU
- pLoc_bal-mHum
- iDNA6mA-PseKNC
- iPPI-PseAAC
- 2L-piRNA
- iUbiq-Lys
- iHyd-PseAAC
- BlaPred
- Fu-SulfPred
Cites Work
- pSuc-Lys: predict lysine succinylation sites in proteins with PseAAC and ensemble random forest approach
- Naïve Bayes classifier with feature selection to identify phage virion proteins
- Prediction of protein structure classes by incorporating different protein descriptors into general Chou's pseudo amino acid composition
- Predicting protein submitochondrial locations by incorporating the pseudo-position specific scoring matrix into the general Chou's pseudo-amino acid composition
- Identifying 5-methylcytosine sites in RNA sequence using composite encoding feature into Chou's PseKNC
- 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
- Some remarks on protein attribute prediction and pseudo amino acid composition
- BlaPred: predicting and classifying \(\beta\)-lactamase using a 3-tier prediction system via Chou's general PseAAC
- Predicting apoptosis protein subcellular localization by integrating auto-cross correlation and PSSM into Chou's PseAAC
- pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC
- Identify Gram-negative bacterial secreted protein types by incorporating different modes of PSSM into Chou's general PseAAC via Kullback-Leibler divergence
- Predicting structural classes of proteins by incorporating their global and local physicochemical and conformational properties into general Chou's PseAAC
- iMethyl-STTNC: identification of N\(^6\)-methyladenosine sites by extending the idea of SAAC into Chou's PseAAC to formulate RNA sequences
- Predicting membrane protein types by incorporating a novel feature set into Chou's general PseAAC
- Analysis and prediction of ion channel inhibitors by using feature selection and Chou's general pseudo amino acid composition
- iPPI-PseAAC(CGR): identify protein-protein interactions by incorporating chaos game representation into PseAAC
- Fu-SulfPred: identification of protein S-sulfenylation sites by fusing forests via Chou's general PseAAC
- pSSbond-PseAAC: prediction of disulfide bonding sites by integration of PseAAC and statistical moments
- Prediction of protein subcellular localization with oversampling approach and Chou's general PseAAC
- \textbf{iLoc-Virus}: a multi-label learning classifier for identifying the subcellular localization of virus proteins with both single and multiple sites
- Prediction of \(\beta\)-lactamase and its class by Chou's pseudo-amino acid composition and support vector machine
- Gram-positive and Gram-negative protein subcellular localization by incorporating evolutionary-based descriptors into Chou's general PseAAC
- Chou's pseudo amino acid composition improves sequence-based antifreeze protein prediction
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