Identify Gram-negative bacterial secreted protein types by incorporating different modes of PSSM into Chou's general PseAAC via Kullback-Leibler divergence

DOI10.1016/J.JTBI.2018.05.035zbMath1406.92196OpenAlexW2807342250WikidataQ56976900 ScholiaQ56976900MaRDI QIDQ1714132

Yunyun Liang, Sheng-Li Zhang

Publication date: 31 January 2019

Published in: Journal of Theoretical Biology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jtbi.2018.05.035

zbMATH Keywords

nonnegative matrix factorizationsupport vector machinecorrelation analysisposition-specific scoring matrixsecreted proteins

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Biochemistry, molecular biology (92C40) Protein sequences, DNA sequences (92D20)

Related Items (3)

pSSbond-PseAAC: prediction of disulfide bonding sites by integration of PseAAC and statistical moments ⋮ SPrenylC-PseAAC: a sequence-based model developed via Chou's 5-steps rule and general PseAAC for identifying S-prenylation sites in proteins ⋮ iEnhancer-MFGBDT: Identifying enhancers and their strength by fusing multiple features and gradient boosting decision tree

Uses Software

• LIBSVM
• PSI-BLAST
• BLAST
• iEnhancer-2L
• UniProt
• Pse-in-One
• iPPI-Esml
• Prnam-PC
• PseKNC
• iRSpot-PseDNC
• iSNO-AAPair
• iPTM-mLys
• iCar-PseCp
• iPhos-PseEvo
• iRNA-AI
• pLoc-mAnimal
• pLoc-mVirus
• pLoc-mEuk
• iRNA-PseColl
• iATC-mHyb
• iRNAm5C-PseDNC
• POSSUM
• iPreny-PseAAC
• iRSpot-EL
• iPromoter-2L
• pLoc-mGneg
• pLoc-mPlant
• iKcr-PseEns
• Gneg-mPLoc
• AAindex
• iProt-Sub
• pLoc-mHum
• 2L-piRNA

Cites Work

• Unnamed Item
• Some remarks on protein attribute prediction and pseudo amino acid composition
• Gneg-mPLoc: a top-down strategy to enhance the quality of predicting subcellular localization of Gram-negative bacterial proteins
• Prediction of protein subcellular localization with oversampling approach and Chou's general PseAAC
• Predicting mycobacterial proteins subcellular locations by incorporating pseudo-average chemical shift into the general form of Chou's pseudo amino acid composition
• Predicting protein structural class based on multi-features fusion
• Gram-positive and Gram-negative protein subcellular localization by incorporating evolutionary-based descriptors into Chou's general PseAAC
• Learning the parts of objects by non-negative matrix factorization

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