Bi-PSSM: position specific scoring matrix based intelligent computational model for identification of mycobacterial membrane proteins

DOI10.1016/j.jtbi.2017.09.013zbMath1394.92002OpenAlexW2756128645WikidataQ47657811 ScholiaQ47657811MaRDI QIDQ1749056

Muslim Khan, Sher Afzal Khan, Saeed Ahmad, Nadeem Iqbal, Maqsood Hayat

Publication date: 15 May 2018

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

Full work available at URL: https://doi.org/10.1016/j.jtbi.2017.09.013

zbMATH Keywords

SVMPSSMmycobacterium protein

Mathematics Subject Classification ID

Biochemistry, molecular biology (92C40) Computational methods for problems pertaining to biology (92-08)

Related Items (1)

Prediction of aptamer-protein interacting pairs based on sparse autoencoder feature extraction and an ensemble classifier

Uses Software

• Memtype-2L
• pSuc-Lys
• UniProt
• Pse-in-One
• iPro54-PseKNC
• iDrug-Target
• iAMP-2L
• iDNA-Methyl
• iPPBS-Opt
• iSuc-PseOpt
• PseAAC-General
• iCTX-Type
• iACP
• iCar-PseCp
• iPhos-PseEn
• iRNA-AI
• iRNA-PseColl
• iRNA-2methyl
• POSSUM
• iPreny-PseAAC
• iRSpot-EL
• Unb-DPC
• MemHyb
• iTIS-PseKNC
• iRSpot-GAEnsC
• iROS-gPseKNC
• Gneg-mPLoc
• Hum-PLoc
• 2L-piRNA

Cites Work

• pSuc-Lys: predict lysine succinylation sites in proteins with PseAAC and ensemble random forest approach
• 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
• Predicting mycobacterial proteins subcellular locations by incorporating pseudo-average chemical shift into the general form of Chou's pseudo amino acid composition
• The modified Mahalanobis discriminant for predicting outer membrane proteins by using Chou's pseudo amino acid composition
• MemHyb: predicting membrane protein types by hybridizing SAAC and PSSM
• Random forests

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