Elman RNN based classification of proteins sequences on account of their mutual information

DOI10.1016/J.JTBI.2012.06.039zbMath1337.92161OpenAlexW2078465348WikidataQ84595940 ScholiaQ84595940MaRDI QIDQ293734

Paras Nath Pandey, Pooja Mishra

Publication date: 9 June 2016

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

Full work available at URL: https://doi.org/10.1016/j.jtbi.2012.06.039

zbMATH Keywords

information-theoryMIVsolvent accessibility

Mathematics Subject Classification ID

Protein sequences, DNA sequences (92D20) Measures of information, entropy (94A17)

Uses Software

• Cell-PLoc
• ProtIdent
• GPCR-2L
• iDNA-Prot
• iLoc-Gpos
• iLoc-Plant
• iLoc-Hum
• iLoc-Euk
• Plant-mPLoc
• Pfam
• Signal-CF
• Euk-mPLoc
• iNR-PhysChem
• NR-2L
• PRMLT

Cites Work

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• On the syntactic structure of protein sequences and the concept of grammar complexity
• Use of fuzzy clustering technique and matrices to classify amino acids and its impact to Chou's pseudo amino acid composition
• Some remarks on protein attribute prediction and pseudo amino acid composition
• Using the concept of Chou's pseudo amino acid composition for risk type prediction of human papillomaviruses
• Prediction of GABA\(_{\mathrm A}\) receptor proteins using the concept of Chou's pseudo-amino acid composition and support vector machine

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