Prediction of GPCRs with Pseudo Amino Acid Composition: Employing Composite Features and Grey Incidence Degree Based Classification
Keywords: BLAST & FASTA; Bayes network method; Chemokine; Frizzled & Smoothened receptors family; G-protein coupled receptor; GPCRs prediction; Hidden Markov models; Hybrid combination; Mathew's Selective Top Down method; Power spectral density; PseAAC; Rhodopsin; amino acids; fast fourier transforms; grey incidence degree measure; nearest neighbor classifier; principle component analysis; pseudo amino acid composition; quaternary structural classes; signal peptides; split amino acid
Document Type: Research Article
Publication date: 2011-09-01
- Protein & Peptide Letters publishes short papers in all important aspects of protein and peptide research, including structural studies, recombinant expression, function, synthesis, enzymology, immunology, molecular modeling, drug design etc. Manuscripts must have a significant element of novelty, timeliness and urgency that merit rapid publication. Reports of crystallisation, and preliminary structure determinations of biologically important proteins are acceptable. Purely theoretical papers are also acceptable provided they provide new insight into the principles of protein/peptide structure and function.