Signal processing for functional analysis of protein mutants.
We present a new technique to predict the functional behaviour of protein mutants using their primary sequence. The amino acid sequences of proteins are used to form biochemical signals. Signal processing techniques are used to extract functionally meaningful measures from these signals. These computational measures are then used to distinguish functional classes of mutant proteins.
College of Information Technology, University of North Carolina at Charlotte, NC 28223, USA. knajaria@uncc.edu
K
K
Najarian
K
K
Gopalakrishnan
R H
RH
Zadeh
D000465:Algorithms; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D004247:DNA / Q000737:chemistry; D004252:DNA Mutational Analysis; D015195:Drug Design; D017709:Fractals; D015972:Gene Expression Regulation, Neoplastic; D005823:Genetics; D006678:HIV / Q000378:metabolism*; D016333:HIV Protease / Q000378:metabolism; D017320:HIV Protease Inhibitors / Q000494:pharmacology; D006801:Humans; D008957:Models, Genetic; D015233:Models, Statistical; D009154:Mutation; D009369:Neoplasms / Q000378:metabolism; D011506:Proteins / Q000737:chemistry*; D015398:Signal Transduction
D017320:HIV Protease Inhibitors; D011506:Proteins; D004247:DNA; D016333:HIV Protease