Preliminary expansion of the resonant recognition model to incorporate multi variable analysis.
The Resonant Recognition Model (rrm) uses digital signal processing methods to investigate protein structure-function; and links the biological function of protein families to unique characteristic frequencies. The rrm originally used a single set of variables: the electron ion interaction potential (EIIP). Here the rrm has been expanded to include 242 sets of variables to analyse a sample of protein families. Despite the evident increase in complexity of the data, distinguishing patterns can be observed between the different protein families. The thus-obtained Signature Profiles (SP) indicate that proteins having similar overall functions may be identifiable and differentiated from others by their characteristic frequency signatures far more readily than with the single variable rrm spectra.
Birch
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Department of Electrical and Computer Systems Engineering, Monash University, Caulfield, Victoria.
West
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Cosic
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D000595:Amino Acid Sequence; D055598:Chemical Phenomena; D002627:Chemistry, Physical; D004563:Electrochemistry; D006454:Hemoglobins / Q000737:chemistry / Q000235:genetics; D006801:Humans; D008956:Models, Chemical; D008969:Molecular Sequence Data; D015394:Molecular Structure; D015999:Multivariate Analysis; D017433:Protein Structure, Secondary; D011506:Proteins / Q000737:chemistry*; D012815:Signal Processing, Computer-Assisted; D013329:Structure-Activity Relationship; D013816:Thermodynamics
D006454:Hemoglobins; D011506:Proteins