Paper Info
Title
Identification of Hot-Spot Locations in Proteins Using Digital Filters
Abstract
A technique for the identification of hot-spot locations in proteins using digital filters is described. In this technique, the characteristic frequency of the protein sequence of interest is first determined from the consensus spectrum of the corresponding functional group. The sequence is then filtered by using a specialized narrowband bandpass digital filter in order to select the characteristic frequency. The energy of the filtered output reveals the hot-spot locations. Zero-phase filtering is used to eliminate the need of computing the phase response of the digital filter. The technique has a unique advantage over existing computational hot-spot location techniques in that it identifies the hot-spot locations solely from the amino-acid sequence of a protein, which is usually the only information initially available for a newly discovered protein molecule. This paper deals also with a MATLAB implementation of the technique that incorporates a user-friendly graphical interface. The technique is illustrated using several protein examples and the results obtained are compared with corresponding results based on biological methodologies in order to demonstrate the usefulness, accuracy, and reliability of the technique.
Year
DOI
Venue
2008
10.1109/JSTSP.2008.923850
Selected Topics in Signal Processing, IEEE Journal of
Keywords
Field
DocType
filtering theory,graphical user interfaces,medical signal processing,proteins,amino-acid sequence,biological methodologies,digital filters,protein molecule,protein sequence,proteins hot-spot locations,user-friendly graphical interface,zero-phase filtering,Characteristic frequency,consensus spectrum,digital filters,electron-ion interaction potential (EIIP),fast Fourier transform (FFT),hot spots,proteins,resonant recognition model (RRM)
Computer vision,Hot spot (veterinary medicine),Digital filter,MATLAB,Narrowband,Pattern recognition,Band-pass filter,Computer science,Filter (signal processing),Phase response,Graphical user interface,Artificial intelligence
Journal
Volume
Issue
ISSN
2
3
1932-4553
Citations 
PageRank 
References 
10
0.98
5
Authors
2
Name
Order
Citations
PageRank
Parameswaran Ramachandran1100.98
A. Antoniou226730.79