Title :
Robust entropy-enhanced frequency-domain genomic analysis under uncertainties
Author :
Lyshevski, Sergey Edward ; Krueger, Frank A.
Author_Institution :
Dept. of Electr. Eng., Rochester Inst. of Technol., NY, USA
Abstract :
Here, we report the application of an entropy-enhanced frequency-domain analysis method to examine large-scale genomic data. This ensures superior coherency for qualitative and quantitative analysis. Different statistical methods are used to analyze large-scale data produced and attempts have been made to perform data mining. These efforts have been partially successful due to sequence gaps, noncoding and low complexity regions, inaccuracy, etc. In contrast, we report a novel robust method that is based on frequency-domain analysis. Our paradigm complements a number of far-reaching perceptions that new concepts emerge to comprehend complex large-scale genomic data under uncertainties.
Keywords :
data mining; frequency-domain analysis; genetics; maximum entropy methods; statistical analysis; complex large-scale genomic data; data mining; different statistical methods; robust entropy enhanced frequency-domain genomic analysis; sequence gaps; Bioinformatics; Data analysis; Data mining; Frequency domain analysis; Genomics; Large-scale systems; Performance analysis; Robustness; Statistical analysis; Uncertainty;
Conference_Titel :
Nanotechnology, 2004. 4th IEEE Conference on
Print_ISBN :
0-7803-8536-5
DOI :
10.1109/NANO.2004.1392418