Prediction of protein structural classes by Chou’s pseudo amino acid composition: approached using continuous wavelet transform and principal component analysis

Amino Acids ◽  
2008 ◽  
Vol 37 (2) ◽  
pp. 415-425 ◽  
Author(s):  
Zhan-Chao Li ◽  
Xi-Bin Zhou ◽  
Zong Dai ◽  
Xiao-Yong Zou
Keyword(s):  
Principal Component Analysis ◽  
Wavelet Transform ◽  
Amino Acid ◽  
Amino Acid Composition ◽  
Acid Composition ◽  
Continuous Wavelet Transform ◽  
Principal Component ◽  
Continuous Wavelet ◽  
Pseudo Amino Acid Composition ◽  
Structural Classes

scholarly journals Microsaccade characterization using the continuous wavelet transform and principal component analysis

2010 ◽  
Vol 3 (5) ◽  
Author(s):  
Mario Bettenbühl ◽  
Claudia Paladini ◽  
Konstantin Mergenthaler ◽  
Reinhold Kliegl ◽  
Ralf Engbert ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Wavelet Transform ◽  
Eye Movements ◽  
Continuous Wavelet Transform ◽  
Principal Component ◽  
Real Data ◽  
Component Analysis ◽  
Continuous Wavelet ◽  
Fixational Eye Movements ◽  
Definition Of

During visual fixation on a target, humans perform miniature (or fixational) eye movements consisting of three components, i.e., tremor, drift, and microsaccades. Microsaccades are high velocity components with small amplitudes within fixational eye movements. However, microsaccade shapes and statistical properties vary between individual observers. Here we show that microsaccades can be formally represented with two significant shapes which we identfied using the mathematical definition of singularities for the detection of the former in real data with the continuous wavelet transform. For character-ization and model selection, we carried out a principal component analysis, which identified a step shape with an overshoot as first and a bump which regulates the overshoot as second component. We conclude that microsaccades are singular events with an overshoot component which can be detected by the continuous wavelet transform.

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