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Based on the chaos game representation of protein sequences, a new method to predict the subcellular location of apoptosis protein sequences was put forward. Using of Support Vector Machine,and tested on a known dataset which includes 317 apoptosis proteins, the higher predictive success rates were obtained. Our prediction results showed that the chaos game representation of protein sequences were...
Can sequence analysis tell us about the function of protein? A basic question in protein science is which kind of proteins extent thermostability. Chaos game representation (CGR) can investigate the patterns hiding in protein sequence, visually revealing previously unknown structure. In this paper, we convert every protein sequence into a 20-dimensional vector by CGR algorithm, and based on these...
We present a new computational approach to measure the distance between two biological sequences. A biological sequence quantifies as a Markov Chain with 20 states. Stochastic state transition matrix is computed as the quantitative index of the biological sequence. The Kullback-Leibler discrimination information is used as a diversity indicator to measure the dissimilarity of each pair of the rows...
This paper applies empirical mode decomposition (EMD) to find functional similarity of proteins with low identity. The cross-correlation coefficient based on the EMD is used to measure the pair-wise similarity. We also use a segmentation technique, combined with EMD, to handle long protein sequences. The results are compared with those using the pair-wise alignment and PSI-BLAST.
Apoptosis proteins have a central role in the development and homeostasis of an organism. These proteins are very important for the understanding the mechanism of programmed cell death, and their function is related to their types. According to the classification scheme by G.P.Zhou (Zhou and Doctor,2003), the apoptosis proteins are categorized into the following four types: (1) Cytoplasmic protein;...
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