Incorporating PCA and fuzzy-ART techniques into achieve organism classification based on codon usage consideration

Author(s): Hsieh, K.L. | Yang, I.C. |

Year: 2008

Citation: COMPUTERS IN BIOLOGY AND MEDICINE Volume: 38 Issue: 8 Pages: 886-893

Abstract: To recognize the DNA sequence and mine the hidden information to achieve the classification of organisms are viewed as a difficult work to biologists. As we know, the amino acids are the basic elements to construct DNA. Hence, if the codon usage of amino acids can be analyzed well, the useful information about classification of organisms may be obtained. However, if we choose too many amino acids to perform the clustering analysis, the high dimensions also lead the clustering analysis to be a complicated structure. Hence, in this study, we will incorporate the principle component analysis and fuzzy-ART clustering techniques into constructing an integrated approach. The useful information about organisms classification based on the codon usage can be mined by using the proposed approach. Finally, we also employ a case including 18 bacteria to demonstrate the rationality and feasibility of our proposed approach.

Topics: Machine Learning, Applications: Chemical Analysis, Models: ART 2 / Fuzzy ART,

PDF download



Cross References


  1. Order of Search in Fuzzy ART and Fuzzy ARTMAP: Effect of the Choice Parameter
    This paper focuses on two ART architectures, the Fuzzy ART and the Fuzzy ARTMAP. Fuzzy ART is a pattern clustering machine, while Fuzzy ARTMAP is a pattern classification machine. Our study concentrates on the order ... Article Details

  2. Fuzzy ART: Fast stable learning and categorization of analog patterns by an adaptive resonance system
    A Fuzzy Adaptive Resonance Theory (ART) model capable of rapid stable learning of recognition categories in response to arbitrary sequences of analog or binary input patterns is described. Fuzzy ART incorporates computations ... Article Details


Back to Articles