| Objective:In this paper, we aim to provide the results of clusters (or groups) that are the PD's associated mRNA sequences by different number of thresholds in the cluster analysis. Make cluster on PD related mRNA sequences, and make groups of cluster upon different number of thresholds. From the cluster analysis point of view, the mRNA sequences in one group have been consisted to have close relationship and similar functions and characters. Based on above, PD related function Genes are classified. This may possibly be made use of information reference in clinical diagnosis and treatment of the PD by the results of the cluster analysis. The cluster analysis can yield useful information on the intrinsic characters or property of this data. The measurement relationship of these sequences was identified and analyzed by the cluster analysis.Methods:By searching of keyword "parkinsonism" from the Nucleotide database of National Center for Biotechnology Information (NCBI),19 mRNA sequences were selected which interrelated with human being and applied that into sequences alignment analysis. Two methods of hierarchical clustering and fuzzy clustering are used in this paper. The method is that cluster analysis divides the data of Parkinson-Relates mRNA Sequences into groups such that similar the data objects belong to the same cluster and dissimilar the data objects to different clusters. The clustering method is based on the measure of distance. This measure is the score that respective pair wise sequence alignment of interrelated mRNA sequences with sequences with those in the NCBI database.Results:On the basis of the equivalent matrix, one can have the cluster graphs by different clustering methods and the clusters by different number of a-cuts (thresholds). By the cluster analysis, some sequences are interrelated with same group, the sequences in one group have been consisted to have close relationship and functions. To choose the appropriateα-cuts, the fuzzy cluster graph can be applied to analysis the problem. In the results of hierarchical clustering, there are three groups {X4, X8, X11, X15},{X6} and {X1, X2, X3, X5, X7, X9, X10, X12, X14, X15, X16, X17, X18, X19} when thresholds is 0.6. In the results of fuzzy graph clustering, there are three groups{X4, X8, X11, X15},{X1, X 5, X16,X6} and {X2, X3, X7, X9, X10, X12, X14, X 15, X17, X18, X19} when thresholds is 0.5. In the results of fuzzy relation clustering, there are four groups{X4, X8, X11, X15},{X6},{X1}和{X5, X16, X 2, X3, X7, X9, X10, X12, X14, X15, X17, X18, X19} when thresholds is 0.6.Conclusion:There are used the data resources of biological sequences in public databases to do research on Parkinson-Relates genes. Study on interrelated mRNA/gene sequences of the disease by the bioinformatics method is one of the topics on gene research. From the three cluster graphs, one can have conformable results that is the four element X4, X8, X11 and X 15 are interrelated with same group. Although related relationship from cluster analysis should be confirmed by medicine before it is used on PD's prevention, clinical diagnosis and treatment, The results still could give big support on study of PD. This method of study can not only be used in PD's research, but also apply for other disease explore.
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