Microarray techniques provide new methods to find coregulated genes based on their coexpression profiles. Under the assumption that coregulated genes share cis acting regulatory elements, it is important to investigate the upstream sequences controlling the transcription of these genes. A modified Gibbs sampling algorithm with background interpolated Markov model (IMM) has been developed to detect regulatory elements in the upstream regions of translation start site of coexpressed genes. Simulated data are used to test our algorithm successfully. Results show that the improved Gibbs sampling has better performance in extracting less-conserved elements than algorithms with single nucleotide independent model and fixed higher-order Markov models. Then, upstream sequences of two clusters of coexpressed genes from Saccharomyces cerevisiae under diauxic shift conditions are analyzed, several putative motifs that may be involved in the pathway are found.

A linear symmetry based 3D edge orientation estimation method is presented. By introducing a "triple number" concept, which can be used to represent 3D space vector, the 3D edge orientation can be easily estimation. The basic principle and the algorithm are described.

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This paper presents a new exponential behaviour based entropy operator for extracting image edges. Edges can be detected by computing the entropy of brightness or hue in a local region of a picture. The entropy depends not only on the rate of change of brightness or hue, but also on the average brightness or hue. The experimental result verifies the efficiency of the new entropy operator.