Over the Past decade Medical Image segmentation is one of the most challenging and focused topic for intensive research in interdisciplinary areas of Image processing and computer vision. Segmentation is the process of automatic or semi-automatic detection of boundaries [5]. In this paper, we implement a novel unsupervised method for segmenting MRI brain Images based on multiresolution transforms and region based active contour. Application of multiscale, multiresolution methods with active contour is most interesting research topic in image segmentation [6].This new application makes segmentation algorithms more economical for computation.
The comparative analysis of motifs of promoter sequences of the genes encoding enzymes of metabolic pathways such as glycolysis and kreb cycle in different genomes can give insights into the understanding of evolutionary and organizational relationships among both the species as well as enzymes. The comparison of resulting analysis with those of the evolutionary distances drawn considering coding regions of the genes allows one to measure the evolution of complete processes. In the present study we have collected promoter sequences of the glycolysis and kreb cycle genes encoding the respective enzymes from the standard EMBL database and extracted ten Transcription factors (TFs) using the TFsearch tool. This information was put together to develop a database CMPP database both offline and online (http://cmpp.sbbiotech.com). The matrix was developed by calculating the distances based on the presence or absence of motifs (TFs). The phylogenetic tree was obtained by using the NJ method by calculating the distances both within and between the enzymes of glycolysis and kreb cycle individually. The present study could also be extended to pathways such as carbohydrate and lipid metabolic networks.
We propose a method for identifying transcription factor binding sites (TFBS) in the given promoter sequence and mapping the transcription factors (TFs). The proposed algorithm searches the +1 transcription start site (TSS) for eukaryotic and prokaryotic sequences individually. The algorithm was tested with sequences from both eukaryotes and prokaryotes for at least 9 experimentally verified and validated functional TFs in promoter sequences. The order and type of TF binding to the promoter of genes encoding central metabolic pathway (CMP) enzyme was tabulated. A new similarity measure was devised for scoring the similarity between a pair of promoter sequences based on the number and order of motifs. Further, these were grouped in clusters considering the scores between them. The distance between each of the clusters in individual pathway was calculated and a phylogenetic tree was developed. This method is further applied to other pathways such as lipid and amino acid biosynthesis to retrieve and compare experimentally verified and conserved TFBS.
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