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Recent advances on human pluripotent stem cells (hPSCs), including human embryonic stem cells (hESCs) and induced pluripotent stem cells (hiPSCs) have brought us closer to the realization of their clinical potential. Nonetheless, tissue engineering and regenerative medicine applications will require the generation of hPSC products well beyond the laboratory(More)
Clustering is a separation of data into groups of similar objects. Every group called cluster consists of objects that are similar to one another and dissimilar to objects of other groups. In this paper, the K-Means algorithm is implemented by three distance functions and to identify the optimal distance function for clustering methods. The proposed K-Means(More)
— Bioinformatics is the application of information technology to the management of molecular biological data. Motif finding in protein sequence is one of the most crucial tasks in bioinformatics research. Motifs are identifying as overly recurring sub-patterns in segment of protein sequence biological data. Sequence motifs are verifying by their structural(More)
A large molecule composed of one or more chains of amino acids in a specific order, the order is determined by the base sequence of nucleotides in the gene that codes for the protein. Proteins are required for the structure, function, and regulation of the body's cells, tissues, and organs and each protein has unique functions. Localization sites of(More)
Clustering is a process for classifying objects or patterns in such a way that samples of the same group are more similar to one another than samples belonging to different groups. In this paper, we introduce the clustering method called soft clustering and its type Fuzzy C-Means. The clustering algorithms are improved by implementing the two different(More)
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