Swarm Intelligence (SI) is an innovative artificial intelligence technique for solving complex optimization problems. Data clustering is the process of grouping data into a number of clusters. The goal of data clustering is to make the data in the same cluster share a high degree of similarity while being very dissimilar to data from other clusters. Clustering algorithms have been applied to a ...

We report evidence that the enzyme transglutaminase (glutaminyl-peptide gamma-glutamyltransferase; R-glutaminyl-peptide:amine gamma-glutamyltransferase, EC2.3.2.13) participates in receptor-mediated endocytosis. Clustering and internalization of rhodamine-labeled alpha 2-macroglobulin (R alpha 2 M) in normal rat kidney (NRK) cells is inhibited by a wide spectrum of compounds that inhibit transg...

in this paper an application of gustafson-kessel clustering algorithm is presented to create a fault detection map (fdm). five post-stack seismic attributes are extracted from a desired seismic time slice related to 3d seismic data of a gas field located in southwest of iran. to find the optimal cluster numbers, two frequently used clustering validity measures, i.e. sc and xb, are used and then...

Chromatographic fingerprints recorded for a set of genuine and counterfeit samples of Viagra(®) and Cialis(®) were evaluated for their use in the detection and classification of counterfeit samples of these groups of medicines. Therefore several exploratory chemometric techniques were applied to reveal structures in the data sets as well as differences among the samples. The focus was on the di...

knowing the fact that the main weakness of the most standard methods including k-means and hierarchical data clustering is their sensitivity to initialization and trapping to local minima, this paper proposes a modification of convex data clustering  in which there is no need to  be peculiar about how to select initial values. due to properly converting the task of optimization to an equivalent...

this paper compares clusters of aligned persian and english texts obtained from k-means method. text clustering has many applications in various fields of natural language processing. so far, much english documents clustering research has been accomplished. now this question arises, are the results of them extendable to other languages? since the goal of document clustering is grouping of docum...

An understanding of bacterial diversity and evolution in any environment requires knowledge of phenotypic diversity. In this study, the underlying factors leading to phenotypic clustering were analyzed and interpreted using a novel approach based on a four-tiered graph. Bacterial isolates were organized into equivalence classes based on their phenotypic profile. Likewise, phenotypes were organi...

This research work intends to propose a system with improved cuckoo searchbased robust ensemble co-clustering algorithm (ICS RECCA) for enzyme clustering. The cuckoo search algorithm has been inspired by the obligate brood parasitism of some cuckoo species by laying their eggs in the nests of other host birds (of other species). Some host birds can engage direct conflict with the intruding cuck...

Neurotransmission is ensured by a high concentration of neurotransmitter receptors at the postsynaptic membrane. This is mediated by scaffold proteins that bridge the receptors with cytoskeleton. One such protein is rapsyn (receptor-associated protein at synapse), which is essential for acetylcholine receptor (AChR) clustering and NMJ (neuromuscular junction) formation. We show that the RING do...