traditional leveraging statistical methods for analyzing today’s large volumes of spatial data have high computational burdens. to eliminate the deficiency, relatively modern data mining techniques have been recently applied in different spatial analysis tasks with the purpose of autonomous knowledge extraction from high-volume spatial data. fortunately, geospatial data is considered a proper s...

This research work intends to propose a system with improved cuckoo search based 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 cuc...

Nowadays, the clustering of proteins and enzymes in particular, are one of the most popular topics in bioinformatics. Increasing number of chitinase genes from different organisms and their sequences have beenidentified. So far, various mathematical algorithms for the clustering of chitinase genes have been used butmost of them seem to be confusing and sometimes insufficient. In the...

assigning a set of objects to groups such that objects in one group or cluster are more similar to each other than the other clusters’ objects is the main task of clustering analysis. sspco optimization algorithm is anew optimization algorithm that is inspired by the behavior of a type of bird called see-see partridge. one of the things that smart algorithms are applied to solve is the problem ...

The 85 kDa human cytosolic phospholipase A2 has been cloned and expressed in insect Sf21 cells. The pure enzyme has been investigated using a fluorescence displacement assay that provides a continuous record of phospholipid hydrolysis [Wilton (1990) Biochem. J. 266, 435-439]. The unusual kinetic properties of this enzyme, previously described using radioactive assays, were readily demonstrated ...

this paper presents a fuzzy decision-making approach to deal with a clustering supplier problem in a supply chain system. during recent years, determining suitable suppliers in the supply chain has become a key strategic consideration. however, the nature of these decisions is usually complex and unstructured. in general, many quantitative and qualitative factors, such as quality, price, and fl...

There is a high demand for engineering thermostable enzymes in some industries; especially in paper industries to use environmental friendly enzymes instead of toxic chlorine chemicals. Hence, understanding protein attributes involved in enzyme thermostability is important. Herein, the most important protein features contributing to enzyme thermostability was searched by using data mining algor...

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 ...