clustering is the process of dividing a set of input data into a number of subgroups. the members of each subgroup are similar to each other but different from members of other subgroups. the genetic algorithm has enjoyed many applications in clustering data. one of these applications is the clustering of images. the problem with the earlier methods used in clustering images was in selecting in...

Research on change-point detection, the classical problem of detecting abrupt changes in sequential data, has focused predominantly on datasets with a single observable. A growing number of time series datasets, however, involve many observables, often with the property that a given change typically affects only a few of the observables. We introduce a general statistical method that, given man...

The determination of molecular structures is of growing importance in modern chemistry and biology. This thesis presents two practical, systematic algorithms for two structure determination problems. Both algorithms are branch-and-bound techniques adapted to their respective domains. The rst problem is the determination of structures of multimers given rigid monomer structures and (potentially ...

We present a novel de novo method to generate protein models from sparse, discretized restraints on the conformation of the main chain and side chain atoms. We focus on C -trace generation, the problem of constructing an accurate and complete model from approximate knowledge of the positions of the C atoms and, in some cases, the side chain centroids. Spatial restraints on the C atoms and side ...

in this study the genetic polymorphism of growth hormone (gh) gene as a candidate gene in livestock was investigated. blood samples were randomly collected from 34 alpine and 42 saanen goats. dna was extracted from blood samples and a 365 bp region of exon 5 of the gh genewas amplified by polymerase chain reaction (pcr). pcr products were analyzed using single strand conformation polymorphism (...

this study emphasized the ability of genetic algorithm and cellular automate to simulate urban land use changes by integrating adaptive model. the most important part of modeling is to define transition rules.  in this research, a cellular automata model in dinamica ego software was used coupled with genetic algorithm. according to disability of the software for manipulating large number of var...

In this study the genetic polymorphism of growth hormone (GH) gene as a candidate gene in livestock was investigated. Blood samples were randomly collected from 34 Alpine and 42 Saanen goats. DNA was extracted from blood samples and a 365 bp region of exon 5 of the GH genewas amplified by polymerase chain reaction (PCR). PCR products were analyzed using single strand conformation polymorphism (...