Modules Identification in Gene Positive Networks of Hepatocellular Carcinoma Using Pearson Agglomerative Method and Pearson Cohesion Coupling Modularity

Modules Identification in Gene Positive Networks of Hepatocellular Carcinoma Using Pearson Agglomerative Method and Pearson Cohesion Coupling Modularity

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Pearson System Based Method for Blind Separation

Component Identification Method with Coupling and Cohesion

Since the introduction of component-based development (CBD), effective component identification technique is known to be an important factor for successful CBD projects. As in CORBA Component Model by OMG, a component consists of one or more related objects, carrying out a homogeneous functionality. Most of the CBD methodologies utilize UML as the basic notational convention. Especially the com...

A Null Model for Pearson Coexpression Networks

Gene coexpression networks inferred by correlation from high-throughput profiling such as microarray data represent simple but effective structures for discovering and interpreting linear gene relationships. In recent years, several approaches have been proposed to tackle the problem of deciding when the resulting correlation values are statistically significant. This is most crucial when the n...

Revisiting Clopper-Pearson

This paper adds one more contribution to the large literature on binomial confidence intervals for small samples (e.g., Clopper and Pearson 1934; Pearson and Hartley 1954; Sterne 1954; Crow 1956; Blyth and Still 1983; Blyth 1986; Santner and Duffy 1989; Agresti and Coull 1998; Henderson and Meyer 2001). Clopper and Peason (1934) gave the first two-sided binomial confidence intervals, in graphic...