Intensity based registration methods, such as the mutual information (MI), do not commonly consider the spatial geometric information and the initial correspondences are uncertainty. In this paper, we present a novel approach for achieving highly-automatic 2D/3D image registration integrating the advantages from both entropy MI and spatial geometric features correspondence methods. Inspired by ...

Motivation: Clustering is a frequently used concept in variety of bioinformatical applications. We present a new method for hierarchical clustering of data called mutual information clustering (MIC) algorithm. It uses mutual information (MI) as a similarity measure and exploits its grouping property: The MI between three objects X,Y, and Z is equal to the sum of the MI between X and Y , plus th...

ARACNe networks This package contains 24 Mutual Information-based networks assembled by ARACNeAP [1] with default parameters (MI p-value = 10−8, 100 bootstraps and permutation seed = 1). ARACNe is a network inference algorithm based on an Adaptive Partioning (AP) Mutual Information (MI) approach [1]. In short, ARACNe-AP estimates all pairwise Mutual Information scores between gene expression pr...

Background: Alignment of biological sequences such as DNA, RNA or proteins is one of the most widely used tools in computational bioscience. All existing alignment algorithms rely on heuristic scoring schemes based on biological expertise. Therefore, these algorithms do not provide model independent and objective measures for how similar two (or more) sequences actually are. Although informatio...

MISTIC (mutual information server to infer coevolution) is a web server for graphical representation of the information contained within a MSA (multiple sequence alignment) and a complete analysis tool for Mutual Information networks in protein families. The server outputs a graphical visualization of several information-related quantities using a circos representation. This provides an integra...

A major difficulty of text categorization is the high dimensionality of the original feature space. Feature selection plays an important role in text categorization. Automatic feature selection methods such as document frequency thresholding (DF), information gain (IG), mutual information (MI), and so on are commonly applied in text categorization. Many existing experiments show IG is one of th...

We study the entanglement wedge cross-section (EWCS) in holographic massive gravity theory, which a first and second-order phase transition can occur. find that mixed state measures, EWCS mutual information (MI) characterize transitions. The MI show exactly opposite behavior critical region, suggests captures distinct degrees of freedom from MI. More importantly, EWCS, HEE all same scaling regi...

Abstract Mutual Information (MI) is an important dependency measure between random variables, due to its tight connection with information theory. It has numerous applications, both in theory and practice. However, when employed in practice, it is often necessary to estimate the MI from available data. There are several methods to approximate the MI, but arguably one of the simplest and most wi...