MOTIVATION Stem cell differentiation is largely guided by master transcriptional regulators, but it also depends on the expression of other types of genes, such as cell cycle genes, signaling genes, metabolic genes, trafficking genes, etc. Traditional approaches to understanding gene expression patterns across multiple conditions, such as principal components analysis or K-means clustering, can...

This article revisits the objective function (or metric) used in extraction of photovoltaic (PV) model parameters. A theoretical investigation shows that widely current distance (CD) metric does not yield maximum likelihood estimates (MLE) parameters when there is noise both voltage and samples. It demonstrates Euclidean (ED) should be instead, powers are equal. For general case, a new noise-sc...

The increasing amount of digital audio-visual content accessible today calls for scalable solutions for content based search. The state of the art solutions reveal linear scalability in respect to the collection size due to the large number of distance computations needed for comparing low level audio-visual features. As a result, search in large audio-visual collections is limited to associate...

INTRODUCTION The human functional connectome is a graphical representation, consisting of nodes connected by edges, of the inter-relationships of blood oxygenation-level dependent (BOLD) time-series measured by MRI from regions encompassing the cerebral cortices and, often, the cerebellum. Semi-metric analysis of the weighted, undirected connectome distinguishes an edge as either direct (metric...

Introduction: Population and longitudinal analyses using Diffusion Tensor Imaging (DTI) data have become feasible over the past decade with advanced sequences and sophisticated mathematical tools. These studies make use of some form of elastic tensor field registration framework to derive a population average brain and the deviation modes. These registration algorithms need to employ a speciali...

Missing data is a common drawback in many real-life pattern classification scenarios. One of the most popular solutions is missing data imputation by the K nearest neighbours ðKNNÞ algorithm. In this article, we propose a novel KNN imputation procedure using a feature-weighted distance metric based on mutual information (MI). This method provides a missing data estimation aimed at solving the c...

Supervised attribute relevance detection using cross-comparisons (SARDUX), a recently proposed method for data-driven metric learning, is extended from dimension-weighted Minkowski distances to metrics induced by a data transformation matrix Ω for modeling mutual attribute dependence. Given class labels, parameters of Ω are adapted in such a manner that the inter-class distances are maximized, ...