The field of pattern recognition and machine learning has a long and distinguished history. In particular, there are many excellent textbooks on the topic, so the question of why a new …
We have developed a novel molecular methodology that utilizes stool samples containing intact sloughed epithelial cells to quantify intestinal gene expression profiles in the …
This paper investigates feature selection based on rough sets for dimensionality reduction in Case-Based Reasoning classifiers. In order to be useful, Case-Based Reasoning systems …
D Stowell, MD Plumbley - IEEE Signal Processing Letters, 2009 - ieeexplore.ieee.org
We describe a nonparametric estimator for the differential entropy of a multidimensional distribution, given a limited set of data points, by a recursive rectilinear partitioning. The …
An important problem in bioinformatics is the inference of gene regulatory networks (GRNs) from expression profiles. In general, the main limitations faced by GRN inference methods …
Background An accurate understanding of interactions among genes plays a major role in developing therapeutic intervention methods. Gene regulatory networks often contain a …
In Machine Learning, feature selection is an important step in classifier design. It consists of finding a subset of features that is optimum for a given cost function. One possibility to solve …
Background Gene regulatory networks (GRN) inference is an important bioinformatics problem in which the gene interactions need to be deduced from gene expression data …
Background Sequencing datasets consist of a finite number of reads which map to specific regions of a reference genome. Most effort in modeling these datasets focuses on the …