A tutorial on analysis and simulation of boolean gene regulatory network models
Y Xiao - Current genomics, 2009 - ingentaconnect.com
Driven by the desire to understand genomic functions through the interactions among genes
and gene products, the research in gene regulatory networks has become a heated area in …
and gene products, the research in gene regulatory networks has become a heated area in …
[图书][B] Fundamentals of pattern recognition and machine learning
U Braga-Neto - 2020 - Springer
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 …
In particular, there are many excellent textbooks on the topic, so the question of why a new …
Noninvasive stool-based detection of infant gastrointestinal development using gene expression profiles from exfoliated epithelial cells
We have developed a novel molecular methodology that utilizes stool samples containing
intact sloughed epithelial cells to quantify intestinal gene expression profiles in the …
intact sloughed epithelial cells to quantify intestinal gene expression profiles in the …
Rough set based approaches to feature selection for case-based reasoning classifiers
M Salamo, M Lopez-Sanchez - Pattern Recognition Letters, 2011 - Elsevier
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 …
Case-Based Reasoning classifiers. In order to be useful, Case-Based Reasoning systems …
Fast Multidimensional Entropy Estimation by -d Partitioning
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 …
distribution, given a limited set of data points, by a recursive rectilinear partitioning. The …
A feature selection technique for inference of graphs from their known topological properties: Revealing scale-free gene regulatory networks
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 …
from expression profiles. In general, the main limitations faced by GRN inference methods …
Efficient experimental design for uncertainty reduction in gene regulatory networks
Background An accurate understanding of interactions among genes plays a major role in
developing therapeutic intervention methods. Gene regulatory networks often contain a …
developing therapeutic intervention methods. Gene regulatory networks often contain a …
An efficient, parallelized algorithm for optimal conditional entropy-based feature selection
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 …
finding a subset of features that is optimum for a given cost function. One possibility to solve …
Gene regulatory networks inference using a multi-GPU exhaustive search algorithm
Background Gene regulatory networks (GRN) inference is an important bioinformatics
problem in which the gene interactions need to be deduced from gene expression data …
problem in which the gene interactions need to be deduced from gene expression data …
MCMC implementation of the optimal Bayesian classifier for non-Gaussian models: model-based RNA-Seq classification
JM Knight, I Ivanov, ER Dougherty - BMC bioinformatics, 2014 - Springer
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 …
regions of a reference genome. Most effort in modeling these datasets focuses on the …