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Clustering of high throughput gene expression data
High throughput biological data need to be processed, analyzed, and interpreted to address
problems in life sciences. Bioinformatics, computational biology, and systems biology deal …
problems in life sciences. Bioinformatics, computational biology, and systems biology deal …
Fuzzy rough sets, and a granular neural network for unsupervised feature selection
A granular neural network for identifying salient features of data, based on the concepts of
fuzzy set and a newly defined fuzzy rough set, is proposed. The formation of the network …
fuzzy set and a newly defined fuzzy rough set, is proposed. The formation of the network …
Fast and accurate hashing via iterative nearest neighbors expansion
Recently, the hashing techniques have been widely applied to approximate the nearest
neighbor search problem in many real applications. The basic idea of these approaches is …
neighbor search problem in many real applications. The basic idea of these approaches is …
An introduction to new robust linear and monotonic correlation coefficients
Background The most common measure of association between two continuous variables is
the Pearson correlation (Maronna et al. in Safari an OMC. Robust statistics, 2019 …
the Pearson correlation (Maronna et al. in Safari an OMC. Robust statistics, 2019 …
A granular self-organizing map for clustering and gene selection in microarray data
A new granular self-organizing map (GSOM) is developed by integrating the concept of a
fuzzy rough set with the SOM. While training the GSOM, the weights of a winning neuron and …
fuzzy rough set with the SOM. While training the GSOM, the weights of a winning neuron and …
[ספר][B] Data mining for bioinformatics
S Dua, P Chowriappa - 2012 - books.google.com
Data Mining for Bioinformatics enables researchers to meet the challenge of mining vast
amounts of biomolecular data to discover real knowledge. Covering theory, algorithms, and …
amounts of biomolecular data to discover real knowledge. Covering theory, algorithms, and …
Fuzzy rough granular self-organizing map and fuzzy rough entropy
A fuzzy rough granular self-organizing map (FRGSOM) involving a 3-dimensional linguistic
vector and connection weights, defined in an unsupervised manner, is proposed for …
vector and connection weights, defined in an unsupervised manner, is proposed for …
Genetic algorithm for assigning weights to gene expressions using functional annotations
A method, named genetic algorithm for assigning weights to gene expressions using
functional annotations (GAAWGEFA), is developed to assign proper weights to the gene …
functional annotations (GAAWGEFA), is developed to assign proper weights to the gene …
A supervised weighted similarity measure for gene expressions using biological knowledge
A supervised similarity measure for Saccharomyces cerevisiae gene expressions is
developed which can capture the gene similarity when multiple types of experimental …
developed which can capture the gene similarity when multiple types of experimental …
Similarity Measure Learning in Closed‐Form Solution for Image Classification
Adopting a measure is essential in many multimedia applications. Recently, distance
learning is becoming an active research problem. In fact, the distance is the natural measure …
learning is becoming an active research problem. In fact, the distance is the natural measure …