Clustering of high throughput gene expression data

H Pirim, B Ekşioğlu, AD Perkins, C Yüceer - Computers & operations …, 2012‏ - Elsevier
High throughput biological data need to be processed, analyzed, and interpreted to address
problems in life sciences. Bioinformatics, computational biology, and systems biology deal …

Fuzzy rough sets, and a granular neural network for unsupervised feature selection

A Ganivada, SS Ray, SK Pal - Neural Networks, 2013‏ - Elsevier
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 …

Fast and accurate hashing via iterative nearest neighbors expansion

Z **, D Zhang, Y Hu, S Lin, D Cai… - IEEE transactions on …, 2014‏ - ieeexplore.ieee.org
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 …

An introduction to new robust linear and monotonic correlation coefficients

M Tabatabai, S Bailey, Z Bursac, H Tabatabai… - BMC …, 2021‏ - Springer
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 …

A granular self-organizing map for clustering and gene selection in microarray data

SS Ray, A Ganivada, SK Pal - IEEE transactions on neural …, 2015‏ - ieeexplore.ieee.org
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 …

[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 …

Fuzzy rough granular self-organizing map and fuzzy rough entropy

A Ganivada, SS Ray, SK Pal - Theoretical Computer Science, 2012‏ - Elsevier
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 …

Genetic algorithm for assigning weights to gene expressions using functional annotations

SS Ray, S Misra - Computers in Biology and Medicine, 2019‏ - Elsevier
A method, named genetic algorithm for assigning weights to gene expressions using
functional annotations (GAAWGEFA), is developed to assign proper weights to the gene …

A supervised weighted similarity measure for gene expressions using biological knowledge

SS Ray, S Misra - Gene, 2016‏ - Elsevier
A supervised similarity measure for Saccharomyces cerevisiae gene expressions is
developed which can capture the gene similarity when multiple types of experimental …

Similarity Measure Learning in Closed‐Form Solution for Image Classification

J Chen, YY Tang, CLP Chen, B Fang… - The Scientific World …, 2014‏ - Wiley Online Library
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 …