0000000000328230
AUTHOR
Asoke Nandi
showing 4 related works from this author
Comprehensive analysis of forty yeast microarray datasets reveals a novel subset of genes (APha-RiB) consistently negatively associated with ribosome…
2014
This article has been made available through the Brunel Open Access Publishing Fund. Background: The scale and complexity of genomic data lend themselves to analysis using sophisticated mathematical techniques to yield information that can generate new hypotheses and so guide further experimental investigations. An ensemble clustering method has the ability to perform consensus clustering over the same set of genes from different microarray datasets by combining results from different clustering methods into a single consensus result. Results: In this paper we have performed comprehensive analysis of forty yeast microarray datasets. One recently described Bi-CoPaM method can analyse express…
Diverse partner selection with brood recombination in genetic programming
2018
The ultimate goal of learning algorithms is to find the best solution from a search space without testing each and every solution available in the search space. During the evolution process new solutions (children) are produced from existing solutions (parents), where new solutions are expected to be better than existing solutions. This paper presents a new parent selection method for the crossover operation in genetic programming. The idea is to promote crossover between two behaviourally (phenotype) diverse parents such that the probability of children being better than their parents increases. The relative phenotype strengths and weaknesses of pairs of parents are exploited to find out i…
UNCLES: Method for the identification of genes differentially consistently co-expressed in a specific subset of datasets
2015
Background Collective analysis of the increasingly emerging gene expression datasets are required. The recently proposed binarisation of consensus partition matrices (Bi-CoPaM) method can combine clustering results from multiple datasets to identify the subsets of genes which are consistently co-expressed in all of the provided datasets in a tuneable manner. However, results validation and parameter setting are issues that complicate the design of such methods. Moreover, although it is a common practice to test methods by application to synthetic datasets, the mathematical models used to synthesise such datasets are usually based on approximations which may not always be sufficiently repres…
Low-rank approximation based non-negative multi-way array decomposition on event-related potentials
2014
Non-negative tensor factorization (NTF) has been successfully applied to analyze event-related potentials (ERPs), and shown superiority in terms of capturing multi-domain features. However, the time-frequency representation of ERPs by higher-order tensors are usually large-scale, which prevents the popularity of most tensor factorization algorithms. To overcome this issue, we introduce a non-negative canonical polyadic decomposition (NCPD) based on low-rank approximation (LRA) and hierarchical alternating least square (HALS) techniques. We applied NCPD (LRAHALS and benchmark HALS) and CPD to extract multi-domain features of a visual ERP. The features and components extracted by LRAHALS NCPD…