TriRNSC: triclustering of gene expression microarray data using restricted neighbourhood search

Computational analysis of microarray data is crucial for understanding the gene behaviours and deriving meaningful results. Clustering and biclustering of gene expression microarray data in the unsupervised domain are extremely important as their outcomes directly dominate healthcare research in man...

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Vydáno v:	IET systems biology Ročník 14; číslo 6; s. 323 - 333
Hlavní autoři:	Biswal, Bhawani Sankar, Patra, Sabyasachi, Mohapatra, Anjali, Vipsita, Swati
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	England The Institution of Engineering and Technology 01.12.2020
Témata:	Algorithms biology computing Cluster Analysis Computational Biology - methods data analysis disease identification diseases drug discovery gene expression microarray data clustering Gene Expression Profiling gene ontology genetics genomics graph based clustering graph theory health care healthcare research Humans KEGG pathway analysis Oligonucleotide Array Sequence Analysis ontologies (artificial intelligence) pattern clustering Research Article restricted neighbourhood search clustering search problems three dimensional data triclustering algorithm TriRNSC algorithm unsupervised learning unsupervised machine learning data analysis disease identification graph theory graph based clustering KEGG pathway analysis diseases healthcare research unsupervised learning gene expression microarray data clustering gene ontology unsupervised machine learning restricted neighbourhood search clustering genetics biology computing pattern clustering drug discovery genomics ontologies (artificial intelligence) three dimensional data triclustering algorithm search problems health care TriRNSC algorithm
ISSN:	1751-8849, 1751-8857, 1751-8857
On-line přístup:	Získat plný text
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