Results 91 to 100 of about 6,396 (182)
A Survey of Adaptive Resonance Theory Neural Network Models for Engineering Applications
, 2019 This survey samples from the ever-growing family of adaptive resonance theory (ART) neural network models used to perform the three primary machine learning modalities, namely, unsupervised, supervised and reinforcement learning.
da Silva, Leonardo Enzo Brito +2 more
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Frontiers in Psychiatry, 2017 Clinical and cognitive symptoms domain-based subtyping in schizophrenia (Sz) has been critiqued due to the lack of neurobiological correlates and heterogeneity in symptom scores.
Cota Navin Gupta +24 more
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Bayesian biclustering of gene expression data
BMC Genomics, 2008 Background Biclustering of gene expression data searches for local patterns of gene expression. A bicluster (or a two-way cluster) is defined as a set of genes whose expression profiles are mutually similar within a subset of experimental conditions ...
Liu Jun S, Gu Jiajun
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Heuristic Search of Exact Biclusters in Binary Data
International Journal of Applied Mathematics and Computer Science, 2020 The biclustering of two-dimensional homogeneous data consists in finding a subset of rows and a subset of columns whose intersection provides a set of cells whose values fulfil a specified condition.
Michalak Marcin +2 more
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Visual analytics in FCA-based clustering [PDF]
, 2015 Visual analytics is a subdomain of data analysis which combines both human and machine analytical abilities and is applied mostly in decision-making and data mining tasks.
Kashnitsky, Yury
core
Extracting regulatory modules from gene expression data by sequential pattern mining
BMC Genomics, 2011 Background Identifying a regulatory module (RM), a bi-set of co-regulated genes and co-regulating conditions (or samples), has been an important challenge in functional genomics and bioinformatics.
Kim Mingoo +4 more
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Clustering Scatter Plots Using Data Depth Measures. [PDF]
, 2011 Clustering is rapidly becoming a powerful data mining technique, and has been broadly applied to many domains such as bioinformatics and text mining. However, the existing methods can only deal with a data matrix of scalars. In this paper, we introduce a
Borneman, James +5 more
core
Semantic biclustering for finding local, interpretable and predictive expression patterns
BMC Genomics, 2017 Background One of the major challenges in the analysis of gene expression data is to identify local patterns composed of genes showing coherent expression across subsets of experimental conditions. Such patterns may provide an understanding of underlying
Jiří Kléma +2 more
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A New Study on Biclustering Tools, Biclusters Validation and Evaluation Functions
International Journal of Computer Science & Engineering Survey, 2015 There are subsets of genes that have similar behavior under subsets of conditions, so we say that they coexpress, but behaveindependently under other subsets of conditions. Discovering such coexpressions can be helpful to uncover genomic knowledge such as gene networks or gene interactions. That is why, it is of utmost importance to make a simultaneous
Haifa Ben Saber, Mourad Elloumi
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