Results 121 to 130 of about 3,388 (214)
RcmdrPlugin.BiclustGUI: 'Rcmdr' Plug-in GUI for Biclustering
, 2016 A plug-in for R Commander ('Rcmdr'). The package is a Graphical User Interface (GUI) in which several biclustering methods can be executed, followed by diagnostics and plots of the results. Further, the GUI also has the possibility to connect the methods
DE TROYER, Ewoud, OTAVA, Martin
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Bayesian biclustering in the presence of covariates: theory and applications
openIl biclustering rappresenta un'estensione del clustering tradizionale che permette di identificare simultaneamente gruppi di righe e colonne in matrici di dati ad alta dimensionalità.
VEGHIN, IRENE
core
This article proposes a biconvex modification to convex biclustering in order to improve its performance in high-dimensional settings. In contrast to heuristics that discard a subset of noisy features a priori, our method jointly learns and accordingly weighs informative features while discovering biclusters.
Rosen, Sam, Chi, Eric C., Xu, Jason
openaire +2 more sources
Feature Grouping Technique Based on Biclustering for the Analysis of LC-MS Metabolomic Data
, 2011 Feature Grouping Technique Based on Biclustering for the Analysis of LC-MS Metabolomic ...
周丽娜 +4 more
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Problemy EkorozwojuThis study evaluates the progress of 31 countries, including EU member states, Norway, Iceland, Switzerland, and the United Kingdom (UK), towards the United Nations (UN) 2030 Agenda for Sustainable Development (SD) and its 17 Sustainable Development ...
Magdaléna Drastichová, Peter Filzmoser
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The penalized biclustering model and related algorithms
, 2015 Biclustering is the simultaneous clustering of two related dimensions, for example, of individuals and features, or genes and experimental conditions. Very few statistical models for biclustering have been proposed in the literature. Instead, most of the
Thierry Chekouo (683161) +1 more
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Biclustering for multivariate longitudinal data
, 2019 Applications in various domains often lead to high-dimensional data, which put up the challenge of interpreting a huge mass of data often consisting of millions of measurements.
Francesca Martella +2 more
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Pattern-driven neighborhood search for biclustering of microarray data
, 2012 Biclustering aims at finding subgroups of genes that show highly correlated behaviors across a subgroup of conditions. Biclustering is a very useful tool for mining microarray data and has various practical applications.
M. Elloumi +5 more
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Biclustering a dataset using photonic quantum computing
Frontiers in Computer ScienceBiclustering is a problem in machine learning and data mining that seeks to group together rows and columns of a dataset according to certain criteria. In this work, we highlight the natural relation that quantum computing models like boson and Gaussian ...
Ajinkya Borle, Ameya Bhave
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IEEE AccessThe manuscript details the outcomes of a comprehensive study on the application of cluster-bicluster analysis, gene ontology analysis, and convolutional neural network (CNN) for diagnosing cancer and Alzheimer’s disease using gene expression data ...
Sergii Babichev, Igor Liakh, Jiri Skvor
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