Results 101 to 110 of about 3,388 (214)

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, Shin Hyunjung, Su Chung Tae, Joung Je-Gun, Kim Ju Han   +4 more
doaj   +1 more source

Biclustered Independent Component Analysis for Complex Biomarker and Subtype Identification from Structural Magnetic Resonance Images in Schizophrenia

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, Cota Navin Gupta, Eduardo Castro, Eduardo Castro, Srinivas Rachkonda, Theo G. M. van Erp, Steven Potkin, Judith M. Ford, Daniel Mathalon, Hyo Jong Lee, Bryon A. Mueller, Douglas N. Greve, Ole A. Andreassen, Ole A. Andreassen, Ingrid Agartz, Ingrid Agartz, Ingrid Agartz, Andrew R. Mayer, Julia Stephen, Rex E. Jung, Juan Bustillo, Vince D. Calhoun, Vince D. Calhoun, Jessica A. Turner, Jessica A. Turner   +24 more
doaj   +1 more source

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, Jaksik Roman, Ślęzak Dominik   +2 more
doaj   +1 more source

Biclustering meets triadic concept analysis [PDF]

, 2014
International audienceBiclustering numerical data became a popular data-mining task at the be-ginning of 2000's, especially for gene expression data analysis and recommender sys-tems.
Kaytoue, Mehdi, Napoli, Amedeo, Macko, Juraj, Kuznetsov, Sergei,, Kuznetsov, Sergei, O.   +4 more
core   +1 more source

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, František Malinka, Filip železný   +2 more
doaj   +1 more source

Optimisation algorithms for microarray biclustering

, 2013
In providing simultaneous information on expression profiles for thousands of genes, microarray technologies have, in recent years, been largely used to investigate mechanisms of gene expression.
Dimitri Perrin, Perrin, Dimitri, Duhamel, Christophe, Christophe Duhamel   +3 more
core   +1 more source

A probabilistic coevolutionary biclustering algorithm for discovering coherent patterns in gene expression dataset

BMC Bioinformatics, 2012
Background Biclustering has been utilized to find functionally important patterns in biological problem. Here a bicluster is a submatrix that consists of a subset of rows and a subset of columns in a matrix, and contains homogeneous patterns. The problem
Joung Je-Gun, Kim Soo-Jin, Shin Soo-Yong, Zhang Byoung-Tak   +3 more
doaj   +1 more source

The Influence of the Binary Process Threshold on the BCBimax Algorithm in Finding Optimal BC

InPrime
Selecting an appropriate threshold is crucial in the binarization process because it directly affects the quality of biclusters generated by the BCBimax algorithm.
Femmy Diwidian, I Made Sumertajaya, Indahwati Indahwati, Hari Wijayanto, Bagus Sartono   +4 more
doaj   +1 more source

Adatbányászati Algoritmusok Bi-Clustering Alkalmazásokban

, 2009
A szakdolgozat célja a biclustering, mint technika bemutatása, és az adatbányászat e biológiai alkalmazásának, gyakorlati szinten történő illusztrációja ...
Kocsis, Annamária
core  

Graphical Model approaches for Biclustering [PDF]

, 2017
In many scientific areas, it is crucial to group (cluster) a set of objects, based on a set of observed features. Such operation is widely known as Clustering and it has been exploited in the most different scenarios ranging from Economics to Biology ...
Denitto, Matteo
core