G-bic: generating synthetic benchmarks for biclustering [PDF]
BMC Bioinformatics, 2023 Background Biclustering is increasingly used in biomedical data analysis, recommendation tasks, and text mining domains, with hundreds of biclustering algorithms proposed.
Eduardo N. Castanho +3 more
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Protocol for analyzing functional gene module perturbation during the progression of diseases using a single-cell Bayesian biclustering framework [PDF]
STAR ProtocolsSummary: The pathogenesis of complex diseases involves intricate gene regulation across cell types, necessitating a comprehensive analysis approach.
Kunyue Wang +6 more
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A personalized reinforcement learning recommendation algorithm using bi-clustering techniques. [PDF]
PLoS ONERecommender systems have become a core component of various online platforms, helping users get relevant information from the abundant digital data.
Muhammad Waqar, Mubbashir Ayub
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Biclustering of Log Data: Insights from a Computer-Based Complex Problem Solving Assessment [PDF]
Journal of IntelligenceComputer-based assessments provide the opportunity to collect a new source of behavioral data related to the problem-solving process, known as log file data.
Xin Xu, Susu Zhang, Jinxin Guo, Tao Xin
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Evolutionary Mechanism Based Conserved Gene Expression Biclustering Module Analysis for Breast Cancer Genomics [PDF]
BiomedicinesThe identification of significant gene biclusters with particular expression patterns and the elucidation of functionally related genes within gene expression data has become a critical concern due to the vast amount of gene expression data generated by ...
Wei Yuan +7 more
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Biclustering Performance Evaluation of Cheng and Church Algorithm and Iterative Signature Algorithm
JTAM (Jurnal Teori dan Aplikasi Matematika), 2023 Biclustering has been widely applied in recent years. Various algorithms have been developed to perform biclustering applied to various cases. However, only a few studies have evaluated the performance of bicluster algorithms.
I Made Sumertajaya Sumertajaya +3 more
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Biclustering fMRI time series: a comparative study
BMC Bioinformatics, 2022 Background The effectiveness of biclustering, simultaneous clustering of rows and columns in a data matrix, was shown in gene expression data analysis. Several researchers recognize its potentialities in other research areas.
Eduardo N. Castanho +2 more
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QServer: a biclustering server for prediction and assessment of co-expressed gene clusters. [PDF]
PLoS ONE, 2012 BackgroundBiclustering is a powerful technique for identification of co-expressed gene groups under any (unspecified) substantial subset of given experimental conditions, which can be used for elucidation of transcriptionally co-regulated genes.ResultsWe
Fengfeng Zhou +3 more
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BMC Bioinformatics, 2022 Biclustering algorithm is an effective tool for processing gene expression datasets. There are two kinds of data matrices, binary data and non-binary data, which are processed by biclustering method.
He-Ming Chu +5 more
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Identification of bicluster regions in a binary matrix and its applications. [PDF]
PLoS ONE, 2013 Biclustering has emerged as an important approach to the analysis of large-scale datasets. A biclustering technique identifies a subset of rows that exhibit similar patterns on a subset of columns in a data matrix.
Hung-Chia Chen +3 more
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