Results 11 to 20 of about 3,388 (214)

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, João P. Lobo, Rui Henriques, Sara C. Madeira   +3 more
doaj   +2 more sources

Protocol for analyzing functional gene module perturbation during the progression of diseases using a single-cell Bayesian biclustering framework [PDF]

STAR Protocols
Summary: The pathogenesis of complex diseases involves intricate gene regulation across cell types, necessitating a comprehensive analysis approach.
Kunyue Wang, Yuqiao Gong, Zixin Yan, Zhiyuan Dang, Junhao Wang, Maoying Wu, Yue Zhang   +6 more
doaj   +2 more sources

RUBic: rapid unsupervised biclustering. [PDF]

BMC Bioinformatics, 2023
Biclustering of biologically meaningful binary information is essential in many applications related to drug discovery, like protein-protein interactions and gene expressions. However, for robust performance in recently emerging large health datasets, it
Sriwastava BK, Halder AK, Basu S, Chakraborti T.   +3 more
europepmc   +5 more sources

Biclustering of Log Data: Insights from a Computer-Based Complex Problem Solving Assessment [PDF]

Journal of Intelligence
Computer-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
doaj   +2 more sources

A personalized reinforcement learning recommendation algorithm using bi-clustering techniques. [PDF]

PLoS ONE
Recommender systems have become a core component of various online platforms, helping users get relevant information from the abundant digital data.
Muhammad Waqar, Mubbashir Ayub
doaj   +2 more sources

An Efficient Algorithm for Convex Biclustering

Mathematics, 2021
We consider biclustering that clusters both samples and features and propose efficient convex biclustering procedures. The convex biclustering algorithm (COBRA) procedure solves twice the standard convex clustering problem that contains a non ...
Jie Chen, Joe Suzuki
doaj   +2 more sources

Applying spectral biclustering to mortality data [PDF]

Risks, 2017
We apply spectral biclustering to mortality datasets in order to capture three relevant aspects: the period, the age and the cohort effects, as their knowledge is a key factor in understanding actuarial liabilities of private life insurance companies ...
Gabriella Piscopo, Marina Resta
doaj   +2 more sources

Evolutionary Mechanism Based Conserved Gene Expression Biclustering Module Analysis for Breast Cancer Genomics [PDF]

Biomedicines
The 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, Yaming Li, Zhengpan Han, Yu Chen, Jinnan Xie, Jianguo Chen, Zhisheng Bi, Jianing Xi   +7 more
doaj   +2 more sources

Dominant Set Biclustering

, 2017
Biclustering, which can be defined as the simultaneous clustering of rows and columns in a data matrix, has received increasing attention in recent years, being applied in many scientific scenarios (e.g.
A. Farinelli, M. Bicego, M. Pelillo, M. Denitto   +3 more
core   +3 more sources

Bayesian biclustering of gene expression data [PDF]

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
doaj   +2 more sources