- Development of Biclustering Techniques for Gene Expression Data ...🔍
- Performance evaluation and enhancement of biclustering algorithms🔍
- Biclustering Using Message Passing🔍
- Evolutionary biclustering of gene expressions🔍
- Prognostic Prediction through Biclustering|Based Classification of ...🔍
- biclustermd🔍
- Biclustering🔍
- Identifying gene|specific subgroups🔍
Pairwise gene GO|based measures for biclustering of high ...
Development of Biclustering Techniques for Gene Expression Data ...
Other researchers examined the external relationship among modules, e.g., grouped modules of host proteins based on a distance measure to form higher-level ...
Performance evaluation and enhancement of biclustering algorithms
Keywords: Biclustering, Evaluation, Gene Expression Pattern Recognition, Validation Measures. ... based biclustering algorithm for analysis of ...
Biclustering Using Message Passing
Applied to three gene expression datasets, our method found biclusters of high quality in terms of cluster size and density. 2 Methods. 2.1 Problem statement.
Evolutionary biclustering of gene expressions - ACM Digital Library
Biclustering or simultaneous clustering of both genes and conditions is challenging particularly for the analysis of high-dimensional gene expression data in ...
MIBiClus: Mutual Information based Biclustering Algorithm - CiteSeerX
The gene expression data has the expression of thousands of genes under thousands of conditions. Standard clustering algorithms like k-means clustering work ...
Prognostic Prediction through Biclustering-Based Classification of ...
In this context, biclustering algorithms emerged as an important tool to discover local expression patterns in biomedical applications, and CCC- ...
biclustermd: An R Package for Biclustering with Missing Values
For completeness we give an overview of their algorithm here. Notation. • X is a data matrix with I rows and J columns. Xij is a response measure of row i ...
Biclustering, block clustering, Co-clustering or two-mode clustering is a data mining technique which allows simultaneous clustering of the rows and columns ...
Identifying gene-specific subgroups: an alternative to biclustering
Keywords: Gene expression analysis, Biclustering, Gene enrichment analysis, Identification of significant GO terms. Background. Gene expression data is ...
Biclustering with dominant sets - profs.scienze.univr.it
a group of rows that exhibit high similarities with a group of columns, hence a bicluster. ... Calvo , A new measure for gene expression biclustering based on non ...
An effective measure for assessing the quality of biclusters
Biclustering is becoming a popular technique for the study of gene expression data. This is mainly due to the capability of biclustering to address the data ...
Uncovering hidden gene-trait patterns through biclustering ... - bioRxiv
b) Biclusters were grouped based on gene overlap using a clustering algorithm on the Jaccard similarity coe cient. c) Gene Ontology (GO) and ...
Biclustering with Background Knowledge using Formal Concept ...
To this end, query-based biclustering algorithms have been recently developed in the context of microarray data; these algorithms utilize a set of seed genes ...
Boolean Reasoning–Based Biclustering for Shifting Pattern Extraction
A new measure for gene expression biclustering based ... Pairwise gene GO-based measures for biclustering of high- dimensional expression data.
Our method, spectral biclustering, is based on the observation that checkerboard structures in ... eigenvectors, for example, using a pairwise measure such ...
Similarity Measures for Comparing Biclusterings - GitHub Pages
The biclustering paradigm has become popular in the gene expression field, as a set of genes will rarely be similar to each other under all investigated ...
a comprehensive review of biclustering applications in biological ...
Biclustering is deemed as a powerful tool that could identify novel target genes, indicated drugs or biomarkers of drug responses, in which the principles of ...
A GPU-accelerated algorithm for biclustering analysis and detection ...
Here we propose a GPU-accelerated biclustering algorithm, based on searching for the largest Condition-dependent Correlation Subgroups (CCS) for each gene in ...
Context Specific and Differential Gene Co-expression Networks via ...
Compared with related biclustering methods, BicMix recovers latent structure with higher precision across diverse simulation scenarios as compared to state ...
Pattern Based Co-Regulated Biclustering of Gene Expression Data
context of microarray gene-expression data analysis (3, 4, 5, 6). 7. Each microarray provides expression measurements for thousands of genes. 8.