SVD, discrepancy, and regular structure of contingency tables
, 2013 We will use the factors obtained by correspondence analysis to find biclustering of a contingency table such that the row-column cluster pairs are regular, i.e., they have small discrepancy.
Bolla, Marianna
core +1 more source
Deep learning methods for protein function prediction
PROTEOMICS, Volume 25, Issue 1-2, January 2025.Abstract Predicting protein function from protein sequence, structure, interaction, and other relevant information is important for generating hypotheses for biological experiments and studying biological systems, and therefore has been a major challenge in protein bioinformatics.
Frimpong Boadu +2 more
wiley +1 more source
DPCT: A Dynamic Method for Detecting Protein Complexes From TAP-Aware Weighted PPI Network
Frontiers in Genetics, 2020 Detecting protein complexes from the Protein-Protein interaction network (PPI) is the essence of discovering the rules of the cellular world. There is a large amount of PPI data available, generated from high throughput experimental data.
Ali SabziNezhad, Saeed Jalili
doaj +1 more source
Description of sup- and inf-preserving aggregation functions via families of clusters in data tables
, 2017 Connection between the theory of aggregation functions and formal concept analysis is discussed and studied, thus filling a gap in the literature by building a bridge between these two theories, one of them living in the world of data fusion, the second ...
Halaš, Radomír +2 more
core +1 more source
Computational Methods for Data Integration and Imputation of Missing Values in Omics Datasets
PROTEOMICS, Volume 25, Issue 1-2, January 2025.ABSTRACT Molecular profiling of different omic‐modalities (e.g., DNA methylomics, transcriptomics, proteomics) in biological systems represents the basis for research and clinical decision‐making. Measurement‐specific biases, so‐called batch effects, often hinder the integration of independently acquired datasets, and missing values further hamper the ...
Yannis Schumann +2 more
wiley +1 more source
Context Specific and Differential Gene Co-expression Networks via Bayesian Biclustering.
PLoS Computational Biology, 2016 Identifying latent structure in high-dimensional genomic data is essential for exploring biological processes. Here, we consider recovering gene co-expression networks from gene expression data, where each network encodes relationships between genes that
Chuan Gao +4 more
doaj +1 more source
Genetic subtypes of Alzheimer’s disease are related to differential biomarker and cognitive trajectories [PDF]
Alzheimers DementAbstract Background Alzheimer’s disease (AD) exhibits considerable phenotypic heterogeneity, suggesting the potential existence of subtypes. AD is under substantial genetic influence, thus identifying systematic variation in genetic risk may provide insights into disease origins. We previously identified a genetic heterogeneity across two levels.
Elman J, Schork N, Rangan A.
europepmc +2 more sources
A biclustering algorithm based on a Bicluster Enumeration Tree: application to DNA microarray data
BioData Mining, 2009 Background In a number of domains, like in DNA microarray data analysis, we need to cluster simultaneously rows (genes) and columns (conditions) of a data matrix to identify groups of rows coherent with groups of columns.
Ayadi Wassim +2 more
doaj +1 more source
An evaluation study of biclusters visualization techniques of gene expression data
Journal of Integrative Bioinformatics, 2021 Biclustering is a non-supervised data mining technique used to analyze gene expression data, it consists to classify subgroups of genes that have similar behavior under subgroups of conditions.
Aouabed Haithem +2 more
doaj +1 more source
Mining Biclusters of Similar Values with Triadic Concept Analysis [PDF]
, 2011 Biclustering numerical data became a popular data-mining task in the beginning of 2000's, especially for analysing gene expression data. A bicluster reflects a strong association between a subset of objects and a subset of attributes in a numerical ...
Kaytoue, Mehdi +4 more
core +3 more sources