A simple mathematical model of cell clustering by chemotaxis.
Sign Up to like & getrecommendations! Published in 2017 at "Mathematical biosciences"
DOI: 10.1016/j.mbs.2017.10.008
Abstract: Chemotaxis is the process by which cells and clusters of cells follow chemical signals in order to combine and form larger clusters. The spreading of the chemical signal from any given cell can be modeled… read more here.
Keywords: clustering chemotaxis; model cell; simple mathematical; cell ... See more keywords
SCMcluster: a high-precision cell clustering algorithm integrating marker gene set with single-cell RNA sequencing data.
Sign Up to like & getrecommendations! Published in 2023 at "Briefings in functional genomics"
DOI: 10.1093/bfgp/elad004
Abstract: Single-cell clustering is the most significant part of single-cell RNA sequencing (scRNA-seq) data analysis. One main issue facing the scRNA-seq data is noise and sparsity, which poses a great challenge for the advance of high-precision… read more here.
Keywords: cell; high precision; marker; cell clustering ... See more keywords
scHybridBERT: integrating gene regulation and cell graph for spatiotemporal dynamics in single-cell clustering
Sign Up to like & getrecommendations! Published in 2024 at "Briefings in Bioinformatics"
DOI: 10.1093/bib/bbae018
Abstract: Abstract Graph learning models have received increasing attention in the computational analysis of single-cell RNA sequencing (scRNA-seq) data. Compared with conventional deep neural networks, graph neural networks and language models have exhibited superior performance by… read more here.
Keywords: single cell; cell clustering; cell; dynamics single ... See more keywords
Robust and efficient single-cell Hi-C clustering with approximate k-nearest neighbor graphs.
Sign Up to like & getrecommendations! Published in 2021 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btab394
Abstract: MOTIVATION Hi-C technology provides insights into the 3D organization of the chromatin, and the single-cell Hi-C method enables researchers to gain knowledge about the chromatin state in individual cell levels. Single-cell Hi-C interaction matrices are… read more here.
Keywords: single cell; efficient single; approximate nearest; robust efficient ... See more keywords
scDRMAE: integrating masked autoencoder with residual attention networks to leverage omics feature dependencies for accurate cell clustering
Sign Up to like & getrecommendations! Published in 2024 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btae599
Abstract: Abstract Motivation Cell clustering is foundational for analyzing the heterogeneity of biological tissues using single-cell sequencing data. With the maturation of single-cell multi-omics sequencing technologies, we can integrate multiple omics data to perform cell clustering,… read more here.
Keywords: masked autoencoder; multi omics; attention; cell clustering ... See more keywords
scAGCI: an anchor graph-based method for cell clustering from integrated scRNA-seq and scATAC-seq data
Sign Up to like & getrecommendations! Published in 2024 at "Briefings in Bioinformatics"
DOI: 10.1101/2024.10.20.619321
Abstract: Cell clustering plays a crucial role in the analysis of single-cell multi-omics research. Despite many methods for multi-omics integrated clustering, challenges such as noise, data sparsity, and biointerpretability analysis hider effective clustering. Recent studies have… read more here.
Keywords: cell; anchor graph; seq; cell clustering ... See more keywords
Mobility-Aware Cell Clustering Mechanism for Self-Organizing Networks
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Access"
DOI: 10.1109/access.2018.2876601
Abstract: Self-Organizing Networks (SON) which automate the mobile networks in a cost-efficient way can provide extensive benefits for mobile network operators that are facing several challenges, such as providing maximum coverage and balanced/efficient usage of spectrum… read more here.
Keywords: clustering mechanism; organizing networks; mobility; mobility aware ... See more keywords
Learning Consistency and Specificity of Cells From Single-Cell Multi-Omic Data
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Journal of Biomedical and Health Informatics"
DOI: 10.1109/jbhi.2024.3370868
Abstract: Advancements in single-cell technologies concomitantly develop the epigenomic and transcriptomic profiles at the cell levels, providing opportunities to explore the potential biological mechanisms. Even though significant efforts have been dedicated to them, it remains challenging… read more here.
Keywords: single cell; consistency; cell clustering; multi omic ... See more keywords
scCompressSA: dual-channel self-attention based deep autoencoder model for single-cell clustering by compressing gene–gene interactions
Sign Up to like & getrecommendations! Published in 2024 at "BMC Genomics"
DOI: 10.1186/s12864-024-10286-2
Abstract: Background Single-cell clustering has played an important role in exploring the molecular mechanisms about cell differentiation and human diseases. Due to highly-stochastic transcriptomics data, accurate detection of cell types is still challenged, especially for RNA-sequencing… read more here.
Keywords: single cell; cell clustering; cell; gene interactions ... See more keywords