Dirichlet process mixture models for single-cell RNA-seq clustering | Citedby Results | Biology Open | The Company of Biologists

Skip to Main Content

Skip Nav Destination

Dirichlet process mixture models for single-cell RNA-seq clustering

Biol Open (2022) 11 (4): bio059001.

This article has been cited by the following articles in journals that are participating in Crossref Cited-by Linking.

scBubbletree: computational approach for visualization of single cell RNA-seq data

Simo Kitanovski
Yingying Cao
Dimitris Ttoouli
Farnoush Farahpour
Jun Wang
Daniel Hoffmann

BMC Bioinformatics (2024) 25 (1)

Cell-to-cell distance that combines gene expression and gene embeddings

Fangfang Guo
Dailin Gan
Jun Li

Computational and Structural Biotechnology Journal (2024) 23: 3929.

An interpretable single-cell RNA sequencing data clustering method based on latent Dirichlet allocation

Qi Yang
Zhaochun Xu
Wenyang Zhou
Pingping Wang
Qinghua Jiang
Liran Juan

Briefings in Bioinformatics (2023) 24 (4)

Hot Topic Recognition of Health Rumors Based on Anti-Rumor Articles on the WeChat Official Account Platform: Topic Modeling

Ziyu Li
Xiaoqian Wu
Lin Xu
Ming Liu
Cheng Huang

Journal of Medical Internet Research (2023) 25: e45019.

Sprod for de-noising spatially resolved transcriptomics data based on position and image information

Yunguan Wang
Bing Song
Shidan Wang
Mingyi Chen
Yang Xie
Guanghua Xiao
Li Wang
Tao Wang

Nature Methods (2022) 19 (8): 950.