Network-based Structural Learning Nonnegative Matrix Factorization Algorithm for Clustering of scRNA-seq Data-Reference-Cited by-同舟云学术

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Network-based Structural Learning Nonnegative Matrix Factorization Algorithm for Clustering of scRNA-seq Data

Published:2022 Issue: Volume: Page:1-1
ISSN:1545-5963
Container-title:IEEE/ACM Transactions on Computational Biology and Bioinformatics
language:
Short-container-title:IEEE/ACM Trans. Comput. Biol. and Bioinf.

Author:

Wu Weming,Ma Xiaoke

Funder

Key Research and Development Program of Gansu

Fundamental Research Funds for the Central Universities

Shaanxi Natural Science Funds for Distinguished Young Schalor

Innovation Fund of Xidian University

Key Research and Development Program of Shaanxi

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Genetics,Biotechnology

Link

http://xplorestaging.ieee.org/ielx7/8857/4359833/09739884.pdf?arnumber=9739884

Reference55 articles.

1. SAME-clustering: Single-cell Aggregated Clustering via Mixture Model Ensemble

2. CIDR: Ultrafast and accurate clustering through imputation for single-cell RNA-seq data

3. Color channel encoding with NMF for face recognition

4. Learning the parts of objects by non-negative matrix factorization

5. A tutorial on spectral clustering

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1. HGN2T: A Simple but Plug-and-Play Framework Extending HGNNs on Heterogeneous Temporal Graphs;IEEE Transactions on Big Data;2024-10

2. Single-cell RNA sequencing data analysis utilizing multi-type graph neural networks;Computers in Biology and Medicine;2024-09

3. Graph-Regularized Non-Negative Matrix Factorization for Single-Cell Clustering in scRNA-Seq Data;IEEE Journal of Biomedical and Health Informatics;2024-08

4. The rise of nonnegative matrix factorization: Algorithms and applications;Information Systems;2024-07

5. SCSMD: Single Cell Consistent Clustering based on Spectral Matrix Decomposition;Briefings in Bioinformatics;2024-05-23

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