A Non-Negative Matrix Factorization-Based Framework for the Analysis of Multi-Class Time-Series Single-Cell RNA-Seq Data

A Non-Negative Matrix Factorization-Based Framework for the Analysis of Multi-Class Time-Series Single-Cell RNA-Seq Data

The development of single-cell RNA sequencing (scRNA-seq) has enabled gene expression to be quantified at single-cell resolution. Such advancement is expected to solve important issues that bulk RNA sequencing could not fully answer, such as inferring cell population heterogeneity, genetic variabili...

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Bibliographic Details
Main Authors: Inuk Jung, Joungmin Choi, Heejoon Chae
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Gene expression
multi-class
single-cell
time-series
Online Access:https://ieeexplore.ieee.org/document/9018223/

Internet

https://ieeexplore.ieee.org/document/9018223/

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