Combining Gene Ontology With Deep Neural Networks to Enhance the Clustering of Single Cell RNA-Seq Data

BMC Bioinformatics - United Kingdom
doi 10.1186/s12859-019-2769-6
Full Text
Abstract

Available in full text

Date
Authors
Publisher

Springer Science and Business Media LLC

Related search

Single Cell RNA-seq Data Clustering Using TF-IDF Based Methods

BMC Genomics
BiotechnologyGenetics
2018English

A Hybrid Clustering Algorithm for Identifying Cell Types From Single-Cell RNA-Seq Data

Genes
Genetics
2019English

CIDR: Ultrafast and Accurate Clustering Through Imputation for Single-Cell RNA-seq Data

Genome Biology
2017English

Using Transfer Learning From Prior Reference Knowledge to Improve the Clustering of Single-Cell RNA-Seq Data

Scientific Reports
Multidisciplinary
2019English

Iterative Transfer Learning With Neural Network for Clustering and Cell Type Classification in Single-Cell RNA-seq Analysis

2020English

DTWscore: Differential Expression and Cell Clustering Analysis for Time-Series Single-Cell RNA-seq Data

BMC Bioinformatics
BiochemistryApplied MathematicsComputer Science ApplicationsStructural BiologyMolecular Biology
2017English

An Interpretable Framework for Clustering Single-Cell RNA-Seq Datasets

BMC Bioinformatics
BiochemistryApplied MathematicsComputer Science ApplicationsStructural BiologyMolecular Biology
2018English

Alignment of Time-Course Single-Cell RNA-seq Data With CAPITAL

2019English

Single-Cell RNA-seq Imputation Using Generative Adversarial Networks

2020English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2024 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy