DANCE: a deep learning library and benchmark platform for single-cell analysis

3Citations
Citations of this article
37Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

DANCE is the first standard, generic, and extensible benchmark platform for accessing and evaluating computational methods across the spectrum of benchmark datasets for numerous single-cell analysis tasks. Currently, DANCE supports 3 modules and 8 popular tasks with 32 state-of-art methods on 21 benchmark datasets. People can easily reproduce the results of supported algorithms across major benchmark datasets via minimal efforts, such as using only one command line. In addition, DANCE provides an ecosystem of deep learning architectures and tools for researchers to facilitate their own model development. DANCE is an open-source Python package that welcomes all kinds of contributions.

References Powered by Scopus

Learning representations by back-propagating errors

20930Citations
N/AReaders
Get full text

Fast unfolding of communities in large networks

15123Citations
N/AReaders
Get full text

Integrated analysis of multimodal single-cell data

6582Citations
N/AReaders
Get full text

Cited by Powered by Scopus

scDFN: enhancing single-cell RNA-seq clustering with deep fusion networks

1Citations
N/AReaders
Get full text

Benchmarking single-cell cross-omics imputation methods for surface protein expression

0Citations
N/AReaders
Get full text

Single-cell genomics and spatial transcriptomics in islet transplantation for diabetes treatment: advancing towards personalized therapies

0Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Ding, J., Liu, R., Wen, H., Tang, W., Li, Z., Venegas, J., … Tang, J. (2024). DANCE: a deep learning library and benchmark platform for single-cell analysis. Genome Biology, 25(1). https://doi.org/10.1186/s13059-024-03211-z

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 13

68%

Researcher 4

21%

Professor / Associate Prof. 2

11%

Readers' Discipline

Tooltip

Biochemistry, Genetics and Molecular Bi... 8

42%

Computer Science 5

26%

Agricultural and Biological Sciences 4

21%

Engineering 2

11%

Article Metrics

Tooltip
Mentions
News Mentions: 2

Save time finding and organizing research with Mendeley

Sign up for free