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Updated: Jun 30, 2025

A Versatile Automated Platform for Micro-scale Cell Stimulation Experiments
Published on: August 6, 2013
DANCE: a deep learning library and benchmark platform for single-cell analysis
Jiayuan Ding1, Renming Liu2, Hongzhi Wen3
1Department of Computer Science and Engineering, Michigan State University, East Lansing, USA. dingjia5@msu.edu.
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.

