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DANCE:单细胞分析的深度学习库和基准平台。

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

机构信息

Department of Computer Science and Engineering, Michigan State University, East Lansing, USA.

Department of Computational Mathematics, Science and Engineering, Michigan State University, East Lansing, USA.

出版信息

Genome Biol. 2024 Mar 19;25(1):72. doi: 10.1186/s13059-024-03211-z.

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.

摘要

DANCE 是第一个用于访问和评估众多单细胞分析任务基准数据集计算方法的通用、可扩展的基准平台。目前,DANCE 支持 3 个模块和 8 个流行任务,在 21 个基准数据集上有 32 个最先进的方法。人们只需少量工作,例如只使用一个命令行,就可以轻松地在主要基准数据集上重现支持算法的结果。此外,DANCE 还为研究人员提供了一个深度学习架构和工具的生态系统,以方便他们自己的模型开发。DANCE 是一个开源的 Python 包,欢迎各种贡献。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83f4/10949782/9963725f5674/13059_2024_3211_Fig1_HTML.jpg

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