生物
舞蹈
人类遗传学
水准点(测量)
计算生物学
基因组生物学
深度学习
进化生物学
人工智能
图书馆学
基因组学
计算机科学
遗传学
地图学
视觉艺术
基因组
基因
艺术
地理
作者
Jiayuan Ding,Renming Liu,Hongzhi Wen,Wenzhuo Tang,Zhaoheng Li,Julian Venegas,Runze Su,Dylan Molho,Wei Jin,Yixin Wang,Qiaolin Lu,Lingxiao Li,Wangyang Zuo,Yi Chang,Yuying Xie,Jiliang Tang
标识
DOI:10.1186/s13059-024-03211-z
摘要
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.
科研通智能强力驱动
Strongly Powered by AbleSci AI