Nature BiotechnologyBioinformaticsPeer-reviewed journal article
Democratizing Protein Language Model Training, Sharing and Collaboration
Jin SuiD, Zhikai LiiD, Tianli Tao, Chenchen HaniD, Yan HeiD, Fengyuan Dai, Qingyan YuaniD, Yuan GaoiD, Tong SiiD, Xuting ZhangiD, Yuyang ZhouiD, Junjie Shan, Xibin ZhouiD, Xing ChangiD, Shiyu JiangiD, Dacheng MaiD, The OPMC, Anthony GitteriD, Milot MirditaiD, Kevin YangiD, Pascal NotiniD, Debora S. MarksiD, Pranam ChatterjeeiD, Rohit SinghiD, Philip A. RomeroiD, , Sergey OvchinnikoviD
Abstract
Training and deploying large-scale protein language models typically requires deep machine learning expertise -- a barrier for researchers outside this field. SaprotHub overcomes this challenge by offering an intuitive platform that facilitates training and prediction as well as storage and sharing of models. We provide the ColabSaprot framework built on Google Colab which potentially powers hundreds of protein training and prediction applications, enabling researchers to collaboratively build and share customized models.
- Citations
- 35
- FWCI
- 9.86
- Field percentile
- top 1%
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