Zobrazeno 1 - 10
of 83
pro vyhledávání: '"Song, Zhenqiao"'
Nucleic acid-based drugs like aptamers have recently demonstrated great therapeutic potential. However, experimental platforms for aptamer screening are costly, and the scarcity of labeled data presents a challenge for supervised methods to learn pro
Externí odkaz:
http://arxiv.org/abs/2406.09586
Enzymes are genetically encoded biocatalysts capable of accelerating chemical reactions. How can we automatically design functional enzymes? In this paper, we propose EnzyGen, an approach to learn a unified model to design enzymes across all function
Externí odkaz:
http://arxiv.org/abs/2405.08205
How can we design proteins with desired functions? We are motivated by a chemical intuition that both geometric structure and biochemical properties are critical to a protein's function. In this paper, we propose SurfPro, a new method to generate fun
Externí odkaz:
http://arxiv.org/abs/2405.06693
How can large language models (LLMs) process and translate endangered languages? Many languages lack a large corpus to train a decent LLM; therefore existing LLMs rarely perform well in unseen, endangered languages. On the contrary, we observe that 2
Externí odkaz:
http://arxiv.org/abs/2402.18025
Proteins are macromolecules responsible for essential functions in almost all living organisms. Designing reasonable proteins with desired functions is crucial. A protein's sequence and structure are strongly correlated and they together determine it
Externí odkaz:
http://arxiv.org/abs/2310.04343
Designing novel proteins with desired functions is crucial in biology and chemistry. However, most existing work focus on protein sequence design, leaving protein sequence and structure co-design underexplored. In this paper, we propose GeoPro, a met
Externí odkaz:
http://arxiv.org/abs/2310.02546
Autor:
Xu, Wenda, Wang, Danqing, Pan, Liangming, Song, Zhenqiao, Freitag, Markus, Wang, William Yang, Li, Lei
Automatically evaluating the quality of language generation is critical. Although recent learned metrics show high correlation with human judgement, these metrics can not explain their verdict or associate the scores with defects in generated text. T
Externí odkaz:
http://arxiv.org/abs/2305.14282
Autor:
Song, Zhenqiao, Li, Lei
Designing protein sequences with desired biological function is crucial in biology and chemistry. Recent machine learning methods use a surrogate sequence-function model to replace the expensive wet-lab validation. How can we efficiently generate div
Externí odkaz:
http://arxiv.org/abs/2305.00386
Autor:
Chen, Yiran, Song, Zhenqiao, Wu, Xianze, Wang, Danqing, Xu, Jingjing, Chen, Jiaze, Zhou, Hao, Li, Lei
We introduce MTG, a new benchmark suite for training and evaluating multilingual text generation. It is the first-proposed multilingual multiway text generation dataset with the largest human-annotated data (400k). It includes four generation tasks (
Externí odkaz:
http://arxiv.org/abs/2108.07140
Autor:
Zhang, Yujuan, Lu, Yanni, Wang, Xianchang, Zhang, Yayu, Xu, Wei, Zhou, Yun, Tang, Huili, Zhao, Jingying, Song, Zhenqiao, Lv, Haihong, Wang, Zhifen, Han, Jinlong, Zhu, Yanwei, Zhang, Feng, Tian, Beijing, Wu, Shuang, Shan, Chenggang
Publikováno v:
In Industrial Crops & Products May 2024 211