51 citations · 54 across the 3 of their papers we have counts for
3 papers
cs.LG2026
RXNRECer Enables Fine-grained Enzymatic Function Annotation through Active Learning and Protein Language Models
Zhenkun Shi, Jun Zhu, Dehang Wang +7
A key challenge in enzyme annotation is identifying the biochemical reactions catalyzed by proteins. Most existing methods rely on Enzyme Commission (EC) numbers as intermediaries:…
q-bio.MN2024★ 3 cited
A generalizable framework for unlocking missing reactions in genome-scale metabolic networks using deep learning
Xiaoyi Liu, Hongpeng Yang, Chengwei Ai +5
Incomplete knowledge of metabolic processes hinders the accuracy of GEnome-scale Metabolic models (GEMs), which in turn impedes advancements in systems biology and metabolic engine…
cs.LG2022★ 51 cited
ECRECer: Enzyme Commission Number Recommendation and Benchmarking based on Multiagent Dual-core Learning
Zhenkun Shi, Qianqian Yuan, Ruoyu Wang +3
Enzyme Commission (EC) numbers, which associate a protein sequence with the biochemical reactions it catalyzes, are essential for the accurate understanding of enzyme functions and…