Abstract Multimodal protein language models (PLMs) deliver strong performance on mutation-effect prediction, but training such models from scratch demands substantial computational resources. In this paper, we propose a fine-tuning framework called InstructPLM-mu and investigate the question: Can a pretrained sequence-...
Jun-De Xu, Ya-Pin Shi, Li-Jun Lang et al.· Briefings in Bioinformatics· 0 citations
The database is built on direct literature investigation by human experts and serves as a crucial tool for studying structures and functions of STRs in cancers and neurodegenerative diseases, supporting research on structural polymorphisms and pathogenic mechanisms of STRs, and facilitating drug design targeting STRs f...
Ka-Si Jie, An-Qi Song, Yang Wang et al.· International Journal of Mol...· 0 citations
OmniMol is presented, a framework using hypergraphs to improve predictions of molecular properties, addressing challenges of imperfect data annotation and enhancing model explainability, and achieves state-of-the-art performance in properties prediction.