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Dual-Space Optimization: Improved Molecule Sequence Design by Latent Prompt Transformer
Feb. 28, 2024, 5:41 a.m. | Deqian Kong, Yuhao Huang, Jianwen Xie, Edouardo Honig, Ming Xu, Shuanghong Xue, Pei Lin, Sanping Zhou, Sheng Zhong, Nanning Zheng, Ying Nian Wu
cs.LG updates on arXiv.org arxiv.org
Abstract: Designing molecules with desirable properties, such as drug-likeliness and high binding affinities towards protein targets, is a challenging problem. In this paper, we propose the Dual-Space Optimization (DSO) method that integrates latent space sampling and data space selection to solve this problem. DSO iteratively updates a latent space generative model and a synthetic dataset in an optimization process that gradually shifts the generative model and the synthetic data towards regions of desired property values. Our …
abstract arxiv cs.lg data design designing molecules optimization paper prompt protein protein targets q-bio.bm sampling solve space targets transformer type updates
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