1 code implementation • 19 Mar 2024 • Qiangguo Jin, Hui Cui, Changming Sun, Yang song, Jiangbin Zheng, Leilei Cao, Leyi Wei, Ran Su
To address these issues, we first propose a novel inter- and intra-uncertainty regularization method to measure and constrain both inter- and intra-inconsistencies in the teacher-student architecture.
no code implementations • 13 Jun 2023 • Yu Wang, Jingjie Zhang, Junru Jin, Leyi Wei
Molecular representation learning (MRL) is a fundamental task for drug discovery.
no code implementations • 3 Dec 2022 • Chao Pang, Yu Wang, Yi Jiang, Ruheng Wang, Ran Su, Leyi Wei
Moreover, case study results on targeted molecule generation for the SARS-CoV-2 main protease (Mpro) show that by integrating molecule docking into our model as chemical priori, we successfully generate new small molecules with desired drug-like properties for the Mpro, potentially accelerating the de novo design of Covid-19 drugs.
no code implementations • 6 Nov 2022 • Fengsheng Wang, Leyi Wei
Then the multi-grained feature learning is utilized to perceive object-level semantics relation of multi-scale features by introducing the shunted self-attention.
2 code implementations • Genome Biology 2022 • Junru Jin, Yingying Yu, Ruheng Wang, Xin Zeng, Chao Pang, Yi Jiang, Zhongshen Li, Yutong Dai, Ran Su, Quan Zou, Kenta Nakai, Leyi Wei
In this study, we propose iDNA-ABF, a multi-scale deep biological language learning model that enables the interpretable prediction of DNA methylations based on genomic sequences only.
1 code implementation • 11 Oct 2022 • Tianling Liu, Ran Su, Changming Sun, Xiuting Li, Leyi Wei
Next, we developed a survival prediction model, named DeepConvAttentionSurv (DCAS), which was able to extract patch-level features, removed less discriminative clusters and predicted the EOC survival precisely.
1 code implementation • 6 Oct 2022 • Yu Wang, Chao Pang, Yuzhe Wang, Yi Jiang, Junru Jin, Sirui Liang, Quan Zou, Leyi Wei
Leveraging artificial intelligence for automatic retrosynthesis speeds up organic pathway planning in digital laboratories.
1 code implementation • 20 Apr 2021 • Qiangguo Jin, Hui Cui, Changming Sun, Zhaopeng Meng, Leyi Wei, Ran Su
DASC-Net consists of a novel attention and feature domain enhanced domain adaptation model (AFD-DA) to solve the domain shifts and a self-correction learning process to refine segmentation results.
1 code implementation • 4 Nov 2018 • Qiangguo Jin, Zhaopeng Meng, Changming Sun, Leyi Wei, Ran Su
Automatic extraction of liver and tumor from CT volumes is a challenging task due to their heterogeneous and diffusive shapes.
no code implementations • 3 Nov 2018 • Qiangguo Jin, Zhaopeng Meng, Tuan D. Pham, Qi Chen, Leyi Wei, Ran Su
Results show that more detailed vessels are extracted by DUNet and it exhibits state-of-the-art performance for retinal vessel segmentation with a global accuracy of 0. 9697/0. 9722/0. 9724 and AUC of 0. 9856/0. 9868/0. 9863 on DRIVE, STARE and CHASE_DB1 respectively.
Ranked #4 on
Retinal Vessel Segmentation
on STARE