公开(公告)号：US20240347142A1

公开(公告)日：2024-10-17

申请号：US18632639

申请日：2024-04-11

Applicant: Lemon Inc. ,  Beijing Youzhuju Network Technology Co., Ltd.

Inventor： Yuwei YANG ,  Xiangxin ZHOU ,  Yu BAO ,  Jiaqi GUAN

IPC: G16C20/50 ,  G16C20/30

CPC classification number: G16C20/50 ,  G16C20/30

Abstract: Embodiments of the present disclosure relate to a method and an electronic device for ligand generation. The method comprises: obtaining a trained ligand generation model, wherein the trained ligand generation model is generated based on decomposition of a ligand by modeling of atom positions, atom types, and chemical bonds; and obtaining, based on a target protein, a target ligand molecule corresponding to the target protein by using the trained ligand generation model. According to the method, the ligand generation model in the embodiments of the present disclosure considers the decomposition of the ligand and also models the chemical bonds, so that it can generate the target ligand molecule with higher affinity.

公开(公告)号：US20250053808A1

公开(公告)日：2025-02-13

申请号：US18797228

申请日：2024-08-07

Applicant: Beijing Youzhuju Network Technology Co., Ltd.

Inventor： Zaixiang ZHENG ,  Jiasheng YE ,  Yu BAO

IPC: G06N3/08

Abstract: The embodiment of the disclosure provides a method, apparatus, electronic device, and storage medium for data processing. The method includes: receiving a corpus to be processed; obtaining a target prediction result corresponding to the corpus to be processed by processing the corpus to be processed based on a target diffusion language model, wherein the target diffusion language model is obtained by training based on a plurality of corpus samples, and a mask corpora in the corpus samples corresponds to different mask rates; and displaying the target prediction result. According to the technical solution of the embodiment of the disclosure, the effect of making the target diffusion language model can process the corpus data based on the principle of diffusion model and the obtained corpus data processing results can meet the requirements of corpus processing tasks is implemented.