日期:
2020 年 — 2026 年
2020
2021
2022
2023
2024
2025
2026
影响因子:

ProteoformDB: an integrative database for functional roles of proteoforms

ProteoformDB:一个整合蛋白质异构体功能作用的数据库

Luo, Hanwen; Qiu, Sichao; Guo, Maozu; Xin, Beibei; Wang, Jun; Yu, Guoxian

TRAPT: a multi-stage fused deep learning framework for predicting transcriptional regulators based on large-scale epigenomic data

TRAPT:一种基于大规模表观基因组数据预测转录调控因子的多阶段融合深度学习框架

Zhang, Guorui; Song, Chao; Yin, Mingxue; Liu, Liyuan; Zhang, Yuexin; Li, Ye; Zhang, Jianing; Guo, Maozu; Li, Chunquan

sc2GWAS: a comprehensive platform linking single cell and GWAS traits of human

sc2GWAS:一个连接人类单细胞和全基因组关联研究(GWAS)特征的综合平台

Yin, Mingxue; Feng, Chenchen; Yu, Zhengmin; Zhang, Yuexin; Li, Ye; Wang, Xuan; Song, Chao; Guo, Maozu; Li, Chunquan

HetFCM: functional co-module discovery by heterogeneous network co-clustering

HetFCM:基于异构网络共聚类的功能共模块发现

Tan, Haojiang; Guo, Maozu; Chen, Jian; Wang, Jun; Yu, Guoxian

KnockTF 2.0: a comprehensive gene expression profile database with knockdown/knockout of transcription (co-)factors in multiple species

KnockTF 2.0:一个包含多种物种转录(辅)因子敲低/敲除信息的综合基因表达谱数据库

Feng, Chenchen; Song, Chao; Song, Shuang; Zhang, Guorui; Yin, Mingxue; Zhang, Yuexin; Qian, Fengcui; Wang, Qiuyu; Guo, Maozu; Li, Chunquan

GWASTool: A web pipeline for detecting SNP-phenotype associations

GWASTool:用于检测SNP-表型关联的网络流程

Wang, Xin; Xin, Beibei; Guo, Maozu; Yu, Guoxian; Wang, Jun

GEFormerDTA: drug target affinity prediction based on transformer graph for early fusion

GEFormerDTA:基于Transformer图的药物靶点亲和力预测,用于早期融合

Liu, Youzhi; Xing, Linlin; Zhang, Longbo; Cai, Hongzhen; Guo, Maozu

Detection of Road Crack Images Based on Multistage Feature Fusion and a Texture Awareness Method

基于多阶段特征融合和纹理感知方法的道路裂缝图像检测

Guo, Maozu; Tian, Wenbo; Li, Yang; Sui, Dong

Equivariant score-based generative diffusion framework for 3D molecules

面向三维分子的等变评分生成扩散框架

Zhang, Hao; Liu, Yang; Liu, Xiaoyan; Wang, Cheng; Guo, Maozu

A Deep Learning Model with Signal Decomposition and Informer Network for Equipment Vibration Trend Prediction

基于信号分解和信息网络的深度学习模型用于设备振动趋势预测

Wang, Huiyun; Guo, Maozu; Tian, Le