刘育松｜哈尔滨医科大学｜学者主页

2025

TriCLFF: a multi-modal feature fusion framework using contrastive learning for spatial domain identification

Fenglan Pang, Guangfu Xue, Wenyi Yang, Yideng Cai, Jinhao Que, Haoxiu Sun, Pingping Wang, Shuaiyu Su, Xiyun Jin, Qian Ding, Zuxiang Wang, Meng Luo, Yuexin Yang, Lin Yi, Renjie Tan, Yusong Liu, Zhaochun Xu, Qinghua Jiang

Briefings in Bioinformatics

DOI

2024

Dimension reduction, cell clustering, and cell–cell communication inference for single-cell transcriptomics with DcjComm

Qian Ding, Wenyi Yang, Guangfu Xue, Hongxin Liu, Yideng Cai, Jinhao Que, Xiyun Jin, Meng Luo, Fenglan Pang, Yuexin Yang, Yi Lin, Yusong Liu, Haoxiu Sun, Renjie Tan, Pingping Wang, Zhaochun Xu, Qinghua Jiang

Genome biology

DOI

2023

Identify potential driver genes for PAX-FOXO1 fusion-negative rhabdomyosarcoma through frequent gene co-expression network mining

Xiaohui Zhan, Yusong Liu, Asha Jacob Jannu, Shaoyan Huang, Bo Ye, Wei Wei, P. Pandya, Xiu-Fen Ye, K. Pollok, J. Renbarger, Kun Huang, Jie Zhang

Frontiers in Oncology

DOI

2022

多数据整合基因共表达网络的构建与分析方法研究

刘育松

《哈尔滨工程大学》

2022

Distance correlation application to gene co-expression network analysis

Jie Hou, Xiu-Fen Ye, Weixing Feng, Qiaosheng Zhang, Yatong Han, Yusong Liu, Yu Li, Y. Wei

BMC Bioinformatics

DOI

2022

UIR-Net: A Simple and Effective Baseline for Underwater Image Restoration and Enhancement

Xinkui Mei, Xiufen Ye, Xiaofeng Zhang, Yusong Liu, Junting Wang, Jun Hou, Xuli Wang

Remote Sensing

DOI

2021

TPSC: a module detection method based on topology potential and spectral clustering in weighted networks and its application in gene co-expression module discovery

Yusong Liu, Xiu-Fen Ye, Christina Y. Yu, Wei Shao, Jie Hou, Weixing Feng, Jie Zhang, Kun Huang

BMC Bioinformatics

DOI

2021

TPQCI: A Topology Potential-Based Method to Quantify Functional Influence of Copy Number Variations.

Yusong Liu, Xiu-Fen Ye, Xiaohui Zhan, Christina Y. Yu, Jie Zhang, Kun Huang

Methods

DOI

2021

SPCS: a spatial and pattern combined smoothing method for spatial transcriptomic expression

Yusong Liu, Tongxin Wang, Ben Duggan, Michael F. Sharpnack, Kun Huang, Jie Zhang, Xiu-Fen Ye, T. Johnson

bioRxiv

DOI

2021

Differential Gene Expression and Functional Enrichment Analysis of Smoothed PDAC Spatial Transcriptomics Slides

Ben Duggan, Yusong Liu, Tongxin Wang, Jie Zhang, T. Johnson, Xiu-Fen Ye, Kun Huang

Proceedings of IMPRS

DOI

2020

A pan-kidney cancer study identifies subtype specific perturbations on pathways with potential drivers in renal cell carcinoma

Xiaohui Zhan, Yusong Liu, Christina Y. Yu, Tian-Fu Wang, Jie Zhang, Dong Ni, Kun Huang

BMC Medical Genomics

DOI

2019

Integration of molecular features with clinical information for predicting outcomes for neuroblastoma patients

Yatong Han, Xiu-Fen Ye, Chao Wang, Yusong Liu, Siyuan Zhang, Weixing Feng, Kun Huang, Jie Zhang

Biology Direct

DOI

刘育松

精选作品

期刊论文

TriCLFF: a multi-modal feature fusion framework using contrastive learning for spatial domain identification

Dimension reduction, cell clustering, and cell–cell communication inference for single-cell transcriptomics with DcjComm

Identify potential driver genes for PAX-FOXO1 fusion-negative rhabdomyosarcoma through frequent gene co-expression network mining

多数据整合基因共表达网络的构建与分析方法研究

Distance correlation application to gene co-expression network analysis

UIR-Net: A Simple and Effective Baseline for Underwater Image Restoration and Enhancement

TPSC: a module detection method based on topology potential and spectral clustering in weighted networks and its application in gene co-expression module discovery

TPQCI: A Topology Potential-Based Method to Quantify Functional Influence of Copy Number Variations.

SPCS: a spatial and pattern combined smoothing method for spatial transcriptomic expression

Differential Gene Expression and Functional Enrichment Analysis of Smoothed PDAC Spatial Transcriptomics Slides

A pan-kidney cancer study identifies subtype specific perturbations on pathways with potential drivers in renal cell carcinoma

Integration of molecular features with clinical information for predicting outcomes for neuroblastoma patients

研究方向