孙慧妍｜吉林大学｜学者主页

2026

Rethinking Covariate Selection for Causal Effect Inference: The Primacy of Proximal Confounders

Yonghe Zhao, Yuezhu Wang, Dan Han, Chao Ma, Huiyan Sun

ACM Transactions on Knowledge Discovery from Data

DOI

2025

VLUCI: Variational Learning of Unobserved Confounders for Counterfactual Inference

Yonghe Zhao, Yuezhu Wang, Shuai Fu, Yun Peng, Huiyan Sun

Communications in computer and information science

DOI

2025

Cancer gene identification through integrating causal prompting large language model with omics data–driven causal inference

Haolong Zeng, Chaoyi Yin, Chunyang Chai, Yuezhu Wang, Qi Dai, Huiyan Sun

Briefings in Bioinformatics

DOI

2024

ScMOGAE: A Graph Convolutional Autoencoder-Based Multi-omics Data Integration Framework for Single-Cell Clustering

Benjie Zhou, H. Jiang, Yuezhu Wang, Yujie Gu, Huiyan Sun

International Symposium on Bioinformatics Research and Applications

DOI

2024

SSGCN: A Spatial Domain Identification Framework Based on Graph Convolutional Neural Network with Adaptively Reweighting Edges

Wenhui Du, Chunyang Chai, Yujie Gu, Shuang Hao, Huiyan Sun

International Conference on Bioinformatics & Computational Biology

DOI

2024

Identifying cancer prognosis genes through causal learning

Siwei Wu, Chaoyi Yin, Yuezhu Wang, Huiyan Sun

Briefings in Bioinformatics

DOI

2024

Avoiding the Unconfoundednes Assumption: Counterfactual Inference Considering Unobserved Confounders

Yonghe Zhao, Yun Peng, Huiyan Sun

Communications in computer and information science

DOI

2024

Estimating Individual Causal Treatment Effect by Variable Decomposition

Hongyang Jiang, Yonghe Zhao, Qiang Huang, Yangkun Cao, Huiyan Sun, Yi Chang

DOI

2024

SLIVER: Unveiling large scale gene regulatory networks of single-cell transcriptomic data through causal structure learning and modules aggregation

Hongyang Jiang, Yuezhu Wang, Chaoyi Yin, Hao Pan, Liqun Chen, Ke Feng, Yi Chang, Huiyan Sun

Computers in Biology and Medicine

DOI

2024

A Comprehensive Comparison between Primary Liver Cancer and Liver Metastases through scRNA-Seq Data Analysis

Shuang Hao, Liqun Chen, Wenhui Du, Huiyan Sun

Metabolites

DOI

2023

Gene regulatory network inference based on causal discovery integrating with graph neural network

Ke Feng, Hongyang Jiang, Chaoyi Yin, Huiyan Sun

Quantitative Biology

DOI

2023

A comprehensive tool for tumor precision medicine with pharmaco-omics data analysis

Yijun Liu, Fu Song, Zhi Li, Liang Chen, Ying Xu, Huiyan Sun, Yi Chang

Frontiers in Pharmacology

DOI

2023

Editorial: Statistical methods for genome-wide association studies (GWAS) and transcriptome-wide association studies (TWAS) and their applications

Mengting Shao, Zilong Zhang, Huiyan Sun, Jing-Ni He, Jue-Xin Wang, Qing-Run Zhang, Chen Cao

Frontiers in Genetics

DOI

2023

Identification of Cancer Driver Genes by Integrating Multiomics Data with Graph Neural Networks

Hongzhi Song, Chaoyi Yin, Zhuopeng Li, Ke Feng, Yangkun Cao, Yujie Gu, Huiyan Sun

Metabolites

DOI

2023

Improve Robustness of Graph Neural Networks: Multi-hop Neighbors Meet Homophily-based Truncation Defense

Yujie Gu, Huiyan Sun, Yan-Song Wang, Haobo Shi

IEEE International Joint Conference on Neural Network

DOI

2023

Contrastive self-supervised graph convolutional network for detecting the relationship among lncRNAs, miRNAs, and diseases

Nan Sheng, Lan Huang, Yan Wang, Ling Gao, Huiyan Sun, Xuping Xie

IEEE International Conference on Bioinformatics and Biomedicine

DOI

2023

Modeling Interference for Individual Treatment Effect Estimation from Networked Observational Data

Qiang Huang, Jing Ma, Jundong Li, Ruocheng Guo, Huiyan Sun, Yi Chang

ACM Transactions on Knowledge Discovery from Data

DOI

2023

SemiITE: Semi-supervised Individual Treatment Effect Estimation via Disagreement-Based Co-training

Qiang Huang, Jing Ma, Jundong Li, Huiyan Sun, Yi Chang

Lecture notes in computer science

DOI

2022

Molecular Subtyping of Cancer Based on Distinguishing Co-Expression Modules and Machine Learning

Peishuo Sun, Ying Wu, Chaoyi Yin, H. Jiang, Ying Xu, Huiyan Sun

Frontiers in Genetics

DOI

2022

Molecular Subtyping of Cancer Based on Robust Graph Neural Network and Multi-Omics Data Integration

Chaoyi Yin, Yangkun Cao, Peishuo Sun, Hengyuan Zhang, Zhi Li, Ying Xu, Huiyan Sun

Frontiers in Genetics

DOI

2022

Identification of key somatic oncogenic mutation based on a confounder-free causal inference model

Yijun Liu, Ji Sun, Huiyan Sun, Yi Chang

PLoS Comput. Biol.

DOI

2021

An AutoEncoder-Based Matrix Factorization Approach to Estimating Cell Proportion from Bulk Tumor RNA-seq Data

Yingze Xu, Yan Wang, Xuping Xie, Fei-Long Wang, Qiong Chen, Huiyan Sun

IEEE International Conference on Bioinformatics and Biomedicine

DOI

2021

DBPOM: a comprehensive database of pharmaco-omics for cancer precision medicine

Yijun Liu, Fu Song, Zhi Li, Liang Chen, Ying Xu, Huiyan Sun, Yi Chang

bioRxiv

DOI

2021

A causality-inspired feature selection method for cancer imbalanced high-dimensional data

Yijun Liu, Q. Huang, Huiyan Sun, Yi Chang

bioRxiv

DOI

2021

A Breast Cancer Patients’ Survival Prediction Model Using mRMR Feature Selection with Artificial Neural Network

Xing Wei, Kangping Wang, Huiyan Sun, Yan Wang

International Conference on Computer Science and Application Engineering (CSAE)

DOI

2020

Metabolic reprogramming in cancer: the bridge that connects intracellular stresses and cancer behaviors

Yi Zhou, Huiyan Sun, Ying Xu

National Science Review

DOI

2020

The bioinformatics toolbox for circRNA discovery and analysis

Liang Chen, Changliang Wang, Huiyan Sun, Jue-Xin Wang, Yan-Chun Liang, Yan Wang, Garry Wong

Briefings Bioinform.

DOI

2020

Identification of Cancer Development Related Pathways Based on Co-Expression Analyses

H. Jiang, Zhihang Wang, Chaoyi Yin, Peishuo Sun, Ying Xu, Huiyan Sun

IEEE International Conference on Bioinformatics and Biomedicine

DOI

2020

Unsupervised Nonlinear Feature Selection from High-Dimensional Signed Networks

Q. Huang, Tingyu Xia, Huiyan Sun, Makoto Yamada, Yi Chang

AAAI Conference on Artificial Intelligence

DOI

2020

CaMeRe: A Novel Tool for Inference of Cancer Metabolic Reprogramming

Haoyang Li, Juexiao Zhou, Huiyan Sun, Zhaowen Qiu, Xin Gao, Ying Xu

Frontiers in Oncology

DOI

2019

Warburg Effects in Cancer and Normal Proliferating Cells: Two Tales of the Same Name

Huiyan Sun, Liang Chen, Sha Cao, Yan-Chun Liang, Ying Xu

Genomics, Proteomics & Bioinformatics

DOI

2019

Link Prediction Based on Extended Local Path Gain in Protein-Protein Interaction Network

Huiyan Sun, Yanchun Liang, Yan Wang, Liang Chen, W. Du, Yuexu Jiang, Xiao-Hu Shi

Tehnički Vjesnik

DOI

2019

Trends in the development of miRNA bioinformatics tools

Liang Chen, Liisa Heikkinen, Changliang Wang, Yang Yang, Huiyan Sun, Garry Wong

Briefings Bioinform.

DOI

2019

Multi-Classification of Cancer Samples Based on Co-Expression Analyses

H. Jiang, Q. Huang, Liang Chen, Zhi Li, Ying Xu, Huiyan Sun, Yi Chang

IEEE International Conference on Bioinformatics and Biomedicine

DOI

2018

数据挖掘在癌症细胞增殖机制分析中的应用研究

孙慧妍

《吉林大学》

2014

Identification of Essential Proteins Based on Ranking Edge-Weights in Protein-Protein Interaction Networks

Yan Wang, Huiyan Sun, W. Du, E. Blanzieri, G. Viero, Ying Xu, Yanchun Liang

PLoS ONE

DOI

2014

Essential protein identification based on essential protein-protein interaction prediction by integrated edge weights

Yuexu Jiang, Yan Wang, Wei Pang, Liang Chen, Huiyan Sun, Yan-Chun Liang, E. Blanzieri

IEEE International Conference on Bioinformatics and Biomedicine

DOI

2013

Silhouette Index Supervised Affinity Propagation Clustering

Liang Chen, W. Du, Yan Wang, Huiyan Sun, Ying Sun, Yanchun Liang

DOI

2013

An Improved Sum of Edge Clustering Coefficient Method for Essential Protein Identification

Huiyan Sun, Yanchun Liang, Liang Chen, Yan Wang, W. Du, Xiao-Hu Shi

DOI

精选作品

期刊论文

Rethinking Covariate Selection for Causal Effect Inference: The Primacy of Proximal Confounders

VLUCI: Variational Learning of Unobserved Confounders for Counterfactual Inference

Cancer gene identification through integrating causal prompting large language model with omics data–driven causal inference

ScMOGAE: A Graph Convolutional Autoencoder-Based Multi-omics Data Integration Framework for Single-Cell Clustering

SSGCN: A Spatial Domain Identification Framework Based on Graph Convolutional Neural Network with Adaptively Reweighting Edges

Identifying cancer prognosis genes through causal learning

Avoiding the Unconfoundednes Assumption: Counterfactual Inference Considering Unobserved Confounders

Estimating Individual Causal Treatment Effect by Variable Decomposition

SLIVER: Unveiling large scale gene regulatory networks of single-cell transcriptomic data through causal structure learning and modules aggregation

A Comprehensive Comparison between Primary Liver Cancer and Liver Metastases through scRNA-Seq Data Analysis

Gene regulatory network inference based on causal discovery integrating with graph neural network

A comprehensive tool for tumor precision medicine with pharmaco-omics data analysis

Editorial: Statistical methods for genome-wide association studies (GWAS) and transcriptome-wide association studies (TWAS) and their applications

Identification of Cancer Driver Genes by Integrating Multiomics Data with Graph Neural Networks

Improve Robustness of Graph Neural Networks: Multi-hop Neighbors Meet Homophily-based Truncation Defense

Contrastive self-supervised graph convolutional network for detecting the relationship among lncRNAs, miRNAs, and diseases

Modeling Interference for Individual Treatment Effect Estimation from Networked Observational Data

SemiITE: Semi-supervised Individual Treatment Effect Estimation via Disagreement-Based Co-training

Molecular Subtyping of Cancer Based on Distinguishing Co-Expression Modules and Machine Learning

Molecular Subtyping of Cancer Based on Robust Graph Neural Network and Multi-Omics Data Integration

Identification of key somatic oncogenic mutation based on a confounder-free causal inference model

An AutoEncoder-Based Matrix Factorization Approach to Estimating Cell Proportion from Bulk Tumor RNA-seq Data

DBPOM: a comprehensive database of pharmaco-omics for cancer precision medicine

A causality-inspired feature selection method for cancer imbalanced high-dimensional data

A Breast Cancer Patients’ Survival Prediction Model Using mRMR Feature Selection with Artificial Neural Network

Metabolic reprogramming in cancer: the bridge that connects intracellular stresses and cancer behaviors

The bioinformatics toolbox for circRNA discovery and analysis

Identification of Cancer Development Related Pathways Based on Co-Expression Analyses

Unsupervised Nonlinear Feature Selection from High-Dimensional Signed Networks

CaMeRe: A Novel Tool for Inference of Cancer Metabolic Reprogramming

Warburg Effects in Cancer and Normal Proliferating Cells: Two Tales of the Same Name

Link Prediction Based on Extended Local Path Gain in Protein-Protein Interaction Network

Trends in the development of miRNA bioinformatics tools

Multi-Classification of Cancer Samples Based on Co-Expression Analyses

数据挖掘在癌症细胞增殖机制分析中的应用研究

Identification of Essential Proteins Based on Ranking Edge-Weights in Protein-Protein Interaction Networks

Essential protein identification based on essential protein-protein interaction prediction by integrated edge weights

Silhouette Index Supervised Affinity Propagation Clustering

An Improved Sum of Edge Clustering Coefficient Method for Essential Protein Identification

预印本

Biological Regulatory Network Inference through Circular Causal Structure Learning

A General Causal Inference Framework for Cross-Sectional Observational Data

Does Misclassifying Non-confounding Covariates as Confounders Affect the Causal Inference within the Potential Outcomes Framework?

De-confounding Representation Learning for Counterfactual Inference on Continuous Treatment via Generative Adversarial Network

研究方向