张乃千｜山东大学｜学者主页

2025

A semi-supervised Bayesian approach for marker gene trajectory inference from single-cell RNA-seq data

Junchao Wang, Ling Sun, Nana Wei, Yi-Sheng Huang, Naiqian Zhang

Bioinform.

DOI

2024

BS-clock, advancing epigenetic age prediction with high-resolution DNA methylation bisulfite sequencing data

Congcong Hu, Yunxiao Li, Longhui Li, Naiqian Zhang, Xiao-Qi Zheng

Bioinform.

DOI

2024

GSRF-DTI: a framework for drug-target interaction prediction based on a drug-target pair network and representation learning on a large graph

Yongdi Zhu, Chunhui Ning, Naiqian Zhang, Ming-Yi Wang, Yu-Sen Zhang

BMC Biology

DOI

2024

A novel hypergraph model for identifying and prioritizing personalized drivers in cancer

Naiqian Zhang, Fubin Ma, Dong Guo, Yuxuan Pang, Chen-Ye Wang, Yu-Sen Zhang, Xiao-Qi Zheng, Ming-Yi Wang

PLoS Comput. Biol.

DOI

2023

MaxCLK: discovery of cancer driver genes via maximal clique and information entropy of modules

Jian Liu, Fubin Ma, Yongdi Zhu, Naiqian Zhang, Lingming Kong, Jia Mi, Haiyan Cong, Rui Gao, Ming-Yi Wang, Yu-Sen Zhang

Bioinform.

DOI

2021

DriverRWH: discovering cancer driver genes by random walk on a gene mutation hypergraph

Chen-Ye Wang, Junhan Shi, Jiansheng Cai, Yu-Sen Zhang, Xiaoqi Zheng, Naiqian Zhang

BMC Bioinformatics

DOI

2021

CStreet: a computed Cell State trajectory inference method for time-series single-cell RNA sequencing data

Chengchen Zhao, Wen-Chao Xiu, Yuwei Hua, Naiqian Zhang, Yong Zhang

Bioinform.

DOI

2021

Protein-Protein Interaction Prediction Based on Spectral Radius and General Regression Neural Network.

Hanxiao Xu, Da Xu, Naiqian Zhang, Yu-Sen Zhang, Rui Gao

Journal of Proteome Research

DOI

2020

A DNA methylation state transition model reveals the programmed epigenetic heterogeneity in human pre-implantation embryos

Chengchen Zhao, Naiqian Zhang, Yalin Zhang, Nuermaimaiti Tuersunjiang, Shaorong Gao, Wenqiang Liu, Yong Zhang

Genome Biology

DOI

2020

QIMCMDA: MiRNA-Disease Association Prediction by q-Kernel Information and Matrix Completion

Lin Wang, Yaguang Chen, Naiqian Zhang, Wei Chen, Yusen Zhang, Rui Gao

Frontiers in Genetics

DOI

2017

Estimating and accounting for tumor purity in the analysis of DNA methylation data from cancer studies

Xiaoqi Zheng, Naiqian Zhang, Hua-Jun Wu, Hao Wu

Genome Biology

DOI

2016

Tumor purity and differential methylation in cancer epigenomics.

Fayou Wang, Naiqian Zhang, Jun Wang, Hao Wu, Xiaoqi Zheng

Briefings in Functional Genomics

DOI

2015

Anticancer drug sensitivity prediction in cell lines from baseline gene expression through recursive feature selection

Zuoli Dong, Naiqian Zhang, Chun Xing Li, Haiyun Wang, Yun Fang, Jun Wang, Xiaoqi Zheng

BMC Cancer

DOI

2015

DISIS: Prediction of Drug Response through an Iterative Sure Independence Screening

Yun Fang, Yu-Fang Qin, Naiqian Zhang, Jun Wang, Haiyun Wang, Xiaoqi Zheng

PLoS ONE

DOI

2014

Author ' s response to reviews Title : Anticancer drug sensitivity prediction from baseline gene expression by Support Vector Machine via recursive feature selection

Zuoli Dong, Naiqian Zhang, Haiyun Wang, Xiaoqi Zheng, Jun Wang

张乃千

精选作品

期刊论文

A semi-supervised Bayesian approach for marker gene trajectory inference from single-cell RNA-seq data

BS-clock, advancing epigenetic age prediction with high-resolution DNA methylation bisulfite sequencing data

GSRF-DTI: a framework for drug-target interaction prediction based on a drug-target pair network and representation learning on a large graph

A novel hypergraph model for identifying and prioritizing personalized drivers in cancer

MaxCLK: discovery of cancer driver genes via maximal clique and information entropy of modules

DriverRWH: discovering cancer driver genes by random walk on a gene mutation hypergraph

CStreet: a computed Cell State trajectory inference method for time-series single-cell RNA sequencing data

Protein-Protein Interaction Prediction Based on Spectral Radius and General Regression Neural Network.

A DNA methylation state transition model reveals the programmed epigenetic heterogeneity in human pre-implantation embryos

QIMCMDA: MiRNA-Disease Association Prediction by q-Kernel Information and Matrix Completion

Estimating and accounting for tumor purity in the analysis of DNA methylation data from cancer studies

Tumor purity and differential methylation in cancer epigenomics.

Anticancer drug sensitivity prediction in cell lines from baseline gene expression through recursive feature selection

DISIS: Prediction of Drug Response through an Iterative Sure Independence Screening

Author ' s response to reviews Title : Anticancer drug sensitivity prediction from baseline gene expression by Support Vector Machine via recursive feature selection

研究方向