"Hao duan, Xiuhao Fu, Chunling Liu, Xiaofeng Zang, Anqi Xu, Xingfeng Li, Qingchen Zhang, Zilong Zhang, Feifei Cui. Machine learning-based prediction model for distant metastasis of breast cancer."  (Under review)

"Xiuhao Fu, Hao duan, Xiaofeng Zang, Chunling Liu, Xingfeng Li, Qingchen Zhang, Zilong Zhang, Quan Zou, Feifei Cui. Hyb_SEnc: An Antituberculosis Peptide Predictor Based on a Hybrid Feature Vector and Stacked Ensemble Learning."  (Under review)

"Chaorui Yan, Feifei Cui, Quan Zou, Zilong Zhang. Integration Tool for scRNA-seq Data and Spatial Transcriptomics Sequencing Data."  (Under review)

"Yunyun Su, Shiyu Yan, Chen Cao, Feifei Cui, Quan Zou, Zilong Zhang. Human-Spa: An Online Platform Based on Spatial Transcriptome Data for Diseases of Human Systems."  (Under review)

"Ruiqi Liu, Xiuhao Fu, Shankai Yan, Zilong Zhang, Feifei Cui. AIPPT: Predicts anti-inflammatory peptides using the most characteristic subset of bases and sequences by stacking ensemble learning strategies."  (Under review)

"Xiuhao Fu, Ye Yuan, Haoye Qiu, Haodong Suo, Yingying Song, Yupeng Zhang, Lijun Dou, Zilong Zhang, Feifei Cui. AFG-PPIS: A Protein-protein Interaction Site Predictor Based on Attention Mechanism and Graph Convolutional Networks."  (Submitted)

Our work "iKcr_CNN: A novel computational tool for imbalance classification of human nonhistone crotonylation sites based on convolutional neural networks with focal loss." has been accepted for publication on Bioinformatics.

Our work "webSCST: an interactive web application for single−cell RNA−sequencing data and spatial transcriptomic data integration." has been accepted for publication on Bioinformatics.

Our work "DeepMC−iNABP: Deep learning for multiclass identification and classification of nucleic acid−binding proteins. " has been accepted for publication on Computational and Structural Biotechnology Journal.

Our work "Protein−DNA/RNA interactions: Machine intelligence tools and approaches in the era of artificial intelligence and big data. " has been accepted for publication on Proteomics.

Our work "Single−cell RNA analysis reveals the potential risk of organ−specific cell types vulnerable to SARS−CoV−2 infections. " has been accepted for publication on Computers in Biology and Medicine.

Our work "Briefings in functional genomics special section editorial: analysis of integrated multiple omics data. " has been published on Briefings in Functional Genomics.

Our work "Critical downstream analysis steps for single−cell RNA sequencing data. " has been accepted for publication on Briefings in Bioinformatics.

Our work "Single−cell RNA sequencing analysis identifies key genes in brain metastasis from lung adenocarcinoma. " has been accepted for publication on Current Gene Therapy.

Our work " Computational biology and chemistry Special section editorial: Computational analyses for miRNA. " has been accepted for publication on Computational Biology and Chemistry.

Our work " Anticancer peptides prediction with deep representation learning features." has been accepted for publication on Briefings in Bioinformatics..

Our work "Sequence representation approaches for sequence−based protein prediction tasks that use deep learning. " has been accepted for publication on Briefings in Functional Genomics.

Our work "Goals and approaches for each processing step for single−cell RNA sequencing data. " has been accepted for publication on Briefings in Bioinformatics.