Author

Qinyang Ni

Zhejiang University

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Organism:bacteria (other)· 2 Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Approach:machine learning (classical)· 1 Research Focus:protein design· 1 Assay:protein sequence· 1 Assay:proteomics· 1

Frequent Co-Authors

Haoyu ChaoiD· 2 shared Yanyan Zhu· 2 shared Yejun WangiD· 2 shared Yueming HuiD· 2 shared Cong FengiD· 1 shared Enyan Liu· 1 shared Liya LiuiD· 1 shared Ming CheniD· 1 shared

Activity by Year

2023-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 40 mutual co-author links

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2 shared papersBioinformatics

Haoyu ChaoORCID

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2 papers

Recent·Most cited

Improved Prediction of Bacterial Type VI Secretion Effector Proteins Using an Integrated Convolutional Neural Network Model Combining N-terminal Signal Sequences, Evolutionary Information and Pre-Trained Protein Language Features

Yueming Hu, Minqing Yan, Yanyan Zhu, Haoyu Chao, Sida Li, Qinyang Ni, Yanshi Hu, Enyan Liu, Liya Liu, Yifan Chen, Zeya Zhou, Yuhao Chen, Shilong Zhang, Yejun Wang, Cong Feng, Ming Chen

This paper introduces T6CNN, a model that improves T6SE prediction by integrating signal sequences, evolutionary data, and pre-trained features, achieving higher accuracy, sensitivity, and specificity than existing tools.

bioRxiv · Mar 7, 2025 · PreprintBioinformatics

T4SEpp: a pipeline integrated with protein language models effectively predicting bacterial type IV secreted effectors

Yueming Hu, Yejun Wang, Xiaotian Hu, Haoyu Chao, Sida Li, Qinyang Ni, Yanyan Zhu, Yixue Hu, Ziyi Zhao, Ming Chen

T4SEpp predicts bacterial type IV secreted effectors using protein language models and integrates multiple modules, achieving high sensitivity and specificity.

bioRxiv · Jul 1, 2023 · PreprintBioinformatics