Hui Chong

发表

Ontology-aware deep learning enables ultrafast and interpretable source tracking among sub-million microbial community samples from hundreds of niches

K. Ning, Yuguo Zha, Xuefeng Cui, 2022, Genome Medicine.

Utilizing microbiome approaches to assist source tracking, treatment and prevention of COVID-19: Review and assessment

K. Ning, Maozhen Han, Yuguo Zha, 2020, Computational and Structural Biotechnology Journal.

Pre-proofs Utilizing microbiome approaches to assist source tracking , treatment and pre ‐ vention of COVID-19 : Review and Assessment

K. Ning, Maozhen Han, Yuguo Zha, 2020 .

Meta-Prism 2.0: Enabling algorithm and web server for ultra-fast, memory-efficient, and accurate analysis among millions of microbial community samples

K. Ning, Hui Chong, Kai Kang, 2022, GigaScience.

Reliable and Interpretable Mortality Prediction With Strong Foresight in COVID-19 Patients: An International Study From China and Germany

Kang Ning, Jun Song, Tao Bai, 2020, Frontiers in Artificial Intelligence.

Reliable and Interpretable Mortality Prediction With Strong Foresight in COVID-19 Patients: An International Study From China and Germany

H. Einsele, K. Ning, Pengshuo Yang, 2020, Frontiers in Artificial Intelligence.

EXPERT: transfer learning-enabled context-aware microbial community classification

Luis Pedro Coelho, Wei-Hua Chen, K. Ning, 2022, Briefings Bioinform..

Microbiome Sample Comparison and Search: From Pair-Wise Calculations to Model-Based Matching

K. Ning, Hui Chong, Y. Zha, 2021, Frontiers in Microbiology.

Tracing human life trajectory using gut microbial communities by context-aware deep learning

K. Ning, Hui Chong, Mingyue Cheng, 2023, Briefings Bioinform..

Meta-Prism 2.0: Enabling algorithm for ultra-fast, accurate and memory-efficient search among millions of microbial community samples

Kang Ning, Kai Kang, Hui Chong, 2020, bioRxiv.

Ontology-aware deep learning enables ultrafast and interpretable source tracking among sub-million microbial community samples from hundreds of niches

Kang Ning, Kai Kang, Hao Qiu, 2020, Genome Medicine.

Enabling technology for microbial source tracking based on transfer learning: From ontology-aware general knowledge to context-aware expert systems

Wei-Hua Chen, K. Ning, Hui Chong, 2021, bioRxiv.

Microbial Dark Matter: from Discovery to Applications

K. Ning, Pengshuo Yang, Hui Chong, 2022, Genom. Proteom. Bioinform..

Transfer Learning-enabled context-aware microbial 1 source tracking 2 3

Luis Pedro Coelho, Wei-Hua Chen, K. Ning, 2021 .