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Disambiguation of "Zhou, Juexiao"

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DeeReCT-APA: Prediction of Alternative Polyadenylation Site Usage Through Deep Learning.

, , , , , , , , , , and . Genom. Proteom. Bioinform., 20 (3): 483-495 (2022)

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Zhou Zhou

Zhou Zhou

Rui Zhou

Yayun Zhou

Yaming Zhou

 

Other publications of authors with the same name

Personalized and privacy-preserving federated heterogeneous medical image analysis with PPPML-HMI., , , , , , , and . CoRR, (2023)A Rapid, Accurate and Machine-Agnostic Segmentation and Quantification Method for CT-Based COVID-19 Diagnosis., , , , , , , , , and 6 other author(s). IEEE Trans. Medical Imaging, 39 (8): 2638-2652 (2020)Annotating TSSs in Multiple Cell Types Based on DNA Sequence and RNA-seq Data via DeeReCT-TSS., , , , , , , , , and 2 other author(s). Genom. Proteom. Bioinform., 20 (5): 959-973 (October 2022)Path to Medical AGI: Unify Domain-specific Medical LLMs with the Lowest Cost., , and . CoRR, (2023)Deep learning-driven pulmonary arteries and veins segmentation reveals demography-associated pulmonary vasculature anatomy., , , , , , , , , and 4 other author(s). CoRR, (2024)Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021, , , , , , , , , and 1318 other author(s). (2024)DeeReCT-APA: Prediction of Alternative Polyadenylation Site Usage Through Deep Learning., , , , , , , , , and 1 other author(s). Genom. Proteom. Bioinform., 20 (3): 483-495 (2022)Personalized and privacy-preserving federated heterogeneous medical image analysis with PPPML-HMI., , , , , , , and . Comput. Biol. Medicine, (February 2024)SD2: spatially resolved transcriptomics deconvolution through integration of dropout and spatial information., , , and . Bioinform., 38 (21): 4878-4884 (October 2022)An interpretable deep learning workflow for discovering subvisual abnormalities in CT scans of COVID-19 inpatients and survivors., , , , , , , , , and 9 other author(s). Nat. Mach. Intell., 4 (5): 494-503 (2022)