Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Xinzhi Yao"'
PheSeq, a Bayesian deep learning model to enhance and interpret the gene-disease association studies
Autor:
Xinzhi Yao, Sizhuo Ouyang, Yulong Lian, Qianqian Peng, Xionghui Zhou, Feier Huang, Xuehai Hu, Feng Shi, Jingbo Xia
Publikováno v:
Genome Medicine, Vol 16, Iss 1, Pp 1-26 (2024)
Abstract Despite the abundance of genotype-phenotype association studies, the resulting association outcomes often lack robustness and interpretations. To address these challenges, we introduce PheSeq, a Bayesian deep learning model that enhances and
Externí odkaz:
https://doaj.org/article/c8f981816f9e4572905aeda0fed724b8
Publikováno v:
Scientific Data, Vol 11, Iss 1, Pp 1-13 (2024)
Abstract It is vital to investigate the complex mechanisms underlying tumors to better understand cancer and develop effective treatments. Metabolic abnormalities and clinical phenotypes can serve as essential biomarkers for diagnosing this challengi
Externí odkaz:
https://doaj.org/article/d47af246888d4930839167016b3c888c
Autor:
Lei Wang, Wenqing Wu, Lifeng Zhao, Zhanwei Zhu, Xinzhi Yao, Jie Fan, Hongjian Chen, Wenbo Song, Xi Huang, Lin Hua, Ping Qian, Huanchun Chen, Zhong Peng, Bin Wu
Publikováno v:
Frontiers in Veterinary Science, Vol 11 (2024)
Proliferative enteropathy caused by Lawsonia intracellularis is an important economic associated disease to pig industry, but the knowledge about the prevalence of L. intracellularis in pig farms in China is limited. In addition, there is no complete
Externí odkaz:
https://doaj.org/article/3ad850b3259b41f3bd8e3dc6bdc7c663
Autor:
Xinyu Wang, Xinzhi Yao, Huamei Shao, Tian Bai, Yaqiong Xu, Guohang Tian, Albert Fekete, László Kollányi
Publikováno v:
Land, Vol 12, Iss 1, p 257 (2023)
With rapid urban population growth and industrial agglomeration, the urban land supply is becoming gradually tight. Improving land use quality (LUQ) is becoming increasingly critical. This study was carried out in the Luohe built-up zones between 201
Externí odkaz:
https://doaj.org/article/5aa72021cd7f4c83b901482d729ad018
Publikováno v:
JMIR Medical Informatics, Vol 9, Iss 6, p e28247 (2021)
BackgroundNatural language processing has long been applied in various applications for biomedical knowledge inference and discovery. Enrichment analysis based on named entity recognition is a classic application for inferring enriched associations i
Externí odkaz:
https://doaj.org/article/02786d528f36450bac1651476c7bcbd2
Publikováno v:
EURASIP Journal on Advances in Signal Processing, Vol 2010 (2010)
Externí odkaz:
https://doaj.org/article/89bc51d0c5ec430cbc41e14dc45c1496
Publikováno v:
Computer Systems Science and Engineering. 43:103-117
Publikováno v:
Computers, Materials & Continua. 65:2247-2262
Publikováno v:
JMIR Medical Informatics, Vol 9, Iss 6, p e28247 (2021)
JMIR Medical Informatics
JMIR Medical Informatics
Background Natural language processing has long been applied in various applications for biomedical knowledge inference and discovery. Enrichment analysis based on named entity recognition is a classic application for inferring enriched associations
BACKGROUND Natural language processing has long been applied in various applications for biomedical knowledge inference and discovery. Enrichment analysis based on named entity recognition is a classic application for inferring enriched associations
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d14757f1a794f4d7e2473f3da959023b
https://doi.org/10.2196/preprints.28247
https://doi.org/10.2196/preprints.28247