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Akademický článek

Association between high galectin expression and poor prognosis in hematologic cancers: a systematic review and meta-analysis

Autor: Haotian Liu, Qiuying Dai, Yixian Li, Zhenfei Tang, Tiantian She

Publikováno v: Hematology, Vol 28, Iss 1 (2023)

ABSTRACTBackground Galectin (Gal) is considered a promising immune checkpoint molecule. More and more studies have shown that high expression levels of galectins in hematologic cancer are positively correlated with poor clinical prognosis. However, t

Externí odkaz: https://doaj.org/article/b70a1e2078484709b3b0b7a0680153aa

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Efficacy and safety of CDK4/6 inhibitors combined with endocrine therapy versus endocrine therapy alone in hormone receptor-positive, HER2-negative, advanced breast cancer: a systematic review and meta-analysis

Autor: Qiuying Dai, Yongling Wang, Mingjuan Liao, Hongfeng Chen

Publikováno v: Annals of Palliative Medicine. 11:3727-3742

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::12b0bc1628678c59e27620a244180822
https://doi.org/10.21037/apm-22-1306

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Akademický článek

Molecular mechanism of Ruxian Shuhou prescription in the treatment of triple-negative breast cancer based on network pharmacology.

Autor: Meiling Chu, Tian Meng, Yue Zhou, Lan Jin, Qiuying Dai, Lina Ma, Hongfeng Chen

Publikováno v: Medicine; Sep2023, Vol. 102 Issue 35, p1-10, 10p

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MDA-GCNFTG: identifying miRNA-disease associations based on graph convolutional networks via graph sampling through the feature and topology graph

Autor: Yanjing Wang, Dennis R. Salahub, Shaoliang Peng, Jingfei Qiu, Yanyi Chu, Xuhong Wang, Yi Xiong, Dong-Qing Wei, Qiuying Dai, Qiankun Wang, Xiao-Yong Wei

Publikováno v: Briefings in Bioinformatics. 22

Accurate identification of the miRNA-disease associations (MDAs) helps to understand the etiology and mechanisms of various diseases. However, the experimental methods are costly and time-consuming. Thus, it is urgent to develop computational methods

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6f3ef69f8ef7e2f811574649f5dd0531
https://doi.org/10.1093/bib/bbab165

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MLCDForest: multi-label classification with deep forest in disease prediction for long non-coding RNAs

Autor: Qiuying Dai, Dong-Qing Wei, Yi Xiong, Wei Wang, Fang Li

Publikováno v: Briefings in bioinformatics. 22(3)

The long non-coding RNAs (lncRNAs) are subject of intensive recent studies due to its association with various human diseases. It is desirable to build the artificial intelligence-based models for prediction of diseases or tissues based on the lncRNA

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8011b394971419d3614aeb5d8625ba28
https://pubmed.ncbi.nlm.nih.gov/32520339

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MDA-CF: Predicting MiRNA-Disease associations based on a cascade forest model by fusing multi-source information

Autor: Yusong Zhao, Zhiqi Li, Xueying Mao, Yanyi Chu, Dong-Qing Wei, Yanjing Wang, Qiuying Dai, Yi Xiong

Publikováno v: Computers in Biology and Medicine. 136:104706

MicroRNAs (miRNAs) are significant regulators in various biological processes. They may become promising biomarkers or therapeutic targets, which provide a new perspective in diagnosis and treatment of multiple diseases. Since the experimental method

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3c76756d70307c50602f8f50ca127146
https://doi.org/10.1016/j.compbiomed.2021.104706

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