Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Benzhe Su"'
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-13 (2023)
Abstract Hepatocellular carcinoma (HCC) is a prevalent malignancy and there is a lack of effective biomarkers for HCC diagnosis. Living organisms are complex, and different omics molecules interact with each other to implement various biological func
Externí odkaz:
https://doaj.org/article/4beeb71276034415895286c04ba66095
Autor:
Qingqing Wang, Miriam Hoene, Chunxiu Hu, Louise Fritsche, Robert Ahrends, Gerhard Liebisch, Kim Ekroos, Andreas Fritsche, Andreas L. Birkenfeld, Xinyu Liu, Xinjie Zhao, Qi Li, Benzhe Su, Andreas Peter, Guowang Xu, Rainer Lehmann
Publikováno v:
Journal of Lipid Research, Vol 64, Iss 6, Pp 100378- (2023)
Reliability, robustness, and interlaboratory comparability of quantitative measurements is critical for clinical lipidomics studies. Lipids’ different ex vivo stability in blood bears the risk of misinterpretation of data. Clear recommendations for
Externí odkaz:
https://doaj.org/article/a42ab799f397406da6b28c7fe9b90fe6
Autor:
Yang Ouyang, Gaokun Qiu, Xinjie zhao, Benzhe Su, Disheng Feng, Wangjie Lv, Qiuhui Xuan, Lichao Wang, Di Yu, Qingqing Wang, Xiaohui Lin, Tangchun Wu, Guowang Xu
Publikováno v:
Global Challenges, Vol 5, Iss 4, Pp n/a-n/a (2021)
Abstract In a Chinese prospective cohort, 500 patients with new‐onset type 2 diabetes (T2D) within 4.61 years and 500 matched healthy participants are selected as case and control groups, and randomized into discovery and validation sets to discove
Externí odkaz:
https://doaj.org/article/7ad08c3aa8de4ae8acc75cb7cf46b058
Publikováno v:
Molecules, Vol 23, Iss 1, p 52 (2017)
Feature selection is an important topic in bioinformatics. Defining informative features from complex high dimensional biological data is critical in disease study, drug development, etc. Support vector machine-recursive feature elimination (SVM-RFE)
Externí odkaz:
https://doaj.org/article/da58662dfbb3430d999feda604323a9f
Publikováno v:
IEEE/ACM Transactions on Computational Biology and Bioinformatics. 20:923-931
During the development of complex diseases, there is a critical transition from one status to another at a tipping point, which can be an early indicator of disease deterioration. To effectively enhance the performance of early risk identification, a
Publikováno v:
Analytical and Bioanalytical Chemistry. 414:235-250
Omics mainly includes genomics, epigenomics, transcriptomics, proteomics and metabolomics. The rapid development of omics technology has opened up new ways to study disease diagnosis and prognosis and to define prospective information of complex dise
Publikováno v:
Journal of Bioinformatics and Computational Biology. 20
Lung adenocarcinoma (LUAD) seriously threatens human health and generally results from dysfunction of relevant module molecules, which dynamically change with time and conditions, rather than that of an individual molecule. In this study, a novel net
Complex diseases generally result from dysfunction of relevant module molecules, which dynamically change with time and conditions, rather than that of an individual molecule. In this study, a novel network construction algorithm for identifying earl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6cc2594e1cbcb39565f309594bc5fd7c
https://doi.org/10.22541/au.164873464.45732272/v1
https://doi.org/10.22541/au.164873464.45732272/v1
Publikováno v:
Journal of biomedical informatics. 128
The occurrence and development of diseases are related to the dysfunction of biomolecules (genes, metabolites, etc.) and the changes of molecule interactions. Identifying the key molecules related to the physiological and pathological changes of orga
Autor:
Peiyuan Yin, Zaifang Li, Lina Zhou, Pei Yu, Benzhe Su, You-Lin Qiao, Jin-Hu Fan, Guowang Xu, Zhao Yang, Xiaohui Lin, Ping Luo, Xin Huang
Publikováno v:
Analytical and Bioanalytical Chemistry. 411:6377-6386
Omics techniques develop quickly and have made a great contribution to disease study. Omics data are usually complex. How to analyze the data and mine important information has been a key part in omics research. To study the nature of disease mechani