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Your search keyword '"Wang Haiyun"' showing total 1,240 results
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1,240 results on '"Wang Haiyun"'

175. Case Report: Anlotinib combined with PD-1 inhibitor and sequential GA regimen or FOLFIRINOX Chemotherapy in treatment of KRAS G12V mutated pancreatic ductal adenocarcinoma with liver metastasis: A case and literature review

Author

Wang, Yunpeng, primary, Wang, Bofang, additional, Xiang, Lin, additional, Deng, Junge, additional, Xu, Bo, additional, He, Puyi, additional, Pu, Weigao, additional, Wang, Haiyun, additional, Fan, Yong, additional, and Chen, Hao, additional

Published
2022
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185. ExosomePurity: tumour purity deconvolution in serum exosomes based on miRNA signatures.

Author

Wu, Tao, Dai, Yao, Xu, Yue, Zheng, Jie, Chen, Shuting, Zhang, Yinuo, Tian, Peng, Zheng, Xiaoqi, and Wang, Haiyun

Subjects
EXOSOMES, MICRORNA, GENE expression, TUMORS, CANCER invasiveness
Abstract

Exosomes cargo tumour-characterized biomolecules secreted from cancer cells and play a pivotal role in tumorigenesis and cancer progression, thus providing their potential for non-invasive cancer monitoring. Since cancer cell-derived exosomes are often mixed with those from healthy cells in liquid biopsy of tumour patients, accurately measuring the purity of tumour cell-derived exosomes is not only critical for the early detection but also essential for unbiased identification of diagnosis biomarkers. Here, we propose 'ExosomePurity', a tumour purity deconvolution model to estimate tumour purity in serum exosomes of cancer patients based on microribonucleic acid (miRNA)-Seq data. We first identify the differently expressed miRNAs as signature to distinguish cancer cell- from healthy cell-derived exosomes. Then, the deconvolution model was developed to estimate the proportions of cancer exosomes and normal exosomes in serum. The purity predicted by the model shows high correlation with actual purity in simulated data and actual data. Moreover, the model is robust under the different levels of noise background. The tumour purity was also used to correct differential expressed gene analysis. ExosomePurity empowers the research community to study non-invasive early diagnosis and to track cancer progression in cancers more efficiently. It is implemented in R and is freely available from GitHub (https://github.com/WangHYLab/ExosomePurity). [ABSTRACT FROM AUTHOR]

Published
2023
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186. Effect of DFIG control parameters on small signal stability in power systems

Author

Liu Qi, Wu jiahui, Wang Haiyun, Zhang Hua, and Yang Jian

Subjects
Multidisciplinary
Abstract

The doubly-fed induction generator (DFIG) with virtual inertia control and reactive damping control gives a renewable energy generation system inertia and damping characteristics similar to those of a thermal power plant, and the parameters of the control strategy have a direct impact on the small-signal stability of the system. This paper firstly introduces the operating characteristics and control strategies of DFIG-based damping control and virtual inertia control, establishes a small-signal model of the control-based DFIG integrated interconnected system, and investigates the effects of virtual inertia and reactive damping values on the small-signal stability of the system; then, the maximum damping ratio of the interval oscillation mode in small disturbance analysis is taken as the optimization objective, and the control parameters are the optimization variables. An optimization method of inertia and damping parameters is established for improving the small disturbance stability of the system. The results show that the optimization procedure could improve the damping ratio of the interval oscillation mode while ensuring the system frequency. The effects of virtual inertia and reactive damping values on the small signal stability of the system are investigated, and an optimal allocation model and method for virtual inertia used to improve the small disturbance stability of the system is proposed.

Published
2022

191. A Novel Feature Ensemble Technology to Improve Prediction Performance of Multiple Heterogeneous Phenotypes Based on Microarray Data

Author

Wang, Haiyun, Zhang, Qingpu, Wang, Yadong, Li, Xia, Rao, Shaoqi, Ding, Zuquan, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Carbonell, Jaime G., editor, Siekmann, Jörg, editor, Wang, Lipo, editor, and Jin, Yaochu, editor

Published
2005
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