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Your search keyword '"Zhang, Xinmin"' showing total 1,021 results
Start Over Author "Zhang, Xinmin" Publication Type Academic Journals
1,021 results on '"Zhang, Xinmin"'

39. Progression of an emission inventory of China integrating CO2 with air pollutants: A chance to learn the influence of development on emissions

Author

Zhi, Guorui, Du, Jinhong, Chen, Aizhong, Jin, Wenjing, Ying, Na, Huang, Zhihui, Xu, Peng, Wang, Di, Ma, Jinghua, Zhang, Yuzhe, Qu, Jiabao, Zhang, Hao, Yang, Li, Ma, Zhanyun, Ren, Yanjun, Dang, Hongyan, Cui, Jianglong, Lin, Pengchuan, He, Zhuoshi, Zhao, Jinmin, Qi, Shuo, Zhang, Weiqi, Zhao, Wenjuan, Li, Yingxin, Liu, Qian, Zhao, Chen, Tang, Yi, Wei, Peng, Wang, Jingxu, Song, Zhen, Kong, Yao, Zhu, Xiangzhe, Shen, Yi, Zhang, Tianning, Chu, Yangxi, Zhang, Xinmin, Fu, Jiafeng, Gao, Qingxian, Hu, Jingnan, and Xue, Zhigang

Published
2024
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42. Molecular Classification of Breast Cancer: Relevance and Challenges

Author

Zhang, Xinmin

Subjects
Oncology, Experimental, Gene expression -- Research, Molecular diagnostic techniques -- Research, Breast cancer -- Diagnosis -- Genetic aspects, Cancer -- Research, Health
Abstract

* Context.--Appropriate patient management requires precise and meaningful tumor classification. Breast cancer classification continues to evolve from traditional morphologic evaluation to more sophisticated systems with the integration of new knowledge from research being translated into practice. Breast cancer is heterogeneous at the molecular level, with diversified patterns of gene expression, which is presumably responsible for the difference in tumor behavior and prognosis. Since the beginning of this century, new molecular technology has been gradually applied to breast cancer research on issues pertinent to prognosis (prognostic signature) and therapeutic prediction (predictive signature), and much progress has been made. Objective.--To summarize the current state and the prospective future of molecular classification of breast cancer. Data Sources.--Sources include recent medical literature on molecular classification of breast cancer. Conclusions.--Identification of intrinsic tumor subtypes has set a foundation for refining the breast cancer molecular classification. Studies have explored the genetic features within the intrinsic cancer subtypes and have identified novel molecular targets that led to the innovation of clinical assays to predict a patient's prognosis and to provide specific guidelines for therapeutic decisions. With the development and implication of these molecular tools, we have remarkably advanced our knowledge and enhanced our power to provide optimal management to patients. However, challenges still exist. Besides accurate prediction of prognosis, we are still in urgent need of more molecular predictors for tumor response to therapeutic regimes. Further exploration along this path will be critical for improving a patient's prognosis., Breast cancer is a heterogeneous group of malignant tumors with diversified morphology, biologic behavior, clinical course and prognosis, and accurate tumor classification is critical for a patient's care. Theoretically, a [...]

Published
2023
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50. CHOmics: A web-based tool for multi-omics data analysis and interactive visualization in CHO cell lines.

Author

Lin, Dongdong, Yalamanchili, Hima B, Zhang, Xinmin, Lewis, Nathan E, Alves, Christina S, Groot, Joost, Arnsdorf, Johnny, Bjørn, Sara P, Wulff, Tune, Voldborg, Bjørn G, Zhou, Yizhou, and Zhang, Baohong

Subjects
Bioinformatics, Mathematical Sciences, Biological Sciences, Information and Computing Sciences
Abstract

Chinese hamster ovary (CHO) cell lines are widely used in industry for biological drug production. During cell culture development, considerable effort is invested to understand the factors that greatly impact cell growth, specific productivity and product qualities of the biotherapeutics. While high-throughput omics approaches have been increasingly utilized to reveal cellular mechanisms associated with cell line phenotypes and guide process optimization, comprehensive omics data analysis and management have been a challenge. Here we developed CHOmics, a web-based tool for integrative analysis of CHO cell line omics data that provides an interactive visualization of omics analysis outputs and efficient data management. CHOmics has a built-in comprehensive pipeline for RNA sequencing data processing and multi-layer statistical modules to explore relevant genes or pathways. Moreover, advanced functionalities were provided to enable users to customize their analysis and visualize the output systematically and interactively. The tool was also designed with the flexibility to accommodate other types of omics data and thereby enabling multi-omics comparison and visualization at both gene and pathway levels. Collectively, CHOmics is an integrative platform for data analysis, visualization and management with expectations to promote the broader use of omics in CHO cell research.

Published
2020

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