朱丽达
近期热点
资料介绍
个人简历
教育经历2008.9-2015.1: 武汉大学计算机学院,计算机科学与技术,博士2006.9-2008.6: 挪威阿基德大学,ICT,硕士2002.9-2006.6:武汉大学计算机学院,计算机科学与技术,本科工作经历2015.1-2019.1:华中农业大学博士后2009.1-2009.10:新加坡南洋理工大学CS,研究助理研究领域
生物信息学,大数据,数据挖掘,机器学习近期论文
1. Quan Yuan#, Luo Zhi-Hui#, Yang Qing-Yong#, Li Jiang, Zhu Qiang, Liu Ye-Mao, Lv Bo-Min, Cui Ze-Jia, Qin Xuan, Xu Ying, Zhu Li-Da*, Zhang Hong-Yu*. Systems chemical genetics-based drug discovery: prioritizing agents targeting multiple/reliable disease-associated genes as drug candidates.2019. Frontiers in Genetics.2. Quan Yuan#, Liu Meng-Yuan #, Liu Ye-Mao, Zhu Li-Da, Wu Yu-Shan, Luo Zhi-Hui, et al. (2018). Facilitating anti-cancer combinatorial drug discovery by targeting epistatic disease genes. Molecules, 23(4), 7363. Wang Hui#, Wang Gang, Zhu Li-Da, et al. Subnetwork identification and chemical modulation for neural regeneration: A study combining network guided forest and heat diffusion model[J]. Quantitative Biology, 2018, 6(4).4. Yuan Jun#, Zhu Li-Da*, Zhu Fu-xi. Predicting potential Drug-Target Interactions with Multi-label learning and ensemble learning. International Conference on Intelligent Computing (ICIC2019), Accepted5. Zhu Li-Da#, He Chang-Shou, Liu Ye-Mao, et al. A systems chemical biology approach to identify targets of antibacterial agents: A case study of Chelerythrine and Rhein, IEEE International Conference on Bioinformatics and Biomedicine. IEEE, 2015:1047-1056.6. Zhu Li-Da#, Zhu Fuxi*. Identification association of drug-disease by using functional gene module for breast cancer[J]. Bmc Medical Genomics, 2015, 8(S2):1-8.7. Zhu Li-Da#, Liu Juan*. Integration of a prognostic gene module with a drug sensitivity module to identify drugs that could be repurposed for breast cancer therapy. [J]. Computers in Biology & Medicine, 2015, 61(C):163.8. Zhu Li-Da#, Liu Juan*, Liang Feng-Ji, et al. Predicting response to preoperative chemotherapy agents by identifying drug action on modeled microRNA regulation networks[J]. Plos One, 2014, 9(5):e98140.9. Wang Wei, Liu J*, Xiong Yi,Zhu Li-Da, et al. Analysis and classification of DNA-binding sites in single-stranded and double-stranded DNA-binding proteins using protein information[J]. IET Systems Biology, 2014, 8(4):176.10. Zhu Li-Da#, Li Juan*. Water Bioinformatics: An Association between Estrogen Degradation and 16S rRNA Motifs, International Conference on Bioinformatics and 相关热点
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