施绍萍简历
发布时间:2022-03-27
施绍萍,女,1973年9月生,教授、博士生导师,研究生学历,2012年6月博士毕业于南昌大学。联系方式shishaoping@ncu.edu.cn。主要从事生物信息学和生物统计方面的研究工作。近年来,主持国家自然科学基金3项和江西省自然科学基金2项。已在Briefings in Bioinformatics、Bioinformatics、Journal of Chemical Information and Modeling等权威期刊发表SCI论文30余篇,授权发明专利2项,以第二完成人荣获2021年度江西省自然科学奖二等奖1项。
近年代表性论文:
Haiwei Zhou, Wenxi Tan, Shaoping Shi*. DeepGpgs: a novel deep learning framework for predicting arginine methylation sites combined with Gaussian prior and gated self-attention mechanism. Briefings in Bioinformatics, 2023, 24(2): bbad018.
Pengwei Hu, Jinping Zou, Jialin Yu, Shaoping Shi*. De novo drug design based on Stack-RNN with multi-objective reward-weighted sum and reinforcement learning. Journal of Molecular Modeling, 2023, 29:121.
Xinyun Guo, Huan He, Jialin Yu, Shaoping Shi*. PKSPS: a novel method for predicting kinase of specific phosphorylation sites based on maximum weighted bipartite matching algorithm and phosphorylation sequence enrichment analysis.Briefings in Bioinformatics, 2022, 23(1): bbab436.
Ju Zhang, Jialin Yu, Dan Lin, Xinyun Guo, Huan He, Shaoping Shi*. DeepCLA: A hybrid deep learning approach for the identification of clathrin. Journal of Chemical Information and Modeling, 2021, 61(1): 516-524.
Man Cao, Guodong Chen, Jialin Yu, Shaoping Shi*. Computational prediction and analysis of species-specific fungi phosphorylation via feature optimization strategy. Briefings in Bioinformatics, 2020, 21(2): 595-608.
Jialin Yu, Shaoping Shi*, Fang Zhang, Guodong Chen, Man Cao. PredGly: Predicting lysine glycation sites for Homo sapiens based on XGboost feature optimization.Bioinformatics, 2019, 35(16): 2749-2756.
发明专利:
一种癌症分类和特征基因选择方法,专利号ZL202110751724.X。
磷酸化位点特异激酶的预测方法,专利号ZL202110751661.8。
南昌大学数学与计算机学院
School of Mathermatics and Computer Sciences,Nanchang University
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