邱育珊
  • 教育程度:博士及以上

  • 职称:副教授

  • 电话:0755-26538953

  • 邮箱:yushan.qiu@szu.edu.cn

  • 地址:汇星楼312

教程程度 博士及以上 职称 副教授
电话 0755-26538953 邮箱 yushan.qiu@szu.edu.cn
地址 汇星楼312 教育经历 2011.10~2015.08,香港大学-数学系-博士,导师:Ching Wai-Ki;
2013.05~2013.08,京都大学-生物信息学中心-访问学生,导师:Tatsuya Akutsu


工作经历 2016.09~至今,深圳大学-数学与统计学院-助理教授、副教授;
2016.6~2016.8,美国贝勒医学院-博士后,合作导师:Cheng  Chonghui;
2015.9-2016.5,美国西北大学-博士后,合作导师:Cheng  Chonghui


研究领域 生物信息学;机器学习
获得荣誉 深圳市海外高层次人才“孔雀计划”C类人才;
深圳市南山区领航人才;
深圳大学“荔园优青”
教学课程 数学建模、高等数学(全英授课)、数学分析、凸分析与优化
科研成果 <p>
代表性论文:<br>1.    Yushan Qiu, Lingfei Yang, Hao Jiang, Quan Zou. scTPC: a novel semi-supervised deep clustering model for scRNA-seq data. Bioinformatics, 2024, Accepted(数学学会T1).
<br>2. Yushan Qiu, Yahooing Zhang, Liwen Tian, Quan Zou, Pu Zhao. Identification of a comprehensive alternative splicing function during epithelial-mesenchymal transition. iScience, 2023, 26(4):106517 (CELL 子刊)<br>3.    Liangjie Sun, Yushan Qiu(*通讯作者), Wai-Ki Ching, Pu Zhao, Quan Zou. PCB: a pseudotemporal causality-based Bayesian approach to identify EMT-associated regulatory relationships of AS events and RBPs during breast cancer progression. PLoS Computational Biology. 2023, 19(3): e1010939. (学生一作,中科院大类2区)<br>4.    Yushan Qiu, Chang Yan, Pu Zhao, Quan Zou. SSNMDI: a novel joint learning model of semi-supervised non-negative matrix factorization and data imputation for clustering of single-cell RNA-seq data. Briefings in Bioinformatics, 2023,  bbad149. (中科院1区Top期刊,JCR Q1,IF 2020:11.622)<br>5.    Hao Jiang, Dong Shen, Wai-Ki Ching, Yushan Qiu(*通讯作者). A High-Order Norm-Product Regularized Multiple Kernel Learning Framework for Kernel Optimization, Information Sciences, 2022. 606:72-97. (中科院大类1区Top期刊,JCR Q1) <br>6.    Ying Yang, Sha Tian, Yushan Qiu(*通讯作者), Pu Zhao, Quan Zou, MDICC: novel method for multi-omics data integration and cancer subtype identification, Briefings in Bioinformatics, Volume 23, Issue 3, May 2022, bbac132, https://doi.org/10.1093/bib/bbac132. (中科院1区Top期刊,JCR Q1,IF 2021:11.622,学生一作) <br>7.    Yushan Qiu, Wai-Ki Ching, Quan Zou. Matrix factorization-based data fusion for the prediction of RNA-binding protein and alternative splicing event associations during epithelial-mesenchymal transition. Briefings in Bioinformatics, 2021, Doi:10.1093/bib/bbab332. (中科院1区Top期刊,JCR Q1,IF 2020:11.622)<br>8.     Yushan Qiu, Wai-Ki Ching, Quan Zou. Prediction of RNA-binding protein and alternative splicing event associations during epithelial-mesenchymal transition based on inductive matrix completion. Briefings in Bioinformatics. doi: 10.1093/bib/bbaa440. (中科院1区Top期刊,JCR Q1,IF 2020:11.622) <br>9.    Yushan Qiu, Hao Jiang, Wai-Ki Ching. Unsupervised learning framework with multidimensional scaling in predicting epithelial-mesenchymal transitions. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2020,  doi: 10.1109/TCBB.2020.2992605. (中科院小类2区,JCR Q1,IF 2020: 3.015) <br>10.    Yushan Qiu, Jingyi Lyu, Mikayla Dunlap, Sameul E. Harvey, Chonghui Cheng. A combinatorially regulated RNA splicing signature predicts breast cancer EMT states and patient survival. RNA, 2020, 10.1261/rna.074187.119. (中科院大类2区,JCR Q1,IF 2020: 4.942) <br>11.    Hao Jiang, Yushan Qiu(*通讯作者), Wenpin Hou, Xiaoqing Cheng, Manyi Yim, Wai-Ki Ching. Drug side-effect profiles prediction: from empirical risk minimization to structural risk minimization. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2020, 17(2): 402-410. (中科院大类2区,JCR Q1,IF 2020: 4.942) <br>12.    Yushan Qiu, Hao Jiang, Wai-Ki Ching, Xiaoqing Cheng. Discovery of Boolean metabolic networks: integer linear programming based approach. BMC Systems Biology, 2018, 12(1): 53-60. (中科院小类2区,JCR: Q2, IF 2018: 2.048) <br>13.    Hao Jiang, Wai-Ki Ching, Ka Fai Cedric Yiu, Yushan Qiu(*通讯作者). Stationary mahalanobis kernel SVM for credit risk evaluation. Applied Soft Computing, 2018, 71: 407-417. (中科院升级版大类1区,JCR: Q1, IF 2018: 4.873)<br><br></p>
科研项目 1. 国家自然科学基金面上项目,面向乳腺肿瘤转移的分子关联与调控网络推断研究,62372303,主持,50万,2024/01-2027/12;
2. 国家自然科学基金青年项目,面向肿瘤转移标志物识别的多源数据整合方法研究,62002234,主持,24万,2021/01-2023/12;
3. 广东省基础与应用基础研究, 基于多源单细胞组学数据的肿瘤异质性识别模型与算法研究, 2019A1515111180,结题,10万,2020/01-2022/12;
4. 深圳大学新引进教师科研启动项目,基于多源异构的的多组学数据整合方法研究,结题,14万,2019/09-2022/08;
5. 深圳大学新引进高端人才财政补助科研启动项目,面向多源异构生物大数据的模式发现理论及其应用,结题,160万,2019/01-2021/12;
6. 国家自然科学基金面上项目,基于罚函数方法的HJB广义互补问题研究,11871347,参与,52万,2019/01-2022/12;
7. 深圳市科技计划基础研究项目,基于深度数学优化方法的新型生物信息技术,JCYJ20170817100950436,参与,30万,2018/04-2020/03; 7. 深圳大学新引进高端人才财政补助科研启动项目,基于深度特征选择技术的基因调控网络研究,参与,147万,2017/01-2019/12;
8. 深圳大学新引进教师科研启动项目,基于特征提取方法研究及其应用,2017058,主持,6万,2017/06-2019/05,结题。

个人简介

邱育珊,博士研究生导师,于2015年毕业于香港大学,随后先后在美国西北大学和贝勒医学院从事博士后研究,于2016年加入深圳大学数学科学学院。申请人自攻读博士学位以来一直从事生物信息学与机器学习的研究,目前以主要作者身份在CELL子刊、PLoS Computational Biology、Bioinformatics、Briefings in Bioinformatics正式发表SCI论文30余篇,主持国家自然科学面上和青年基金以及多项省部级项目。本人目前担任中国计算机学会(CCF)生物信息学专业委员会委员,同时担任多个期刊的编委,是业内多个顶级期刊的审稿人。也是国际会议BIBM 2023/2022/2021/2020/2019/2018,ISBRA 2018/2017/2016, ICIC 2022/2021等的程序委员会委员。

教育经历

  • 2011.10~2015.08,香港大学-数学系-博士,导师:Ching Wai-Ki; 2013.05~2013.08,京都大学-生物信息学中心-访问学生,导师:Tatsuya Akutsu

工作经历

  • 2016.09~至今,深圳大学-数学与统计学院-助理教授、副教授; 2016.6~2016.8,美国贝勒医学院-博士后,合作导师:Cheng Chonghui; 2015.9-2016.5,美国西北大学-博士后,合作导师:Cheng Chonghui

研究领域

  • 生物信息学;机器学习

获得荣誉

  • 深圳市海外高层次人才“孔雀计划”C类人才; 深圳市南山区领航人才; 深圳大学“荔园优青”

教学课程

  • 数学建模、高等数学(全英授课)、数学分析、凸分析与优化

科研成果

  • 代表性论文:
    1. Yushan Qiu, Lingfei Yang, Hao Jiang, Quan Zou. scTPC: a novel semi-supervised deep clustering model for scRNA-seq data. Bioinformatics, 2024, Accepted(数学学会T1).
    2. Yushan Qiu, Yahooing Zhang, Liwen Tian, Quan Zou, Pu Zhao. Identification of a comprehensive alternative splicing function during epithelial-mesenchymal transition. iScience, 2023, 26(4):106517 (CELL 子刊)
    3. Liangjie Sun, Yushan Qiu(*通讯作者), Wai-Ki Ching, Pu Zhao, Quan Zou. PCB: a pseudotemporal causality-based Bayesian approach to identify EMT-associated regulatory relationships of AS events and RBPs during breast cancer progression. PLoS Computational Biology. 2023, 19(3): e1010939. (学生一作,中科院大类2区)
    4. Yushan Qiu, Chang Yan, Pu Zhao, Quan Zou. SSNMDI: a novel joint learning model of semi-supervised non-negative matrix factorization and data imputation for clustering of single-cell RNA-seq data. Briefings in Bioinformatics, 2023, bbad149. (中科院1区Top期刊,JCR Q1,IF 2020:11.622)
    5. Hao Jiang, Dong Shen, Wai-Ki Ching, Yushan Qiu(*通讯作者). A High-Order Norm-Product Regularized Multiple Kernel Learning Framework for Kernel Optimization, Information Sciences, 2022. 606:72-97. (中科院大类1区Top期刊,JCR Q1)
    6. Ying Yang, Sha Tian, Yushan Qiu(*通讯作者), Pu Zhao, Quan Zou, MDICC: novel method for multi-omics data integration and cancer subtype identification, Briefings in Bioinformatics, Volume 23, Issue 3, May 2022, bbac132, https://doi.org/10.1093/bib/bbac132. (中科院1区Top期刊,JCR Q1,IF 2021:11.622,学生一作)
    7. Yushan Qiu, Wai-Ki Ching, Quan Zou. Matrix factorization-based data fusion for the prediction of RNA-binding protein and alternative splicing event associations during epithelial-mesenchymal transition. Briefings in Bioinformatics, 2021, Doi:10.1093/bib/bbab332. (中科院1区Top期刊,JCR Q1,IF 2020:11.622)
    8. Yushan Qiu, Wai-Ki Ching, Quan Zou. Prediction of RNA-binding protein and alternative splicing event associations during epithelial-mesenchymal transition based on inductive matrix completion. Briefings in Bioinformatics. doi: 10.1093/bib/bbaa440. (中科院1区Top期刊,JCR Q1,IF 2020:11.622)
    9. Yushan Qiu, Hao Jiang, Wai-Ki Ching. Unsupervised learning framework with multidimensional scaling in predicting epithelial-mesenchymal transitions. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2020, doi: 10.1109/TCBB.2020.2992605. (中科院小类2区,JCR Q1,IF 2020: 3.015)
    10. Yushan Qiu, Jingyi Lyu, Mikayla Dunlap, Sameul E. Harvey, Chonghui Cheng. A combinatorially regulated RNA splicing signature predicts breast cancer EMT states and patient survival. RNA, 2020, 10.1261/rna.074187.119. (中科院大类2区,JCR Q1,IF 2020: 4.942)
    11. Hao Jiang, Yushan Qiu(*通讯作者), Wenpin Hou, Xiaoqing Cheng, Manyi Yim, Wai-Ki Ching. Drug side-effect profiles prediction: from empirical risk minimization to structural risk minimization. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2020, 17(2): 402-410. (中科院大类2区,JCR Q1,IF 2020: 4.942)
    12. Yushan Qiu, Hao Jiang, Wai-Ki Ching, Xiaoqing Cheng. Discovery of Boolean metabolic networks: integer linear programming based approach. BMC Systems Biology, 2018, 12(1): 53-60. (中科院小类2区,JCR: Q2, IF 2018: 2.048)
    13. Hao Jiang, Wai-Ki Ching, Ka Fai Cedric Yiu, Yushan Qiu(*通讯作者). Stationary mahalanobis kernel SVM for credit risk evaluation. Applied Soft Computing, 2018, 71: 407-417. (中科院升级版大类1区,JCR: Q1, IF 2018: 4.873)

科研项目

  • 1. 国家自然科学基金面上项目,面向乳腺肿瘤转移的分子关联与调控网络推断研究,62372303,主持,50万,2024/01-2027/12; 2. 国家自然科学基金青年项目,面向肿瘤转移标志物识别的多源数据整合方法研究,62002234,主持,24万,2021/01-2023/12; 3. 广东省基础与应用基础研究, 基于多源单细胞组学数据的肿瘤异质性识别模型与算法研究, 2019A1515111180,结题,10万,2020/01-2022/12; 4. 深圳大学新引进教师科研启动项目,基于多源异构的的多组学数据整合方法研究,结题,14万,2019/09-2022/08; 5. 深圳大学新引进高端人才财政补助科研启动项目,面向多源异构生物大数据的模式发现理论及其应用,结题,160万,2019/01-2021/12; 6. 国家自然科学基金面上项目,基于罚函数方法的HJB广义互补问题研究,11871347,参与,52万,2019/01-2022/12; 7. 深圳市科技计划基础研究项目,基于深度数学优化方法的新型生物信息技术,JCYJ20170817100950436,参与,30万,2018/04-2020/03; 7. 深圳大学新引进高端人才财政补助科研启动项目,基于深度特征选择技术的基因调控网络研究,参与,147万,2017/01-2019/12; 8. 深圳大学新引进教师科研启动项目,基于特征提取方法研究及其应用,2017058,主持,6万,2017/06-2019/05,结题。