个人概况

姓名：习佳宁                  性别：男

职称：副教授                  导师资格：硕士生导师

单位：广州医科大学生物医学工程学院

学历：博士研究生      毕业院校：中国科学技术大学

招生专业：生物医学工程

电子邮件：xjn@gzhmu.edu.cn

通信地址：广州市番禺区新造镇广州医科大学番禺校区

研究方向

1、生物信息学：主要围绕基因组、转录组、表观组等组学的测序/高通量芯片数据分析，旨在挖掘高通量生物分子层面的异常模式与致病因素。

2、智能诊断算法：主要围绕医学语义知识、医学影像数据、医学临床数据等相关信息，旨在通过智能推理算法实现疾病的智能辅助诊断。

所获奖项/荣誉

1、西安市自然科学优秀学术论文奖，2020，西安市科学技术协会/西安市人力资源和社会保障局

2、安徽省生物医学工程年会优秀海报奖，2015，安徽省生物医学工程学会

3、安徽省普通高等学校品学兼优毕业生（省级优秀毕业生），2018，安徽省教育厅

4、硕士研究生国家奖学金，2015，中华人民共和国教育部

5、国家奖学金，2012，中华人民共和国教育部

指导学生获得的科研项目和奖项

1. SCI学术论文：Xie Fei, Jianing Xi*, and Qun Duan. "Driver Attribute Filling for Genes in Interaction Network via Modularity Subspace-Based Concept Learning from Small Samples." Complexity, 2020 (2020), 6643551.

社会兼职

1.国际学术期刊编辑：Frontiers in Genetics (SCI中科院2区)、Mathematical Biosciences and Engineering (SCI)客座编辑、Computational Biology and Bioinformatics编委

2. 国际SCI期刊审稿人：IEEE Transactions on Image Processing, Bioinformatics, Zoological Research, Genomics, Proteomics & Bioinformatics, IEEE/ACM Transactions on Computational Biology and Bioinformatics , BMC Bioinformatics, Journal of Biomedical Informatics, Neurocomputing, Cancer Management and Research, Technology in Cancer Research & Treatment, Journal of Medical Imaging and Health Informatics, Technology in Cancer Research & Treatment, Connection Science

3. 国际会议审稿人：CVPR 2022 (CCF A类), ICCV 2021/2022 (CCF A类), BIBM 2020 (CCF B类), ICME 2021 (CCF B类), ICIP 2021/2022 (CCF C类)

4. 曾任中国科大IEEE学生分会主席(2014-2015)，获中国科大校级优秀学生干部荣誉称号

5.中国医科大学主办课程“生物信息及数据挖掘”线上培训班授课教师

6.中国科学技术大学 信息论(2015, 2016, 2017春)/电磁学(2014, 2015, 2016秋)助教（获校级优秀助教荣誉，全校前5%）

主持科研/教学项目

1、主持：国家级项目，国家自然科学基金青年科学基金项目，61901322，面向肿瘤异质性的亚群特异性驱动基因计算表征及预测研究，24.5万元，在研

2、主持：国家级项目，中国博士后科学基金会面上项目，2020M673494，肿瘤异质性矩阵化建模及癌症驱动基因识别算法研究，8万元, 结题

部分代表性第一和通讯作者论文：

1) Xi J., Yuan X., Wang M., et al. "Inferring subgroup specific driver genes from heterogeneous cancer samples via subspace learning with subgroup indication" [J]. Bioinformatics, 2020, 36(6): 1855–1863. (SCI，Top期刊)

2) Xi J., Ye L., Huang Q., et al. "Tolerating Data Missing in Breast Cancer Diagnosis from Clinical Ultrasound Reports via Knowledge Graph Inference" [C], Proceedings of the 27th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD), 2021. Aug 14-18, Singapore, (pp. 3756-3764). (CCF A类会议)

3) Xi J., Miao Z., Liu L., et. al. "Knowledge Tensor Embedding Framework with Association Enhancement for Breast Ultrasound Diagnosis of Limited Labeled Samples" [J], Neurocomputing, 2021, 468: 60-70. (SCI，Top期刊)

4)Xi J., Li A., Wang M. "HetRCNA: a novel method to identify recurrent copy number alternations from heterogeneous tumor samples based on matrix decomposition framework" [J], IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), 2020, 17(2): 422-434. (SCI)

5)Xi J., Li A., Wang M. "A novel unsupervised learning model for detecting driver genes from pan-cancer data through matrix tri-factorization framework with pairwise similarities constraints" [J], Neurocomputing, 2018, 296: 61-73. (SCI，Top期刊)

6)Xi J., Wang M., Li A. "Discovering mutated driver genes through a robust and sparse co-regularized matrix factorization framework with prior information from mRNA expression patterns and interaction network" [J]. BMC Bioinformatics, 2018, 19(1): 214. (SCI)

7) Xi J., Li A. "Discovering recurrent copy number aberrations in complex patterns via non-negative sparse singular value decomposition" [J]. IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), 2016, 13(4): 656-668. (SCI)

8)Xi J., Chen J., Wang Z., et al. "Simultaneous Segmentation of Fetal Hearts and Lungs for Medical Ultrasound Images via an Efficient Multi-scale Model Integrated with Attention Mechanism" [J], Ultrasonic Imaging, 2021, 01617346211042526. (SCI)

9)Xi J., Wang M., Li A. "Discovering potential driver genes through an integrated model of somatic mutation profiles and gene functional information” [J]. Molecular BioSystems, 2017, 13(10): 2135-2144. (SCI)

10)Xi J., Li A., Wang M. "A novel network regularized matrix decomposition method to detect mutated cancer genes in tumour samples with inter-patient heterogeneity" [J]. Scientific Reports, 2017, 7(1), 2855. (SCI)

11)Xi J., Wang M., Li A. "DGPathinter: a novel model for identifying driver genes via knowledge-driven matrix factorization with prior knowledge from interactome and pathways" [J]. PeerJ Computer Science, 2017, 3(1), e133. (SCI)

12) Xi J., Yu, Z. "Editorial: Unsupervised Learning Models for Unlabeled Genomic, Transcriptomic & Proteomic Data" [J]. Frontiers in Genetics, 2021, 12(1): 2235. (SCI)

13)Xi J., Li A., Wang M. "An efficient nonnegative matrix factorization model for finding cancer associated genes by integrating data from genome, transcriptome and interactome" [C], 52th Annual Conference on Information Sciences and Systems (CISS), 2018, 1-6. (EI)

14)习佳宁, 刘元宁, 王明会, 等 "基于多元方差分析的成对肿瘤SNP array数据分段算法" [J]. 科学通报, 2014, 59(32): 3204-3208. (核心期刊，中文核心期刊要目总览排序：综合性科学技术-第1位 (2014) )

15)Yuan X., Li J., Bai J., Xi J.* "A local outlier factor-based detection of copy number variations from NGS data" [J]. IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), 2021, 18(5): 1811-1820. (SCI，通讯作者)

16)Xie, F., Xi, J.*, Duan Q. "Driver Attribute Filling for Genes in Interaction Network via Modularity Subspace-Based Concept Learning from Small Samples" [J]. Complexity, 2020, 2020(1), 6643551. (SCI，通讯作者)

授权专利

1)习佳宁; 黄庆华; 互斥性约束图拉普拉斯的异质性癌症驱动基因识别方法, 2020-6-23, 中国, ZL202010583114.9（已授权）