基本信息
王勇  男  博导  中国科学院数学与系统科学研究院
电子邮件: ywang@amss.ac.cn
通信地址: 北京市海淀区中关村东路55号
邮政编码: 100190

研究领域

最优化理论与算法

生物信息学

系统生物学

统计学习

运筹学理论与应用


融合最优化、动力系统、统计观点建模多源异质动态海量生物医学数据,提炼数学理论和算法,解决生物医学中的关键问题,并提炼出数学研究中的新的理论问题。


(1) 重点研究生物分子网络建模,在数学上找出产生数据的模型,揭示生物学家关心的因果关系。

(2) 重点研究生物医学数据分析集成,在数学上研究生物医学数据的基本数学结构,通过建模分离信号与噪声。

招生信息

   
招生专业
070105-运筹学与控制论
071400-统计学
081203-计算机应用技术
招生方向
最优化理论与算法,系统生物学,数据科学与大数据建模
统计学习,生物医学统计,大数据分析建模
生物信息学

教育背景

2002-09--2005-05   中国科学院数学与系统科学研究院   博士
1999-09--2002-09   大连理工大学应用数学系   硕士
1995-09--1999-09   内蒙古大学数学系   本科
学历

-- 研究生

学位
-- 博士

工作经历

   
工作简历
2020-05~现在, 中国科学院大学杭州高等研究院, 研究员
2018-01~现在, 中国科学院动物进化与遗传前沿交叉卓越创新中心, 骨干人才
2017-02~现在, 中国科学院数学与系统科学研究院应用数学研究所, 研究员
2012-11~2016-02,美国斯坦福大学, 访问学者
2010-10~2011-04,日本产业技术综合研究所计算生物研究中心, 特别研究员
2010-04~2017-02,中国科学院数学与系统科学研究院应用数学研究所, 副研究员
2007-09~2008-09,美国波士顿大学, 访问学者
2007-06~2010-03,中国科学院数学与系统科学研究院应用数学研究所, 助理研究员
2005-10~2007-03,日本大阪产业大学电子情报通信系, 日本文部省奖学金资助博士后
2005-05~2007-06,国家信息中心, 博士后
社会兼职
2021-11-11-2026-12-31,国家科学评论期刊青年编委 National Science Review, Associate Editor
2021-11-11-2026-12-25,中国运筹学会, 常务理事
2021-11-04-2025-12-31,中国数学学会医学数学专业委员会, 专委
2021-11-04-2025-12-27,中国医学教育协会医学基因组学与生物信息学专业委员会, 专委
2021-11-04-2026-12-25,中国运筹学会青年工作委员会, 委员
2021-01-01-2025-12-31,中国运筹学会计算系统生物学分会, 副理事长
2020-12-31-2025-12-30,自动化学会智能医药与生物信息学专委会委员, 专委
2017-01-01-2021-12-31,工业与应用数学学会大数据人工智能专业委员会, 专委
2017-01-01-2021-12-31,中国生物化学与分子生物学会分子系统生物学专业委员会, 专委
2017-01-01-2021-12-31,中国人工智能学会生物信息学与人工生命专业委员会委员, 专委
2017-01-01-2022-12-31,Associate Editor of BMC Systems Biology, Associate Editor

教授课程

数据分析与优化建模
统计基因组学与网络生物学
本科生毕业设计(数学与应用数学)
计算基因组学
生物信息学与计算系统生物学
生物信息学与系统生物学

专利与奖励

   
奖励信息
(1) 针灸代谢组学方法学构建及其在针灸关键科学问题研究中的应用, 一等奖, 部委级, 2020
(2) 动力学驱动的数据科学理论和方法研究, 一等奖, 省级, 2020
(3) 网络化生物大数据挖掘理论与方法, 二等奖, 部委级, 2017
(4) 中国科学院数学与系统科学研究院突出科研成果奖, 特等奖, 研究所(学校), 2016
(5) 第21届国际基因组信息学大会(GIW 2010)最佳张贴论文奖, 特等奖, 其他, 2010
(6) 中国科学院数学与系统科学研究院突出科研成果奖, 特等奖, 研究所(学校), 2008
(7) 中国科学院数学与系统科学研究院院长奖学金特等奖, 特等奖, 研究所(学校), 2004
专利成果
[1] 王永翠, 王勇. 一种药物的长非编码RNA靶点预测方法和系统. 中国: CN107038350A, 2017-08-11.

[2] 王永翠, 王勇. 一种预测药物的蛋白质相互作用靶点的方法和系统. 中国: CN105160206A, 2015-12-16.

[3] 王勇, 邹猛, 张朋军, 陈洛南, 田亚平. 基于生物医学大数据的生物标记物组合识别方法和系统. 中国: CN103761451A, 2014-04-30.

[4] 王勇. 一种在高维数据中快速识别特征组合的方法及系统. 中国: CN103761426A, 2014-04-30.

出版信息

   
发表论文
[1] Chen, Shengquan, Liu, Qiao, Cui, Xuejian, Feng, Zhanying, Li, Chunquan, Wang, Xiaowo, Zhang, Xuegong, Wang, Yong, Jiang, Rui. OpenAnnotate: a web server to annotate the chromatin accessibility of genomic regions. NUCLEIC ACIDS RESEARCH[J]. 2021, 49(W1): W483-W490, http://dx.doi.org/10.1093/nar/gkab337.
[2] Zeng, Wanwen, Xin, Jingxue, Jiang, Rui, Wang, Yong. Reusability report: Compressing regulatory networks to vectors for interpreting gene expression and genetic variants. NATURE MACHINE INTELLIGENCEnull. 2021, 3(7): 576-580, http://dx.doi.org/10.1038/s42256-021-00371-6.
[3] Pan, Xiangyu, Cai, Yudong, Li, Zongjun, Chen, Xianqing, Heller, Rasmus, Wang, Nini, Wang, Yu, Zhao, Chen, Wang, Yong, Xu, Han, Li, Songhai, Li, Ming, Li, Cunyuan, Hu, Shengwei, Li, Hui, Wang, Kun, Chen, Lei, Wei, Bin, Zheng, Zhuqing, Fu, Weiwei, Yang, Yue, Zhang, Tingting, Hou, Zhuoting, Yan, Yueyang, Lv, Xiaoyang, Sun, Wei, Li, Xinyu, Huang, Shisheng, Liu, Lixiang, Mao, Shengyong, Liu, Wenqing, Hua, Jinlian, Li, Zhipeng, Zhang, Guojie, Chen, Yulin, Wang, Xihong, Qiu, Qiang, Dalrymple, Brian P, Wang, Wen, Jiang, Yu. Modes of genetic adaptations underlying functional innovations in the rumen. SCIENCE CHINA-LIFE SCIENCES[J]. 2021, 64(1): 1-21, http://lib.cqvip.com/Qikan/Article/Detail?id=7103797645.
[4] Zhanying Feng, Zhana Duren, Ziyi Xiong, Sijia Wang, Fan Liu, Wing Hung Wong, Yong Wang. hReg-CNCC reconstructs a regulatory network in human cranial neural crest cells and annotates variants in a developmental context. COMMUNICATIONS BIOLOGY[J]. 2021, 4(1): https://www.webofscience.com/wos/woscc/full-record/WOS:000637808400003.
[5] Zhou, Guofeng, Sun, Shaoyan, Yuan, Qiuyue, Zhang, Run, Jiang, Ping, Li, Guangyu, Wang, Yong, Li, Xiao. Multiple-Tissue and Multilevel Analysis on Differentially Expressed Genes and Differentially Correlated Gene Pairs for HFpEF. FRONTIERS IN GENETICS[J]. 2021, 12: http://dx.doi.org/10.3389/fgene.2021.668702.
[6] Yong Wang. An Optimization Method for Calibrating Wireline Conveyance Tension. Proceedings of the 4th International Conference on Complex Systems Design & Management Asia and of the 12th Conference on Complex Systems Design & Management CSD&M 2021. 2021, [7] Yong Wang. The cell-surface 50-nucleotidase CD73 defines a functional T memory cell subset that declines with age. Cell Reports. 2021, [8] Meng Zou, Zhana Duren, Qiuyue Yuan, Henry Li, Andrew Paul Hutchins, Wing Hung Wong, Yong Wang. MIMIC: an optimization method to identify cell type-specific marker panel for cell sorting. Briefings in Bioinformatics. 2021, 22(6): [9] Feng, ZhanYing, Wang, Yong. ELF: Extract Landmark Features By Optimizing Topology Maintenance, Redundancy, and Specificity. IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS[J]. 2020, 17(2): 411-421, [10] Jingxue Xin, Hui Zhang, Yaoxi He, Zhana Duren, Caijuan Bai, Lang Chen, Xin Luo, DongSheng Yan, Chaoyu Zhang, Xiang Zhu, Qiuyue Yuan, Zhanying Feng, Chaoying Cui, Xuebin Qi, Ouzhuluobu, Wing Hung Wong, Yong Wang, Bing Su. Chromatin accessibility landscape and regulatory network of high-altitude hypoxia adaptation. NATURE COMMUNICATIONS[J]. 2020, 11(1): http://dx.doi.org/10.1038/s41467-020-18638-8.
[11] Yuan, Qiuyue, Wang, Yong. 3Scover: Identifying Safeguard TF from Cell Type-TF Specificity Network by an Extended Minimum Set Cover Model. ISCIENCE[J]. 2020, 23(6): http://dx.doi.org/10.1016/j.isci.2020.101227.
[12] Wang, Yongcui, Chen, Shilong, Li, Wenran, Jiang, Rui, Wang, Yong. Associating divergent lncRNAs with target genes by integrating genome sequence, gene expression and chromatin accessibility data. NAR GENOMICS AND BIOINFORMATICS[J]. 2020, 2(2): http://dx.doi.org/10.1093/nargab/lqaa019.
[13] Duren, Zhana, Chen, Xi, Xin, Jingxue, Wang, Yong, Wong, Wing Hung. Time course regulatory analysis based on paired expression and chromatin accessibility data. GENOME RESEARCH[J]. 2020, 30(4): 622-634, https://www.webofscience.com/wos/woscc/full-record/WOS:000530027100010.
[14] Feng, Zhanying, Ren, Xianwen, Fang, Yuan, Yin, Yining, Huang, Chutian, Zhao, Yimin, Wang, Yong. scTIM: seeking cell-type-indicative marker from single cell RNA-seq data by consensus optimization. BIOINFORMATICS[J]. 2020, 36(8): 2474-2485, https://www.webofscience.com/wos/woscc/full-record/WOS:000537473400020.
[15] Jingxue Xin, Junjun Hao, Lang Chen, Tao Zhang, Lei Li, Luonan Chen, Wenmin Zhao, Xuemei Lu, Peng Shi, Yong Wang. ZokorDB: tissue specific regulatory network annotation for non-coding elements of plateau zokor. QUANTITATIVE BIOLOGY[J]. 2020, 8(1): 43-50, http://lib.cqvip.com/Qikan/Article/Detail?id=7101641596.
[16] Liu, Kairong, Hutchins, Andrew, Wang, Yong, Lee, W, Chen, L, Moon, YS, Bourgeois, J, Bennis, M, Li, YF, Ha, YG, Kwon, HY, Cuzzocrea, A. Identifying cell type specific TF combinatorial regulation via a two-stage statistical method. 2020 IEEE INTERNATIONAL CONFERENCE ON BIG DATA AND SMART COMPUTING (BIGCOMP 2020)null. 2020, 350-357, [17] Li, Fei, Yuan, Qiuyue, Di, Wei, Xia, Xinyi, Liu, Zhuang, Mao, Ninghui, Li, Lin, Li, Chunfeng, He, Juan, Li, Yunguang, Guo, Wangxin, Zhang, Xiaoyu, Zhu, Yiqin, Aji, Rebiguli, Wang, Shangqian, Tong, Xinyuan, Ji, Hongbin, Chi, Ping, Carver, Brett, Wang, Yong, Chen, Yu, Gao, Dong. ERG orchestrates chromatin interactions to drive prostate cell fate reprogramming. JOURNAL OF CLINICAL INVESTIGATION[J]. 2020, 130(11): 5924-5941, http://dx.doi.org/10.1172/JCI137967.
[18] Yong Wang. Identifying cell type specific TF combinatorial regulation via a two-stage statistical model. IEEE International Conference on Big Data and Smart Computing (BigComp). 2020, [19] Zeng, Wanwen, Wang, Yong, Jiang, Rui. Integrating distal and proximal information to predict gene expression via a densely connected convolutional neural network. BIOINFORMATICS[J]. 2020, 36(2): 496-503, https://www.webofscience.com/wos/woscc/full-record/WOS:000526660300021.
[20] Sun, Shaoyan, Sung, Fengnan, Wang, Yong. Multi-Level Comparative Framework Based on Gene Pair-Wise Expression Across Three Insulin Target Tissues for Type 2 Diabetes. FRONTIERS IN GENETICS[J]. 2019, 10: http://ir.amss.ac.cn/handle/2S8OKBNM/34274, http://www.irgrid.ac.cn/handle/1471x/6869265, http://ir.amss.ac.cn/handle/2S8OKBNM/34275, http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000462601100003&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=3a85505900f77cc629623c3f2907beab.
[21] Wang, Wei, Xin, Jingxue, Yang, Xiao, Lam, Sin Man, Shui, Guanghou, Wang, Yong, Huang, Xun. Lipid-gene regulatory network reveals coregulations of triacylglycerol with phosphatidylinositol/lysophosphatidylinositol and with hexosyl-ceramide. BIOCHIMICA ET BIOPHYSICA ACTA-MOLECULAR AND CELL BIOLOGY OF LIPIDS[J]. 2019, 1864(2): 168-180, http://ir.amss.ac.cn/handle/2S8OKBNM/32271.
[22] Li, Lingjie, Wang, Yong, Torkelson, Jessica L, Shankar, Gautam, Pattison, Jillian M, Zhen, Hanson H, Fang, Fengqin, Duren, Zhana, Xin, Jingxue, Gaddam, Sadhana, Melo, Sandra P, Piekos, Samantha N, Li, Jiang, Liaw, Eric J, Chen, Lang, Li, Rui, Wernig, Marius, Wong, Wing H, Chang, Howard Y, Oro, Anthony E. TFAP2C-and p63-Dependent Networks Sequentially Rearrange Chromatin Landscapes to Drive Human Epidermal Lineage Commitment. CELL STEM CELL[J]. 2019, 24(2): 271-+, http://ir.amss.ac.cn/handle/2S8OKBNM/32521.
[23] Wanwen Zeng, Xi Chen, Zhana Duren, Yong Wang, Rui Jiang, Wing Hung Wong. DC3 is a method for deconvolution and coupled clustering from bulk and single-cell genomics data. Nature Communications[J]. 2019, 10(1): 1-11, http://ir.amss.ac.cn/handle/2S8OKBNM/35766, http://www.irgrid.ac.cn/handle/1471x/6865981, http://ir.amss.ac.cn/handle/2S8OKBNM/35767, http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000489557800006&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=3a85505900f77cc629623c3f2907beab.
[24] Yong Wang. scTIM: Seeking Cell-Type-Indicative Marker from single cell RNA-seq data by consensus optimization.. Bioinformatics. 2019, [25] Yongcui Wang, Shilong Chen, Luonan Chen, Yong Wang. Associating lncRNAs with small molecules via bilevel optimization reveals cancer-related lncRNAs.. PLoS Computational Biology[J]. 2019, 15(12): https://doaj.org/article/1461851043d442ddb87d5cc08fdf0c07.
[26] Wang, Yong, Zhang, XiangSun, Chen, Luonan. Systems biology intertwines with single cell and AI. BMC Bioinformatics[J]. 2019, 20(S7): 1-3, https://doaj.org/article/82a27c53c6a6424abf5e5f496c9ff091.
[27] Yong Wang. Integrating distal and proximal information to predict gene expression via a densely con-nected convolutional neural network. Bioinformatics. 2019, [28] Duren, Zhana, Wang, Yaling, Wang, Jiguang, Zhao, XingMing, Lv, Le, Li, Xiaobo, Liu, Jingdong, Zhu, XinGuang, Chen, Luonan, Wang, Yong. Hierarchical graphical model reveals HFR1 bridging circadian rhythm and flower development in Arabidopsis thaliana. NPJ SYSTEMS BIOLOGY AND APPLICATIONS[J]. 2019, 5(1): http://dx.doi.org/10.1038/s41540-019-0106-3.
[29] Wei Wang, Jingxue Xin, Xiao Yang, Sin Man Lam, Guanghou Shui, Yong Wang, Xun Huang. Lipid-gene regulatory network reveals coregulations of triacylglycerol with phosphatidylinositol/lysophosphatidylinositol and with hexosyl-ceramide. BBA - Molecular and Cell Biology of Lipids. 2019, 1864(2): 168-180, http://ir.amss.ac.cn/handle/2S8OKBNM/32271.
[30] Yu, Chang, Zhang, Ning, Zhu, Weikang, Zhang, Yueyue, Yang, Jiao, Wang, Yong, Song, Xiaoge, Hu, Ling, Wu, Zijian, Liu, Qi, Tang, Yong, Wu, Qiaofeng, Yu, Shuguang. Does Moxa Smoke Have Significant Effect on the Acupuncturist’s Respiratory System? A Population-Based Study. Evidence-Based Complementary and Alternative Medicine[J]. 2019, 2019: http://ir.amss.ac.cn/handle/2S8OKBNM/35971, http://www.irgrid.ac.cn/handle/1471x/6866079, http://ir.amss.ac.cn/handle/2S8OKBNM/35972, http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000488459400001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=3a85505900f77cc629623c3f2907beab.
[31] 张瑞阳, 王勇, 王霞. 大数据视角下的高考选科影响因素研究. 中小学信息技术教育. 2019, 41-44, http://lib.cqvip.com/Qikan/Article/Detail?id=7001578767.
[32] Duren, Zhana, Chen, Xi, Zamanighomi, Mahdi, Zeng, Wanwen, Satpathy, Ansuman T, Chang, Howard Y, Wang, Yong, Wong, Wing Hung. Integrative analysis of single-cell genomics data by coupled nonnegative matrix factorizations. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA[J]. 2018, 115(30): 7723-7728, https://www.webofscience.com/wos/woscc/full-record/WOS:000439574700050.
[33] Zhang, Lirong, Xue, Gaogao, Liu, Junjie, Li, Qianzhong, Wang, Yong. Revealing transcription factor and histone modification co-localization and dynamics across cell lines by integrating ChIP-seq and RNA-seq data. BMC GENOMICS[J]. 2018, 19(S10): http://ir.amss.ac.cn/handle/2S8OKBNM/32724.
[34] Wang, Yong, Zhang, XiangSun, Chen, Luonan. Integrating data- and model-driven strategies in systems biology INTRODUCTION. BMC SYSTEMS BIOLOGYnull. 2018, 12: [35] Fan, Wei, Lam, Sin Man, Xin, Jingxue, Yang, Xiao, Liu, Zhonghua, Liu, Yuan, Wang, Yong, Shui, Guanghou, Huang, Xun. Drosophila TRF2 and TAF9 regulate lipid droplet size and phospholipid fatty acid composition. PLOS GENETICS[J]. 2017, 13(3): https://doaj.org/article/c1c43ef857a048fd942933432b16c10b.
[36] Zamanighomi, Mahdi, Lin, Zhixiang, Wang, Yong, Jiang, Rui, Wong, Wing Hung. Predicting transcription factor binding motifs from DNA-binding domains, chromatin accessibility and gene expression data. NUCLEIC ACIDS RESEARCH[J]. 2017, 45(10): 5666-5677, https://www.webofscience.com/wos/woscc/full-record/WOS:000402510700021.
[37] Li, Wenran, Wang, Meng, Sun, Jinghao, Wang, Yong, Jiang, Rui. Gene co-opening network deciphers gene functional relationships. MOLECULAR BIOSYSTEMS[J]. 2017, 13(11): 2428-2439, https://www.webofscience.com/wos/woscc/full-record/WOS:000413732100024.
[38] Yong Wang. Models of global gene expression define major 1 domains of cell type and tissue identity. Nucleic Acids Research. 2017, [39] Guo, Yuzhen, Tao, Fengying, Wu, Zikai, Wang, Yong. Hybrid method to solve HP model on 3D lattice and to probe protein stability upon amino acid mutations. BMC SYSTEMS BIOLOGY[J]. 2017, 11(Suppl 4): http://dx.doi.org/10.1186/s12918-017-0459-4.
[40] Duren, Zhana, Chen, Xi, Jiang, Rui, Wang, Yong, Wong, Wing Hung. Modeling gene regulation from paired expression and chromatin accessibility data. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA[J]. 2017, 114(25): E4914-E4923, https://www.webofscience.com/wos/woscc/full-record/WOS:000403687300006.
[41] Hutchins, Andrew P, Yang, Zhongzhou, Li, Yuhao, He, Fangfang, Fu, Xiuling, Wang, Xiaoshan, Li, Dongwei, Liu, Kairong, He, Jiangping, Wang, Yong, Chen, Jiekai, Esteban, Miguel A, Pei, Duanqing. Models of global gene expression define major domains of cell type and tissue identity. NUCLEIC ACIDS RESEARCH[J]. 2017, 45(5): 2354-2367, https://www.webofscience.com/wos/woscc/full-record/WOS:000397286600020.
[42] Lei M Li, Xiuxiu Liu, Lin Wang, Yong Wang, Xiuqin Liu, Xue Tian, Fuzhou Gong, Li Shen, Xiaoding Peng. A Novel Dual Eigen-Analysis of Mouse Multi-Tissues' Expression Profiles Unveils New Perspectives into Type 2 Diabetes. SCIENTIFIC REPORTS[J]. 2017, 7(1): https://doaj.org/article/9edd34300b2f4d59b5470ae825e27a2c.
[43] Wang, YongCui, Chen, ShiLong, Deng, NaiYang, Wang, Yong. Computational probing protein-protein interactions targeting small molecules. BIOINFORMATICS[J]. 2016, 32(2): 226-234, http://210.75.249.4/handle/363003/6500.
[44] Duren, Zhana, Wang, Yong. A systematic method to identify modulation of transcriptional regulation via chromatin activity reveals regulatory network during mESC differentiation. SCIENTIFIC REPORTS[J]. 2016, 6: http://dx.doi.org/10.1038/srep22656.
[45] Wang, Yong, Jiang, Rui, Wong, Wing Hung. Modeling the causal regulatory network by integrating chromatin accessibility and transcriptome data. NATIONAL SCIENCE REVIEWnull. 2016, 3(2): 240-251, http://lib.cqvip.com/Qikan/Article/Detail?id=78658382504849544850484956.
[46] Bo Jin, Yifan Zhao, Shiying Hao, Andrew Young Shin, Yue Wang, Chunqing Zhu, Zhongkai Hu, Changlin Fu, Jun Ji, Yong Wang, Yingzhen Zhao, Yunliang Jiang, Dorothy Dai, Devore S. Culver, Shaun T. Alfreds, Todd Rogow, Frank Stearns, Karl G. Sylvester, Eric Widen, Xuefeng B. Ling. Prospective stratification of patients at risk for emergency department revisit: resource utilization and population management strategy implications. BMC Emergency Medicine. 2016, 16(1): http://dx.doi.org/10.1186/s12873-016-0074-5.
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发表著作
(1) Operations Research 50周年纪念特刊中文译本, 运筹与管理, 2004-01, 第 5 作者
编制软件

利用最优化模型和算法确定性地对生物数据进行建模,设计算法,编制软件,为生物学家提供了有效、快速、易用的软件工具,促进产生新的发现。代表性软件包括 (https://github.com/AMSSwanglab/ or http://doc.aporc.org/wiki/Software).

 1. Coupled NMF(coupled Nonnegative Matrix Factorizations 集成单细胞染色质可及性数据与转录组数据的耦合聚类软件) 

2. PECA (Paired Expression and Chromatin Accessibility data analysis: 集成染色质状态数据的基因调控网络建模软件) 

3. GRNInfer (Gene Regulatory Network Inference Tool: 基于最优化模型的基因调控网重构软件) 

4. GNTInfer (Gene Regulatory Network Reconstruction Tool with compound Targets: 基于稀疏优化的考虑靶点的基因调控网重构软件) 

5. TRNInfer (Inferring transcriptional regulatory networks from high-throughput data: 基于线性规划的转录调控网重构软件) 

6. DeterminePPI (Inferring protein-protein interactions by parsimony principle: 基于线性规划的蛋白质相互作用网重构软件) 

7. MDCinfer (Inferring protein-protein interactions based on multi-domain Cooperation: 基于线性规划的考虑多结构领域的蛋白质相互作用网重构软件) 

8. MNAligner (Molecular Network Aligner: 基于二次规划的分子生物网络的比对软件) 

9. OTCC (An Optimization Model for Fuzzy Binary Clustering: 基于最优化模型的聚类软件) 

10. NOA (Network Ontology Analysis:基于最优化模型的网络功能分析软件) 

11. SAMO (Structure Alignment by Multi-objective Optimization: 基于多目标规划的蛋白质结构比对软件) 

12. LPFS (Linear Programming based Feature Selection: 基于线性规划的特征选择软件) 

13. ellipsoidFN (a tool for identifying heterogeneous biomarkers: 非冗余特征选择的优化软件) 

14. NetPredATC (Network predicting drug's ATC code: 基于网络预测药物标签) 

15. NCC-AUC (Nearest Centriod Classifier for AUC valuation:基于线性规划的生存时间生物标记物识别软件) 

16. MOCHA (MOdulation of transcriptional regulation via CHromatin Activity:基于Bayesian图模型的调控网络重建软件) 

17. PreDR (Predict Drug Repositioning:基于数据集成的药物重定位软件) 

18. PrePPItar (Machine learning framework to Predict PPI target for drug:药物的蛋白质相互作用靶点预测) 

19. MILP_k (Mixed Integer Linear Programming for multiple-biomarker panel identification:生物组合标记物识别的混合整数规划软件) 

20. DGPsubNet (Drug-Gene-Disease coherent SUBNETworks:药物-基因-疾病子网络识别软件)

21. QMC (A combinatorial model and algorithm for globally searching community structure: 复杂网络模块探测算法)

科研活动

   
科研项目
( 1 ) 基因调控网络重建中的优化模型和算法研究, 主持, 国家级, 2009-01--2010-12
( 2 ) 基因调控网络研究, 主持, 国家级, 2011-01--2011-12
( 3 ) 基于条件随机场的生物信息学研究, 参与, 国家级, 2010-01--2011-12
( 4 ) 最优化方法在信息技术中的应用, 参与, 部委级, 2009-01--2011-12
( 5 ) 诱导多能干细胞的生物信息学研究, 主持, 国家级, 2012-01--2015-12
( 6 ) 生物医学大数据的数学建模, 主持, 国家级, 2015-01--2017-12
( 7 ) 动物复杂性状的进化解析与调控, 主持, 部委级, 2014-12--2019-12
( 8 ) 网络化知识的基础理论与应用, 参与, 国家级, 2017-01--2022-12
( 9 ) 集成染色质状态和表达数据的基因调控网络建模, 主持, 国家级, 2017-01--2020-12
( 10 ) 复杂网络的最优化方法及在系统生物学的应用, 参与, 国家级, 2012-01--2016-12
( 11 ) 中国重大疾病与罕见病临床与生命组学数据库, 参与, 国家级, 2018-01--2021-12
( 12 ) 干细胞增殖的计算建模及其在癌症演变动力学的应用, 参与, 国家级, 2018-01--2019-12
( 13 ) 癌症基因组大数据深度分析中的优化建模和算法研究, 参与, 国家级, 2017-01--2019-12
( 14 ) 阐明遗传变异的调控网络数据建模, 主持, 国家级, 2019-01--2022-12
( 15 ) 基因型与表型的因果调控网络建模, 参与, 国家级, 2018-01--2020-12
( 16 ) 灵长类大脑进化发育研究, 参与, 部委级, 2019-01--2021-12
( 17 ) 计算系统生物学, 主持, 国家级, 2021-01--2025-12
( 18 ) 乳腺癌精准医学中的数学模型与算法研究, 参与, 国家级, 2021-01--2025-12
( 19 ) 动物复杂性状的进化创新与重塑, 参与, 部委级, 2021-01--2021-12
参与会议
(1)解读遗传变异的调控网络   第十届全国生物信息学与系统生物学大会   2021-10-25
(2)计算系统生物学   张江生命科学国际创新峰会   2021-09-04
(3)前列腺癌的细胞类型转化调控模型   国际遗传与表观遗传精准医疗论坛   2021-07-15
(4)Interpreting genetic variant by constructing tissue specific regulatory network   2019-10-31
(5)Statistical model for tissue specific regulatory network inference   2019-09-01
(6)基因调控网络重建的最优化模型与算法   中国运筹学会第十四次学术年会   2018-10-12
(7)Optimization model and algorithm for regulatory network   2018-09-20
(8)基因表达与染色质开放数据集成建模方法   计算表冠遗传学大数据前沿学术论坛   2018-08-04
(9)计算系统生物学的基因调控网络研究   全国大数据与人工智能科学大会   2018-07-07
(10)Tissue specific regulatory network for complex disease   2018-06-20
(11)生物分子网络的数学建模与算法   中国数学学会2017年会   2017-10-26
(12)生物大数据的降维优化模型和生物标记物发现   中国工业与应用数学学会2017年会   2017-10-12
(13)Predicting protein-protein interaction network   Yong Wang   2010-05-11

合作情况

   
合作单位

  1. 美国斯坦福大学NIH 基因组学卓越中心—个性化动态调控组中心 (Center for Personal Dynamic Regulomes)
  2. 中国科学院动物进化与遗传前沿交叉卓越创新中心

  3. 中国科学院上海生命科学研究院
  4. 中国科学院上海生化细胞所
  5. 中国科学院昆明动物所
  6. 中国解放军总医院
  7. 成都中医药大学
  8. 清华大学

指导学生

已指导学生

张朝昱  硕士研究生  070105-运筹学与控制论  

陈浪  硕士研究生  070105-运筹学与控制论  

信晶雪  博士研究生  070105-运筹学与控制论  

都仁扎那  博士研究生  070105-运筹学与控制论  

马朝霞  硕士研究生  070105-运筹学与控制论  

苑秋月  博士研究生  070105-运筹学与控制论  

现指导学生

孙昕琦  硕士研究生  070105-运筹学与控制论  

冯占营  博士研究生  070105-运筹学与控制论  

张家皓  博士研究生  070105-运筹学与控制论  

朱炜康  博士研究生  070105-运筹学与控制论  

苗灏  硕士研究生  025200-应用统计  

邓芷芸  硕士研究生  070105-运筹学与控制论  

孙睿  硕士研究生  070105-运筹学与控制论  

李世锐  硕士研究生  070105-运筹学与控制论  

张泽华  硕士研究生  070105-运筹学与控制论