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健康大数据研究中心简介
2018年10月23日09时 人评论

武汉大学健康大数据研究中心是武汉大学大数据研究院的下属机构,成立于2018年。中心聚焦于医疗健康大数据研究,集科学研究、人才培养、应用服务等功能为一体。本中心的近期发展目标是建设成为国内一流、国际知名的儿童颅脑健康大数据研究中心,为我国大数据发展与应用作出贡献。

一、主要成果

[1] Lu L J, Sboner A, Huang Y J, Lu H X, Gianoulis T A, Yip K Y, Kim P M, Montelione G T, Gerstein M B*, Comparing classical pathways and modern networks: Towards the development of an edge ontology, Trends in Biochemical Science, 2007, 32(7): 320-331

[2] Lu LJ, Xia Y, Paccanaro A, Yu H and Gerstein MB*, Assessing the limits of genomic integration for predicting protein-protein interactions, Genome Research, 2005, 15: 945-53

[3] Lu L, Arakaki AK, Lu H and Skolnick J*, Multimeric threading-based prediction of protein-protein interactions on a genomic scale: Application to the Saccharomyces cerevisiae, Genome Research, 2003, 13:1146-1154

[4] Lu L, Lu H and Skolnick J*. MULTIPROSPECTOR: An algorithm for the prediction of protein-protein interactions bymultimeric threading. Proteins: Structure, Functions, Genetics, 2002, 49: 350-364

[5] Zhu X, Shah AS, Swertfeger DK, Li H, Ren S, Melchior JT, Gordon SM, Davidson WS and Lu LJ*. High density lipoproteins-associated proteins and subspecies related to arterial stiffness in young adults with type 2 diabetes mellitus. Complexity. Jan 2018. https://www.hindawi.com/journals /complexity/aip/7514709/.

[6] Swertfeger DK, Li H, Rebholz S, Zhu X, Shah AS, Davidson WS, and Lu LJ*. Mapping atheroprotective functions and related proteins/lipoproteins in size fractionated human plasma. Molecular & Cellular Proteomics. 2017, 16(4): 680-693

[7] Guo X, Dominick KC, Minai AA, Li H, Erickson CA, and Lu L*. Diagnosing Autism Spectrum Disorder from brain resting-state functional connectivity patterns using a deep neural network with a novel feature selection method. Frontiers in Neuroscience. 2017 Aug 21;11:460.

[8] Tan L, Guo X, Ren S, Epstein JN, and Lu LJ*. A computational model for the automatic diagnosis of Attention Deficit Hyperactivity Disorder based on functional brain volume. Frontiers in Computational Neuroscience. 2017 Sep 8;11:75.

[9] Chen Y, Mazlack L, Minai AA, and Lu LJ*, Inferring causal networks using Fuzzy Cognitive Maps and evolutionary algorithms with application to gene regulatory network reconstruction, Applied Soft Computing, 2015, 37: 667-679

[10] Tan L, Holland S, Deshpande A, Chen Y, Choo D, and Lu LJ*, A semi-supervised SVM model for predicting the language outcomes following cochlear implantation based on pre-implant brain fMRI imaging, Brain and Behavior, 2015, 5(12): e00391

[11] Ren S, Hinzman AA, Kang EL, Szczesniak RD and Lu LJ*, Computational and statistical analysis of metabolomics data, Metabolomics, 2015, 11(6): 1492-1513

[12] Li H, Gordon S, Zhu X, Deng J, Swertfeger D, Davidson WS, and Lu LJ*, Network-based analysis on orthogonal separation of human plasma uncovers distinct high density lipoprotein complexes, Journal of Proteome Research, 2015,14(8): 3082-3094

[13] Lu Y#, Lu Y#, Deng J, Peng H, Lu H, and Lu LJ*, A novel essential domain perspective for exploring gene essentiality, Bioinformatics, 2015, 31(18): 2921-9

[14] Lu Y, Deng J, Rhodes J, Lu H*, and Lu LJ*, Predicting essential genes for identifying potential drug targetsin Aspergillus fumigatus, Computational Biology and Chemistry, 2014, 50:29-40

[15] Guo X, Minai A and Lu L* (2017). Feature selection using multiple Auto-Encoders. 2017 IEEE International Joint Conference on Neural Networks (IJCNN 2017). May 14-19, 2017, Anchorage, Alaska, USA. 4602-4609.

[16] Chen Y, Mazlack LJ and Lu LJ*,Inferring fuzzy cognitive map models for gene regulatory networks from gene expression data. 2012 IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM 2012), Philadelphia, USA, October 4-7, 2012, 598-601

[17] Chen Y, Mazlack LJ and Lu LJ Lu LJ*, Fuzzy cognitive maps development using ant colony optimization with local search procedure. Proceedings of the 2012 Annual Meeting of the North American Fuzzy Information Processing Society (NAFIPS 2012) , Berkeley, USA, August 6-8, 2012, 1-6

[18] Chen Y, Mazlack LJ and Lu LJ*, Learning fuzzy cognitive maps from data by Ant Colony Optimization. Proceedings of the 14th International Conference on Genetic and Evolutionary Computation (GECCO 2012), Philadelphia, USA, July 7-11, 2012, 9-16

[19] Zhang M, Fang CV, Xu Y, Bhatnagar R and Lu LJ*, An integrative scoring approach to identify transcriptional regulations controlling lung surfactant homeostasis, Proceedings of the 10th IEEE International Conference on Data Mining (ICDM) Workshops, Sydney, Australia, December 2010, 787-792

[20] Quan Lu(Corresponding author). Image annotation tactics, transitions, strategies and efficiency, Information Processing and Management, Volume 54, Issue 6, November 2018, Pages 985-1001 (SSCI,JCR1区)

[21] Jing Chen, Dan Wang, Quan Lu(Corresponding author), Zeyuan Xu , (2016), " THC-DAT helps in reading a multi-topic document: Results from a user-centered evaluation of a within-document analysis tool ", Library Hi Tech, Vol. 34 Iss 4  pp. 685 - 704  (SSCI)

[22] Jing Chen , Tian Tian Wang , Quan Lu(Corresponding author), (2016) "THC-DAT: A document analysis tool based on topic hierarchy and context information", Library Hi Tech, Vol. 34 Iss: 1, pp. 64-86    (SSCI,Emerald Literati Award最佳论文奖提名)

[23] Chen Jing, Lu Quan(Corresponding author). A method for automatic analysis Table of Contents in Chinese books, Library Hi Tech, 2015, 33(3): 424-438.   (SSCI)

[24] Quan Lu, Gao Liu, Jing Chen. Integrating PDF interface into Java application[J]. Library Hi Tech, 2014, 32(3):495-508. (SSCI)

[25] Quan Lu, Qing Jun Liu, Jing Chen. Is there any efficient reading strategy when using text signals for navigation in long document,Library Hi Tech (SSCI)

[26] Quan Lu(Corresponding author), Measuring Cognitive Load in Hierarchical Auxiliary Reading of a Research Paper[J]. Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University, v 41, p 67-72(武大学报信息科学版 第41卷IAKS专辑) (EI)

[27] 陆泉. 专题·医疗健康大数据挖掘研究[J]. 信息资源管理学报, 2017(4).(CSSCI)

[28] 陆泉, 张良韬. 处理流程视角下的大数据技术发展现状与趋势[J]. 信息资源管理学报, 2017(4):17-28.(CSSCI)(人大复印资料2018年第2期全文转载)

[29] Ontology based Knowledge Model Research. Midwest Instruction and Computing Symposium, MICS 2014, 4.25-26, USA

[30] Study on Chinese Historical Records Analysis based on Semantic System: Historical Records Knowledge Model, Sharing of Scientific and Technical Resources in the Era of Big Data, the Proceedings of COINFO 2013, p 378-342.

[32] Presenting Android Development in the CS Curriculum, Midwest Instruction and Computing Symposium, MICS 2013, 3.18-22, USA

[33] Using Schema Transformation Pathways for Biological Data Integration, In Journal Biomedical Science and Engineering, 1, 204-209, 2008

[34] Study on Proteomics Data Integration in Web Environments, In Proc. ICBBE’08, IEEE Engineering in Medicine and Biology Society, pages 192-195, 2008

[35] Data Lineage Tracing in Data Warehousing Environments, In Proc. BNCOD’07, Springer Verlag LNCS 4587, pages 25-36, 2007

[36] A Comprehension-Based Approach for Query Optimization, In Proc. SKG’07, IEEE Computer Society, pages 254-257, 2007

[37] Study on Heterogeneous Data Integration Issues in Web Environments, In Proc. Wicom’07, IEEE Engineering Management Society, 2007

[38] OPGSA architecture in e-Business, In Proc. HAIS’07, Springer Verlag LNCS, 2007

[39] Data Access and Integration in the ISPIDER Proteomics Grid, In Proc. DILS’06, Springer Verlag LNCS 4075, pp. 3-18, 2006

[40] Using Schema Transformation Pathways for Incremental View Maintenance, In Proc. DaWaK’05, Springer Verlag LNCS 3589, pp. 126-135, 2005

[41] Using Schema Transformation Pathways for Data Lineage Tracing, In Proc. BNCOD’05, Springer Verlag LNCS 3567, pp. 133-144, 2005

[42] Schema Evolution in Data Warehousing Environment --- a schema transformation-based approach, In proc. ER’04, Springer Verlag LNCS 3288, pages 639-653, 2004

[43] Using AutoMed Metadata in Data Warehousing Environments, In Proc. DOLAP'03, pages 86-93.ACM Press, 2003

[44] Tracing Data Lineage Using Schema Transformation Pathways, In Knowledge Transformation for the Semantic Web, pages 64-79, IOS Press, Eds B.Omelayenko and M.Klein, 2003

[45] Tracing Data Lineage Using Automed Transformation Pathways, In Proc. BNCOD’02, Springer Verlag LNCS 2405, 2002

[46] Mao Jin, Cui Hong. Identifying bacterial biotope entities using sequence labeling: Performance and feature analysis[J]. Journal of the Association for Information Science and Technology, 2018

[47] Mao Jin, Cao Yujie, Lu Kun, Li Gang. Topic scientific community in science: a combined perspective of scientific collaboration and topics[J]. Scientometrics, 2017, 112(2):851-875.

[48] Mao Jin, Lu Kun, Li Gang, et al. Profiling users with tag networks in diffusion-based personalized recommendation[J]. Journal of Information Science, 2016, 42(5):711-722.

[49] Mao Jin, Moore L R, Blank C E, et al. Microbial phenomics information extractor (MicroPIE): a natural language processing tool for the automated acquisition of prokaryotic phenotypic characters from text sources:[J]. BMC Bioinformatics, 2016, 17(1):528.

[50] Mao Jin, Lu Kun, Mu Xiangming, Li Gang. Mining document, concept, and term associations for effective biomedical retrieval: introducing MeSH-enhanced retrieval models[J]. Information Retrieval Journal, 2015, 18(5):413-444.

[51] Zhao Wanying, Mao Jin, Lu Kun. Ranking themes on co-word networks: Exploring the relationships among different metrics[J]. Information Processing & Management, 2018, 54(2):203-218.

[52] Lu Kun, Mao Jin, Li Gang. Toward effective automated weighted subject indexing: A comparison of different approaches in different environments[J]. Journal of the Association for Information Science & Technology, 2018, 69(1).

[53] Lu Kun, Mao Jin. An automatic approach to weighted subject indexing—an empirical study in the biomedical domain[J]. Journal of the Association for Information Science & Technology, 2015, 66(9):1776–1784.

[54] 李纲, 毛进, 芦昆. 医学信息检索中一种基于概念的查询相似度模型[J]. 情报学报,2014(3):239-249.

[55] 李纲, 毛进.文本图表示模型及其在文本挖掘中的应用[J]. 情报学报,2013(12): 1257-1264.

[56] 毛进, 易明, 操玉杰, 等. 一种基于用户标签网络的个性化推荐方法[J]. 情报学报, 2012, 31(1): 23-30.

[57] 毛进,李纲. 一种基于OKM的研究领域专家图谱构建方法[J].图书情报工作,2014(13): 34-40.

[58] 毛进, 李纲, 操玉杰. 利用主题标引进行查询重排序[J]. 现代图书情报技术,2014, 30(7/8): 48-55.

[59] 李纲, 毛进. 元网络视角下的科研团队建模与分析[J]. 图书情报工作,2014,58(8): 65-72.

[60] 李纲,毛进, 陈璟浩.基于语义指纹快速聚类的中文文本去重[J]. 现代图书情报技术,2013(9): 41-47.

二、主要项目

Ø 国家自然科学基金面上项目,2018年,No. 61772375,16万元,主持

Ø 武汉大学信息管理学院自主科研项目,2018年,10万元,主持

Ø 中组部国家千人计划青年项目,2016年,信息科学,No. 104413100019,200

Ø 万元,主持

Ø 武汉大学人才引进项目,2016年,200万元,主持

Ø 武汉市“黄鹤英才计划”,1002-06060001, 2016年-2021年,开发一种基于扩增子测序和生物信息学分析鉴定微生物的新技术,100万元,主持

Ø 湖北省楚天学者(讲座教授),2014年,生物信息学

Ø 美国国家卫生研究院(NIH),R01HL111829,A network based approach to associate HDL subspeciation with function. 2012-2018, 265万美元,已结题,主持

Ø 美国国家科学基金(NSF),IOS-0843424,Probing the robustness of a developmental system, 2009-2014,150万美元,已结题,共同主持

Ø 美国国家卫生研究院(NIH),R01HL116226,MR predictors of infection, inflammation and structural lung damage in CF,2012-2016,215万美元,已结题,参与

Ø 美国国家卫生研究院(NIH),R01HL105433,Role of SREBP network in surfactant lipid homeostasis and lung maturation,2011-2016,218万美元,已结题,参与

Ø 比尔和梅琳达盖茨基金会(GAPPS),12002-Preventing preterm birth,Balance of Th17 cells and regulatory T cells in Candidal colonization in human vaginal tissue,2013-2015,45万美元,已结题,参与,排名第二

Ø 美国国家卫生研究院(NIH),R21AI111062,Translational repression and Aspergillus fumigatus,2014-2016,43万美元,已结题,参与,排名第二

Ø 美国国家卫生研究院(NIH),R21HL104136,The molecular basis for high density lipoprotein heterogeneity. 2010-2012,44万美元,已结题,参与,排名第二

Ø 大数据资源的挖掘与服务研究--面向医疗健康领域,教育部人文社会科学重点研究基地重大项目,2017.1-2020.12,(主持人,在研);

Ø 武汉大学“青年拔尖人才培养出国(境)研修计划”项目,2017,主持

Ø 基于语义网络的信息交流用户知识不对称研究,武汉大学信息管理学院世界一流学科建设项目,2018.1-2019.12,(主持,在研)

Ø 基于认知计算的学术论文评价理论与方法研究,2017年度国家社科基金重大项目,(参与,在研)

Ø 提高反恐怖主义情报信息工作能力对策研究,2017年度教育部哲学社会科学研究重大课题攻关项目,(参与,在研)

Ø 云环境下国家数字学术资源信息安全保障体系研究,国家社会科学基金重大项目,(批准号:14ZDB168)2015-2017(参与,在研)

Ø 一种基于深度学习神经网络的自闭症谱系障碍诊断模型设计, 国家自然科学基金面上项目,(批准号:61772375),2018.1-2018.12(参与,在研)

Ø 新媒体发展战略研究,主持,企业支持课题,2013.8~2014.9;

Ø 不确定性关系数据的溯源方法,参与,国家自然科学基金,2013.1~2015.12;

Ø 国家数字文化资源统一展示与服务平台,参与,科技部863子课题,2012.1~2014.12;

Ø D-SCDMA增强型多媒体数据卡的研发与产业化,主持,国家科技重大专项,2009.1~2010.12;

Ø 基于Web Services的蛋白质组学数据,主持,教育部留学基金,2008.10~2011.10;

Ø 湖湾理化因子与浮游生物的生态模型研究,主持,科技部863计划专题任务,2008.1~2008.12;

Ø 基于数字图书馆的本体演化与知识管理研究,参与,国家自然科学基金,2008.1~2010.12

Ø 国家自然科学基金青年项目,基于学术异质网络表示学习的知识群落发现,71804135,2019/01-2021/12,主持

Ø 中国博士后科学基金一等资助,融合语义与关系的科研社群识别与演化研究,2018M630885,2018/05-2020/10,在研,主持

Ø 武汉大学人文社科青年项目,学科交叉知识网络的结构特征研究,2018/03-2020/03, 在研,主持

Ø 国家自然科学基金重大项目,国家安全大数据综合信息集成与分析方法, 71790612,2018/01-2022/12,在研,主要成员

Ø 国家自然科学基金重点国际(地区)合作项目,大数据环境下的知识组织与服务创新研究, 71420107026,2015/01-2019/12,在研,主要成员

Ø 教育部哲学社会科学研究重大课题攻关项目,提高反恐怖主义情报信息工作能力对策研究,17JZD034,2018/01-2020/12,在研,主要成员

Ø 国家自然科学基金青年项目,突发公共卫生事件社交媒体信息主题演化与影响力建模,71603189,2017/01-2019/12,在研,主要成员

Ø 美国国家自然科学基金项目, Next Generation Phenomics for the Tree of Life, 2012/05-2015/06, NSF DEB-1208567,已结题

三、主要特色

综合数据科学、生物信息学、计算机科学、情报学、管理科学与工程等多学科理论方法,以生物信息挖掘、医学图像深度学习、智慧医学教育、智慧医学考试、电子病历质量评估、慢病知识管理等为特色方向,通过与政府、医院、信息服务企业、高校等的深度合作,打造国内一流、国际知名的儿童颅脑健康大数据研究中心。

 


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