Publication

23.     Optimal Transport on Manifold for Domain Adaptation. Submitted

22.     Graph Refinement via Simultaneously Low-rank and Sparse Approximation. Submitted

21.     Drug repositioning via matrix completion with multi-view side information. Submitted.

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2019

 

20. Limin Li, Menglan Cai, Cross-species Data Classification by Domain Adaptation via Discriminative Heterogeneous Maximum Mean Discrepancy. Accepted by IEEE/ACM transactions on Computational Biology and Bioinformatics(TCBB) 2019

 

2018

19.Menglan Cai, Limin Li. rPCMP: robust p-value combination by multiple partitions with applications to ATAC-seq data.   BMC Systems Biology. 2018

18.Limin Li, Zhenyue Zhang. Semi-supervised Domain Adaptation by Covariance MatchingIEEE transactions on Pattern Analysis and Machine Intelligence(TPAMI).2018

17. Limin Li, Xiao He and Karsten Borgwardt. Multi-target drug repositioning by bipartite block-wise sparse multi-task learningBMC systems biology 2018 

 

2017

16. Menglan Cai, Limin Li*. Subtype identification from heterogeneous TCGA datasets on a genomic scale by multi-view learning with enhanced consensus. BMC Medical Genomics 2017 

15.  Xiao He, Limin Li, Damian Roqueiro and Karsten Borgwardt. Multi-view Spectral Clustering on Conflicting Views. ECML/PKDD 2017

14. Limin Li, Menglan Cai. Drug target prediction by multi-view low rank embedding.  IEEE/ACM transactions on Computational Biology and Bioinformatics(TCBB). 2017

13.  Xinzhang, Limin Li, Michael K Ng, Shuqin Zhang, Drug-target Interaction Prediction by Integrating Multiview Network Data.  Computational biololgy and chemistry. Volumn 69, pages 185-193, 2017

12. Zhenyue Zhang, Zheng Zhai and Limin Li*. Uniform projection for multi-view learning.  IEEE transactions on Pattern Analysis and Machine Intelligence(TPAMI). Volumn 39, Issue 8. 2017 (corresponding author)

 

2015 and Before

11. Limin Li, Shuqin Zhang. Orthogonal projection correction for confounders in biological data classification. International journal of data mining and bioinformatics. vol 13, No 2. 2015. 

10. Limin Li, Kiyoko F Aoki-Kinoshita, Wai-Ki Ching,Hao Jiang.  On Using Physico-Chemical Properties of Amino Acids in String Kernels for Protein Classification via Support Vector Machines.  Journal of Systems Science and Complexity ,2015 28(2) 504-516

9. Limin Li. MPGraph: : Multi-view Penalized Graph Clustering for Predicting Drug-target Interactions. IET Systems Biology  ,Vol8:2,pp67-73, 2014

8. Limin Li, Hao Jiang, Yushan Qiu, Wai-Ki Ching, Vassilios S Vassiliadis. Discovery of metabolite biomarkers: flux

     analysis and reaction-reaction network approachBMC Systems Biology , 7:S13 2013

7. Limin Li, Barbara Rakitsch, Karsten Borgwardt. ccSVM: correcting Support Vector Machines for confounding factors in biological data classification. Bioinformatics 2011 Vol 27, issue 13: ppi343-i348 (ISMB Proceeding 2011)  

6. Limin Li, Xiaobo Zhou, Wai-Ki Ching and Ping Wang. Predicting Enzyme Targets for Cancer Drugs by Profiling Human Metabolic Reactions in NCI-60 Cell lines. BMC Bioinformatics 2010,11:501. 

5. Limin Li, Wai-Ki Ching, Yat-Ming Chan and Hiroshi Mamitsuka.  On Network-Based Kernel Methods for Protein-Protein Interactions with Application in Protein Function Prediction.  Journal of Systems Science and Complexity, 23(2010) 917-930. 

4. Limin Li, Wai-Ki Ching, Taga Yamaguchi and Kiyoko F. Aoki-Kinoshita. Weighted q-gram method for Glycan Classification.BMC Bioinformatics 2010, 11(S1):S33. 

3. Wai-Ki Ching, Limin Li*, Nam-Kiu Tsing, Alice S.Wong and Kwai-Wa Ching. A Weighted Local Least Squares Imputation Method for Missing Value Estimation in Microarray Gene Expression Data. International Journal of Data Mining and Bioinformatics, Vol. 4, No.3 pp. 331 - 347 (2010). (* Corresponding author) 

2. Wai-Ki Ching, Limin Li, Yat-Ming Chan and Hiroshi Mamitsuka. A Study of Network-based Kernel Methods on Protein-Protein Interaction for Protein Functions Prediction. The International Symposium on Optimization and Systems Biology, (OSB 2009).

1. Limin Li, Motoki Shiga, Wai-Ki Ching and Hiroshi Mamitsuka. Genome-wide Function Annotation with Network Modularity-based Clustering Using Sequence Similarities and Microarray Expressions. Genome Informatics Vol.22 (2009): 95-120.

 

项目

1. 国家自然科学基金重点项目, 11631012,典型疾病的多尺度生物系统动力学及数据分析,2017/01-2021/12, 245万元,参与

2. 国家自然科学基金面上项目,11471256,面向基因组相关性研究的迁移学习理论与方法,2015/01-2018/1270万元,主持

3. 国家自然科学基金面上项目,61370006,面向多领域数据的联合流形学习方法及在迁移学习中的应用,2014/01-2017/12, 58万,参与

4. 国家自然科学基金重大研究计划, 91230112,多视野高维复杂数据融合降维方法与理论研究,2013/01-2015/1265万,参与

5. 国家自然科学基金青年科学基金项目,11101328,关于基因组相关性研究中人口结构问题的机器学习方法,2012/01-2014/1222万元,主持

Professional Services

Regular Reviewer of 

NIPS,ICML,PKDD/ECML,AISTAT

PC member of ACML;

Bioinformatics,

IEEE Transactions on Pattern Analysis and Machine Intelligence, 

IEEE Transactions on Computational Biology and Bioinformatics,

IEEE Transactions on Knowledge and Data Engineering,

Machine Learning