Jinyan Li
Jinyan Li
Distinguished Professor, 深圳理工大学;Adjunct Professor, University of Technology Sydney
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Classification, subtype discovery, and prediction of outcome in pediatric acute lymphoblastic leukemia by gene expression profiling
EJ Yeoh, ME Ross, SA Shurtleff, WK Williams, D Patel, R Mahfouz, ...
Cancer cell 1 (2), 133-143, 2002
Efficient mining of emerging patterns: Discovering trends and differences
G Dong, J Li
Proceedings of the fifth ACM SIGKDD international conference on Knowledge …, 1999
A comparative study on feature selection and classification methods using gene expression profiles and proteomic patterns
H Liu, J Li, L Wong
Genome informatics 13, 51-60, 2002
CAEP: Classification by aggregating emerging patterns
G Dong, X Zhang, L Wong, J Li
Discovery Science: Second International Conference, DS’99 Tokyo, Japan …, 1999
Making use of the most expressive jumping emerging patterns for classification
J Li, G Dong, K Ramamohanarao
Knowledge and Information systems 3 (2), 131-145, 2001
Identifying good diagnostic gene groups from gene expression profiles using the concept of emerging patterns
J Li, L Wong
Bioinformatics 18 (5), 725-734, 2002
Mining border descriptions of emerging patterns from dataset pairs
G Dong, J Li
Knowledge and Information Systems 8 (2), 178-202, 2005
Deeps: A new instance-based lazy discovery and classification system
J Li, G Dong, K Ramamohanarao, L Wong
Machine Learning 54 (2), 99-124, 2004
Simple rules underlying gene expression profiles of more than six subtypes of acute lymphoblastic leukemia (ALL) patients
J Li, H Liu, JR Downing, AEJ Yeoh, L Wong
Bioinformatics 19 (1), 71-78, 2003
Automatic classification for field crop insects via multiple-task sparse representation and multiple-kernel learning
C Xie, J Zhang, R Li, J Li, P Hong, J Xia, P Chen
Computers and Electronics in Agriculture 119, 123-132, 2015
Interestingness of discovered association rules in terms of neighborhood-based unexpectedness
G Dong, J Li
Research and Development in Knowledge Discovery and Data Mining: Second …, 1998
Discovery of significant rules for classifying cancer diagnosis data
J Li, H Liu, SK Ng, L Wong
Bioinformatics 19 (suppl_2), ii93-ii102, 2003
Mining statistically important equivalence classes and delta-discriminative emerging patterns
J Li, G Liu, L Wong
Proceedings of the 13th ACM SIGKDD international conference on Knowledge …, 2007
Maximal biclique subgraphs and closed pattern pairs of the adjacency matrix: A one-to-one correspondence and mining algorithms
J Li, G Liu, H Li, L Wong
IEEE Transactions on Knowledge and Data Engineering 19 (12), 1625-1637, 2007
Prediction of 8-state protein secondary structures by a novel deep learning architecture
B Zhang, J Li, Q Lü
BMC bioinformatics 19 (1), 1-13, 2018
Septic shock prediction for ICU patients via coupled HMM walking on sequential contrast patterns
S Ghosh, J Li, L Cao, K Ramamohanarao
Journal of biomedical informatics 66, 19-31, 2017
Instance-based classification by emerging patterns
J Li, G Dong, K Ramamohanarao
European Conference on Principles of Data Mining and Knowledge Discovery …, 2000
The long noncoding RNA MALAT1 promotes tumor-driven angiogenesis by up-regulating pro-angiogenic gene expression
AE Tee, B Liu, R Song, J Li, E Pasquier, BB Cheung, C Jiang, ...
Oncotarget 7 (8), 8663-8675, 2016
Prediction by collective likelihood from emerging patterns
J Li
US Patent App. 10/524,606, 2006
Sequence-based prediction of protein-protein interaction sites by simplified long short-term memory network
B Zhang, J Li, L Quan, Y Chen, Q Lü
Neurocomputing 357, 86-100, 2019
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