Multi-instance multi-label distance metric learning for genome-wide protein function prediction

[1]  Philip S. Yu,et al.  Adaptation Regularization: A General Framework for Transfer Learning , 2014, IEEE Transactions on Knowledge and Data Engineering.

[2]  Daniel W. A. Buchan,et al.  A large-scale evaluation of computational protein function prediction , 2013, Nature Methods.

[3]  Zili Zhang,et al.  Protein Function Prediction by Integrating Multiple Kernels , 2013, IJCAI.

[4]  Quaid Morris,et al.  Fast integration of heterogeneous data sources for predicting gene function with limited annotation , 2010, Bioinform..

[5]  David A. Cieslak,et al.  Learning Decision Trees for Unbalanced Data , 2008, ECML/PKDD.

[6]  Chih-Jen Lin,et al.  LIBSVM: A library for support vector machines , 2011, TIST.

[7]  林继红,et al.  古细菌(Archaebacteria)表面糖蛋白 , 1990 .

[8]  G. A. Edgar.  Measure, Topology, and Fractal Geometry , 1990 .

[9]  Suyu Mei,et al.  Predicting plant protein subcellular multi-localization by Chou's PseAAC formulation based multi-label homolog knowledge transfer learning. , 2012, Journal of theoretical biology.

[10]  Yunming Ye,et al.  Protein functional properties prediction in sparsely-label PPI networks through regularized non-negative matrix factorization , 2015, BMC Systems Biology.

[11]  Shin Ando.  Classifying imbalanced data in distance-based feature space , 2015, Knowledge and Information Systems.

[12]  Zhi-Hua Zhou,et al.  Multi-Instance Multi-Label Learning with Application to Scene Classification , 2006, NIPS.

[13]  Kilian Q. Weinberger,et al.  Distance Metric Learning for Large Margin Nearest Neighbor Classification , 2005, NIPS.

[14]  D. Eisenberg,et al.  A combined algorithm for genome-wide prediction of protein function , 1999, Nature.

[15]  Min-Ling Zhang,et al.  A k-Nearest Neighbor Based Multi-Instance Multi-Label Learning Algorithm , 2010, 2010 22nd IEEE International Conference on Tools with Artificial Intelligence.

[16]  Brian Kulis,et al.  Metric Learning: A Survey , 2013, Found. Trends Mach. Learn..

[17]  Jun Wang,et al.  Solving the Multiple-Instance Problem: A Lazy Learning Approach , 2000, ICML.

[18]  C. Woese,et al.  Phylogenetic structure of the prokaryotic domain: The primary kingdoms , 1977, Proceedings of the National Academy of Sciences of the United States of America.

[19]  Suyu Mei.  Corrigendum to “Predicting plant protein subcellular multi-localization by Chou's PseAAC formulation based multi-label homolog knowledge transfer learning” [J. Theor. Biol. 310 (2012) 80–87] , 2013 .

[20]  Qiang Yang,et al.  A Survey on Transfer Learning , 2010, IEEE Transactions on Knowledge and Data Engineering.

[21]  M. Ashburner,et al.  Gene Ontology: tool for the unification of biology , 2000, Nature Genetics.

[22]  Inderjit S. Dhillon,et al.  Information-theoretic metric learning , 2006, ICML '07.

[23]  Xiao Sun,et al.  A novel method for quantitatively predicting non-covalent interactions from protein and nucleic acid sequence. , 2011, Journal of molecular graphics & modelling.

[24]  Vasant Honavar,et al.  Exploring inconsistencies in genome-wide protein function annotations: a machine learning approach , 2007, BMC Bioinformatics.

[25]  Zhi-Hua Zhou,et al.  Genome-Wide Protein Function Prediction through Multi-Instance Multi-Label Learning , 2014, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[26]  Zhi-Hua Zhou,et al.  Multi-Label Learning by Instance Differentiation , 2007, AAAI.

[27]  O. Kandler,et al.  Towards a natural system of organisms: proposal for the domains Archaea, Bacteria, and Eucarya. , 1990, Proceedings of the National Academy of Sciences of the United States of America.

[28]  Ian T. Jolliffe,et al.  Principal Component Analysis , 2002, International Encyclopedia of Statistical Science.

[29]  Yunming Ye,et al.  Markov-Miml: A Markov chain-based multi-instance multi-label learning algorithm , 2012, Knowledge and Information Systems.

[30]  Zhiwen Yu,et al.  Transductive multi-label ensemble classification for protein function prediction , 2012, KDD.

[31]  Zhi-Hua Zhou,et al.  Multi-instance multi-label learning , 2008, Artif. Intell..