Zheng Rong Yang

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45EEZheng Rong Yang: Crosstalk and Signalling Pathway Complexity - A Case Study on Synthetic Models. HAIS 2008: 696-705
44EEZheng Rong Yang: Explore Residue Significance in Peptide Classification. HAIS 2008: 706-713
43EEZheng Rong Yang: Single-Layer Neural Net Competes with Multi-layer Neural Net. IDEAL 2008: 516-524
42EEDavid C. Trudgian, Zheng Rong Yang: Substitution Matrix Optimisation for Peptide Classification. EvoBIO 2007: 291-300
41EEDavid C. Trudgian, Zheng Rong Yang: A Sparse Bayesian Position Weighted Bio-Kernel Network. IDEAL 2007: 527-536
40 Zheng Rong Yang: Peptide Classification with Genetic Programming Ensemble of Generalised Indicator Models. IMECS 2007: 319-324
39EEZheng Rong Yang: Predicting Palmitoylation Sites Using a Regularised Bio-basis Function Neural Network. ISBRA 2007: 406-417
38EEZheng Rong Yang: A Probabilistic Peptide Machine for Predicting Hepatitis C Virus Protease Cleavage Sites. IEEE Transactions on Information Technology in Biomedicine 11(5): 593-595 (2007)
37EENatasha Young, Zheng Rong Yang: Multivariate Crosstalk Models. IDEAL 2006: 1129-1136
36EEZheng Rong Yang: A Fast Algorithm for Relevance Vector Machine. IDEAL 2006: 33-39
35EEAlex C. Thomas, Zheng Rong Yang: Improved Prediction of HIV-1 Protease Genotypic Resistance Testing Assays using a Consensus Technique. IJCNN 2006: 2308-2314
34EEDavid C. Trudgian, Felicia Charles Johnson, Zheng Rong Yang: Predicting HIV-1 T Cell Epitopes Using Bio-basis Function Neural Networks. IJCNN 2006: 3586-3593
33EEZheng Rong Yang: A novel radial basis function neural network for discriminant analysis. IEEE Transactions on Neural Networks 17(3): 604-612 (2006)
32EEZheng Rong Yang, Jonathan Dry, Rebecca Thomson, T. Charles Hodgman: A bio-basis function neural network for protein peptide cleavage activity characterisation. Neural Networks 19(4): 401-407 (2006)
31EEZheng Rong Yang, Natasha Young: Bio-kernel Self-organizing Map for HIV Drug Resistance Classification. ICNC (1) 2005: 179-186
30EEZheng Rong Yang: Bayesian Radial Basis Function Neural Network. IDEAL 2005: 211-219
29EEZheng Rong Yang: Mining SARS-CoV protease cleavage data using non-orthogonal decision trees: a novel method for decisive template selection. Bioinformatics 21(11): 2644-2650 (2005)
28EEZheng Rong Yang, Rebecca Thomson, Philip McNeil, Robert Esnouf: RONN: the bio-basis function neural network technique applied to the detection of natively disordered regions in proteins. Bioinformatics 21(16): 3369-3376 (2005)
27EEZheng Rong Yang: Prediction of caspase cleavage sites using Bayesian bio-basis function neural networks. Bioinformatics 21(9): 1831-1837 (2005)
26EEZheng Rong Yang: Orthogonal kernel Machine for the prediction of functional sites in proteins. IEEE Transactions on Systems, Man, and Cybernetics, Part B 35(1): 100-106 (2005)
25EEPasak Senawongse, Andrew R. Dalby, Zheng Rong Yang: Predicting the Phosphorylation Sites Using Hidden Markov Models and Machine Learning Methods. Journal of Chemical Information and Modeling 45(4): 1147-1152 (2005)
24EEZheng Rong Yang, Felicia Charles Johnson: Prediction of T-Cell Epitopes Using Biosupport Vector Machines. Journal of Chemical Information and Modeling 45(5): 1424-1428 (2005)
23 Zheng Rong Yang, Richard M. Everson, Hujun Yin: Intelligent Data Engineering and Automated Learning - IDEAL 2004, 5th International Conference, Exeter, UK, August 25-27, 2004, Proceedings Springer 2004
22EEZheng Rong Yang: Mining gene expression data based on template theory. Bioinformatics 20(16): 2759-2766 (2004)
21EEZheng Rong Yang, Andrew R. Dalby, Jing Qiu: Mining HIV protease cleavage data using genetic programming with a sum-product function. Bioinformatics 20(18): 3398-3405 (2004)
20EEZheng Rong Yang, Kuo-Chen Chou: Bio-support vector machines for computational proteomics. Bioinformatics 20(5): 735-741 (2004)
19EEZheng Rong Yang, Kuo-Chen Chou: Predicting the linkage sites in glycoproteins using bio-basis function neural network. Bioinformatics 20(6): 903-908 (2004)
18 Zheng Rong Yang: Biological applications of support vector machines. Briefings in Bioinformatics 5(4): 328-338 (2004)
17EEEmily A. Berry, Andrew R. Dalby, Zheng Rong Yang: Reduced bio basis function neural network for identification of protein phosphorylation sites: comparison with pattern recognition algorithms. Computational Biology and Chemistry 28(1): 75-85 (2004)
16EEZheng Rong Yang, Emily A. Berry: Reduced Bio-basis Function Neural Networks for Protease Cleavage Site Prediction. J. Bioinformatics and Computational Biology 2(3): 511-532 (2004)
15EEVishwesh Venkatraman, Andrew R. Dalby, Zheng Rong Yang: Evaluation of Mutual Information and Genetic Programming for Feature Selection in QSAR. Journal of Chemical Information and Modeling 44(5): 1686-1692 (2004)
14EEEmily A. Berry, Zheng Rong Yang, Xikun Wu: A Biology Inspired Neural Learning Algorithm for Analysing Protein Sequence. ICTAI 2003: 18-25
13 Rebecca Thomson, T. Charles Hodgman, Zheng Rong Yang, Austin K. Doyle: Characterizing proteolytic cleavage site activity using bio-basis function neural networks. Bioinformatics 19(14): 1741-1747 (2003)
12EEZheng Rong Yang, Kuo-Chen Chou: Mining Biological Data Using Self-Organizing Map. Journal of Chemical Information and Computer Sciences 43(6): 1748-1753 (2003)
11 Ajit Narayanan, Xikun Wu, Zheng Rong Yang: Mining viral protease data to extract cleavage knowledge. ISMB 2002: 5-13
10EEZheng Rong Yang, Robert G. Harrison: Analysing company performance using templates. Intell. Data Anal. 6(1): 3-15 (2002)
9EEZheng Rong Yang, Mark Zwolinski: Mutual Information Theory for Adaptive Mixture Models. IEEE Trans. Pattern Anal. Mach. Intell. 23(4): 396-403 (2001)
8 Zheng Rong Yang, Weiping Lu, Robert G. Harrison: Evolving Stacked Time Series Predictors with Multiple Window Scales and Sampling Gaps. Neural Processing Letters 13(3): 203-211 (2001)
7EEZheng Rong Yang, Mark Zwolinski: Applying Mutual Information to Adaptive Mixture Models. IDEAL 2000: 250-255
6EEZheng Rong Yang: Stability Analysis of Financial Ratios. IDEAL 2000: 256-261
5EEZheng Rong Yang, Weiping Lu, Dejin Yu, Robert G. Harrison: Detecting False Benign in Breast Cancer Diagnosis. IJCNN (3) 2000: 655-658
4EEZheng Rong Yang, Robert G. Harrison, Weiping Lu: Identifying Health Inequalities Using Artificial Neural Networks (WHO Data). IJCNN (4) 2000: 113-118
3EEZheng Rong Yang, Mark Zwolinski, Chris D. Chalk, Alan Christopher Williams: Applying a robust heteroscedastic probabilistic neural network toanalog fault detection and classification. IEEE Trans. on CAD of Integrated Circuits and Systems 19(1): 142-151 (2000)
2EEZheng Rong Yang, Mark Zwolinski: Fast, Robust DC and Transient Fault Simulation for Nonlinear Analog Circuits. DATE 1999: 244-248
1EEZheng Rong Yang, Sheng Chen: Robust maximum likelihood training of heteroscedastic probabilistic neural networks. Neural Networks 11(4): 739-747 (1998)

Coauthor Index

1Emily A. Berry [14] [16] [17]
2Chris D. Chalk [3]
3Sheng Chen [1]
4Kuo-Chen Chou [12] [19] [20]
5Andrew R. Dalby [15] [17] [21] [25]
6Austin K. Doyle [13]
7Jonathan Dry [32]
8Robert Esnouf [28]
9Richard M. Everson [23]
10Robert G. Harrison [4] [5] [8] [10]
11Charlie Hodgman (T. Charles Hodgman) [13] [32]
12Felicia Charles Johnson [24] [34]
13Weiping Lu [4] [5] [8]
14Philip McNeil [28]
15Ajit Narayanan [11]
16Jing Qiu [21]
17Pasak Senawongse [25]
18Alex C. Thomas [35]
19Rebecca Thomson [13] [28] [32]
20David C. Trudgian [34] [41] [42]
21Vishwesh Venkatraman [15]
22Alan Christopher Williams [3]
23Xikun Wu [11] [14]
24Hujun Yin [23]
25Natasha Young [31] [37]
26Dejin Yu [5]
27Mark Zwolinski [2] [3] [7] [9]

Colors in the list of coauthors

Copyright © Sun May 17 03:24:02 2009 by Michael Ley (ley@uni-trier.de)