Dr Pengyi Yang

DECRA Fellow and Senior Lecturer

F07 - Carslaw Building
The University of Sydney


Website Lab website

Biographical details

I obtained my PhD in bioinformatics from School of Information Technologies, The University of Sydney, in 2012. I subsequently moved to the United States and completed an interdisciplinary Research Fellowship in Systems Biology Group, Epigenetics & Stem Cell Biology Laboratory, at National Institutes of Health, on characterising transcriptomic and epigenomic regulations in embryonic stem cells (ESCs) using ultrafast sequencing data. I relocated back to Australia in late 2015 on a University of Sydney Postdoctoral Fellowship (DVC Research) to pursue my own research in systems biology. I'm now a Senior Lecturer in School of Mathematics and Statistics (SoMS). I started my own research group in Charles Perkins Centre (CPC) in 2017 with a Discovery Early Career Researcher Award (DECRA) Fellowship.

Research interests

The computational trans-omics group led by Dr. Yang is interested in using systems approach to characterise cell signalling, epigenetic and transcriptional networks, and their cross-talk and cross-regulations. Specifically, the group specialises in developing computational methods and statistical models that cut across mass spectrometry (MS)-based proteomics and phosphoproteomics data, and next-generation sequencing (NGS)-based RNA-seq, ChIP-seq and Hi-C data. By building up computational pipelines and developing novel methodologies, we collaborate closely with molecular biologists to elucidate core regulatory circuitry underline cellular homeostasis, proliferation, differentiation, and cell-fate decisions.

Research team members:

  • Taiyun Kim - Research Associate
  • Irene Chen - Research Assistant
  • Chendong Ma - Honours Student (USyd); in collaboration with Prof Jean Yang
  • Dinuka Perera - Talented Student Program (USyd); in collaboration with Prof David James

Teaching and supervision

2016 Semester 2: Computational Statistical Methods (STAT5003), Lecturer
2017 Semester 1: Nature of Systems (HTIN5001), Guest Lecturer
2017 Semester 2: Computational Statistical Methods (STAT5003), Lecturer

Timetable

P_Yang

Current projects

The computational trans-omics group works in the broad areas of computational and systems biology with a focus on cell signaling, epigenetic, and transcriptional networks.

Please visit our lab website to find out more details on current and potential projects.

Join our group!

The computational trans-omics group is an integral part of a larger team guided by Prof Jean Yang and Prof David James. Their expertise facilitates our development in using not only computational techniques but also rigorous mathematics and statistics to address fundamental and translational biological questions.

If you are interested in joining our team, please send your expression of interest and CV to pengyi.yang@sydney.edu.au

Awards and honours

  • 2017 Finalist of Eureka Prize for Outstanding Early Career Researcher, Australian Museum
  • 2017 J G Russell Award, Australian Academy of Science, Australia
  • 2017 – 2020 Australian Research Council (ARC)/Discovery Early Career Researcher Award (DECRA), Australia
  • 2015 – 2018 University of Sydney Postdoctoral Fellowship (DVC Research), The University of Sydney, Australia
  • 2015 Fellows Award for Research Excellence, National Institutes of Health, USA
  • 2014 Paper of the Year Award, National Institute of Environmental Sciences, National Institutes of Health, USA
  • 2014 Fellows Award for Research Excellence, National Institutes of Health, USA
  • 2012 – 2016 Research Fellowship, National Institutes of Health, USA
  • 2009 – 2012 National ICT Australia (NICTA) International Postgraduate Award (NIPA), Australia
  • 2009 – 2012 National ICT Australia (NICTA) Research Project Award (NRPA), Australia
  • 2009 Best Thesis Award on Master of Engineering, Chongqing Education Commission, China
  • 2008 Student Travel Award, International Conference on Pattern Recognition in Bioinformatics (PRIB 2008), Melbourne, Australia
  • 2005 – 2008 National Scholarship Award on Master of Engineering, Ministry of Education of the People’s Republic of China

In the media

  • https://factor.niehs.nih.gov/2017/11/feature/feature-3-protein/index.htm
  • http://sydney.edu.au/news-opinion/news/2017/07/28/four-sydney-finalists-announced-in-eureka-science-awards.html
  • https://www.science.org.au/news-and-events/news-and-media-releases/young-researchers-win-support-academy
  • http://www.garvan.org.au/news-events/news/mathematicians-solving-today2019s-problems-of-2018systems-biology2019

International links

United States

(National Institute of Environmental Health Sciences, National Institutes of Health) Collaborating with Dr. Raja Jothi, Principal Investigator of Systems Biology Group in Epigenetics & Stem Cell Biology Laboratory.

Selected grants

2017

  • Trans-omic networks: a machine learning and omics integration approach; Yang P; Australian Research Council (ARC)/Discovery Early Career Researcher Award (DECRA).
  • Prognosis based network-type feature extraction for complex biological data; Yang J, Mueller S, Ormerod J, Yang P, Mann G; Australian Research Council (ARC)/Discovery Projects (DP).

2015

  • Computational approaches for imaging genomics: integrating neuroimaging and genomics data; Yang P, Yang J; DVC Research/Postdoctoral Research Fellowship Scheme.

Selected publications

Download citations: PDF RTF Endnote

Book Chapters

  • Yang, P., Zhou, B., Yang, J., Zomaya, A. (2014). Stability of Feature Selection Algorithms and Ensemble Feature Selection Methods in Bioinformatics. In Mourad Elloumi, Albert Y. Zomaya (Eds.), Biological Knowledge Discovery Handbook: Preprocessing, Mining and Postprocessing of Biological Data, (pp. 333-352). New Jersey: John Wiley & Sons. [More Information]

Journals

  • Norris, D., Yang, P., Krycer, J., Fazakerley, D., James, D., Burchfield, J. (2017). An improved Akt reporter reveals intra- and inter-cellular heterogeneity and oscillations in signal transduction. Journal of Cell Science, 130, 2757-2766. [More Information]
  • Yang, P., Oldfield, A., Taiyun, K., Yang, A., Yang, J., Ho, J. (2017). Integrative analysis identifies co-dependent gene expression regulation of BRG1 and CHD7 at distal regulatory sites in embryonic stem cells. Bioinformatics, 33(3), 1916-1920. [More Information]
  • Yang, P., Oldfield, A., Kim, T., Yang, A., Yang, J., Ho, J. (2017). Integrative analysis identifies co-dependent gene expression regulation of BRG1 and CHD7 at distal regulatory sites in embryonic stem cells. Bioinformatics, 33(13), 1916-1920. [More Information]
  • Cinghu, S., Yang, P., Kosak, J., Conway, A., Kumar, D., Oldfield, A., Adelman, K., Jothi, R. (2017). Intragenic Enhancers Attenuate Host Gene Expression. Molecular Cell, 68(1), 104-117. [More Information]
  • Zheng, X., Yang, P., Lackford, B., Bennett, B., Wang, L., Li, H., Wang, Y., Miao, Y., Foley, J., Fargo, D., et al (2016). CNOT3-Dependent mRNA Deadenylation Safeguards the Pluripotent State. Stem cell reports, 7(5), 897-910. [More Information]
  • Yang, P., Patrick, E., Humphrey, S., Ghazanfar, S., James, D., Jothi, R., Yang, J. (2016). KinasePA: Phosphoproteomics data annotation using hypothesis driven kinase perturbation analysis. Proteomics, 16(13), 1868-1871. [More Information]
  • Minard, A., Tan, S., Yang, P., Fazakerley, D., Domanova, W., Parker, B., Humphrey, S., Jothi, R., Stoeckli, J., James, D. (2016). mTORC1 Is a Major Regulatory Node in the FGF21 Signaling Network in Adipocytes. Cell Reports, 17(1), 29-36. [More Information]
  • Lu, C., Wang, J., Zhang, Z., Yang, P., Yu, G. (2016). NoisyGOA: Noisy GO annotations prediction using taxonomic and semantic similarity. Computational Biology and Chemistry, 65, 203-211. [More Information]
  • Yang, P., Humphrey, S., James, D., Yang, J., Jothi, R. (2016). Positive-unlabeled ensemble learning for kinase substrate prediction from dynamic phosphoproteomics data. Bioinformatics, 32(2), 252-259. [More Information]
  • Domanova, W., Krycer, J., Chaudhuri, R., Yang, P., Vafaee, F., Fazakerley, D., Humphrey, S., James, D., Kuncic, Z. (2016). Unraveling Kinase Activation Dynamics Using Kinase-Substrate Relationships from Temporal Large-Scale Phosphoproteomics Studies. PloS One, 11(6), 1-14. [More Information]
  • Pathania, R., Ramachandran, S., Elangovan, S., Padia, R., Yang, P., Cinghu, S., Veeranan-Karmegam, R., Arjunan, P., Gnana-Prakasam, J., Sadanand, F., et al (2015). DNMT1 is essential for mammary and cancer stem cell maintenance and tumorigenesis. Nature Communications, 6, 1-11. [More Information]
  • Hoffman, N., Parker, B., Chaudhuri, R., Fisher-Wellman, K., Kleinert, M., Humphrey, S., Yang, P., Holliday, M., Trefely, S., Fazakerley, D., Stoeckli, J., Burchfield, J., James, D., et al (2015). Global Phosphoproteomic Analysis of Human Skeletal Muscle Reveals a Network of Exercise-Regulated Kinases and AMPK Substrates. Cell Metabolism, 22(5), 922-935. [More Information]
  • Yang, P., Zheng, X., Jayaswal, V., Hu, G., Yang, J., Jothi, R. (2015). Knowledge-Based Analysis for Detecting Key Signaling Events from Time-Series Phosphoproteomics Data. PLoS Computational Biology, 11(8), 1-18. [More Information]
  • Yang, P., Patrick, E., Tan, S., Fazakerley, D., Burchfield, J., Gribben, C., Prior, M., James, D., Yang, J. (2014). Direction pathway analysis of large-scale proteomics data reveals novel features of the insulin action pathway. Bioinformatics, 30(6), 808-814. [More Information]
  • Lackford, B., Yao, C., Charles, G., Weng, L., Zheng, X., Choi, E., Xie, X., Wan, J., Xing, Y., Freudenberg, J., et al (2014). Fip1 regulates mRNA alternative polyadenylation to promote stem cell self-renewal. The EMBO Journal, 33(8), 878-889. [More Information]
  • Oldfield, A., Yang, P., Conway, A., Cinghu, S., Freudenberg, J., Yellaboina, S., Jothi, R. (2014). Histone-fold domain protein NF-Y promotes chromatin accessibility for cell type-specific master transcription factors. Molecular Cell, 55(5), 708-722. [More Information]
  • Ma, X., Yang, P., Kaplan, W., Lee, B., Wu, L., Yang, J., Yasunaga, M., Sato, K., Chisholm, D., James, D. (2014). ISL1 Regulates Peroxisome Proliferator-Activated Receptor gamma Activation and Early Adipogenesis via Bone Morphogenetic Protein 4-Dependent and -Independent Mechanisms. Molecular and Cellular Biology, 34(19), 3607-3617. [More Information]
  • Yang, P., Yoo, P., Fernando, J., Zhou, B., Zhang, Z., Zomaya, A. (2014). Sample Subset Optimization Techniques for Imbalanced and Ensemble Learning Problems in Bioinformatics Applications. IEEE Transactions on Cybernetics, 44(3), 445-455. [More Information]
  • Humphrey, S., Yang, G., Yang, P., Fazakerley, D., Stockli, J., Yang, J., James, D. (2013). Dynamic adipocyte phosphoproteome reveals that akt directly regulates mTORC2. Cell Metabolism, 17(6), 1009-1020. [More Information]
  • Yang, P., Ma, J., Wang, P., Zhu, Y., Zhou, B., Yang, J. (2012). Improving X!Tandem on peptide identification from mass spectrometry by self-boosted percolator. IEEE - ACM Transactions on Computational Biology and Bioinformatics, 9(5), 1273-1280. [More Information]
  • Wang, P., Yang, P., Yang, J. (2012). OCAP: an open comprehensive analysis pipeline for iTRAQ. Bioinformatics, 28(10), 1404-1405. [More Information]
  • Yang, P., Humphrey, S., Fazakerley, D., Prior, M., Yang, G., James, D., Yang, J. (2012). Re-Fraction: A machine learning approach for deterministic identification of protein homologues and splice variants in large-scale MS-based proteomics. Journal of Proteome Research, 11(5), 3035-3045. [More Information]
  • Yang, P., Ho, J., Yang, J., Zhou, B. (2011). Gene-gene interaction filtering with ensemble of filters. BMC Bioinformatics, 12(Supp 1: S10), 1-10. [More Information]
  • Yang, P., Zhang, Z., Zhou, B., Zomaya, A. (2010). A clustering based hybrid system for biomarker selection and sample classification of mass spectrometry data. Neurocomputing, 73(13-15), 2317-2331. [More Information]
  • Wang, P., Yang, P., Arthur, J., Yang, J. (2010). A dynamic wavelet-based algorithm for pre-processing tandem mass spectrometry data. Bioinformatics, 26(18), 2242-2249. [More Information]
  • Yang, P., Ho, J., Zomaya, A., Zhou, B. (2010). A genetic ensemble approach for gene-gene interaction identification. BMC Bioinformatics, 11(524), 1-15. [More Information]
  • Yang, P., Zhou, B., Zhang, Z., Zomaya, A. (2010). A multi-filter enhanced genetic ensemble system for gene selection and sample classification of microarray data. BMC Bioinformatics, 11(Suppl 1), S5-1-S5-12. [More Information]
  • Yang, P., Yang, J., Zhou, B., Zomaya, A. (2010). A Review of Ensemble Methods in Bioinformatics. Current Bioinformatics, 5(4), 296-308. [More Information]
  • Yoo, P., Ho, Y., Ng, J., Charleston, M., Saksena, N., Yang, P., Zomaya, A. (2010). Hierarchical kernel mixture models for the prediction of AIDS disease progression using HIV structural gp120 profiles. BMC Genomics, 11 Suppl 4(S22), 1-10. [More Information]
  • Yang, P., Xu, L., Zhou, B., Zhang, Z., Zomaya, A. (2009). A particle swarm based hybrid system for imbalanced medical data sampling. BMC Genomics, 10(Suppl 3), S34-1-S34-14. [More Information]
  • Zhang, Z., Yang, P., Wu, X., Zhang, C. (2009). An Agent-Based Hybrid System for Microarray Data Analysis. IEEE Intelligent Systems, 24(5), 53-63.
  • Yang, P., Zhang, Z. (2009). An embedded two-layer feature selection approach for microarray data analysis. IEEE Intelligent Informatics Bulletin, 10(1), 24-32.

Conferences

  • Yang, P., Liu, W., Yang, J. (2017). Positive Unlabeled Learning via Wrapper-Based Adaptive Sampling. 26th International Joint Conference on Artificial Intelligence (IJCAI-17), Melbourne: International Joint Conferences on Artificial Intelligence.
  • Yang, P., Liu, W., Zhou, B., Chawla, S., Zomaya, A. (2013). Ensemble-Based Wrapper Methods for Feature Selection and Class Imbalance Learning. 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2013), Berlin: Springer. [More Information]
  • Yang, P., Zhang, Z., Zhou, B., Zomaya, A. (2011). Sample Subset Optimization for Classifying Imbalanced Biological Data. 15th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2011, Heidelberg, Germany: Springer. [More Information]
  • Li, L., Yang, P., Ou, L., Zhang, Z., Cheng, P. (2010). Genetic algorithm-based multi-objective optimisation for QoS-aware web services composition. 4th International Conference on Knowledge Science, Engineering and Management, KSEM 2010, Berlin: Springer. [More Information]
  • Yang, P., Tao, L., Xu, L., Zhang, Z. (2009). Multiagent framework for bio-data mining. 4th International Conference on Rough Sets and Knowledge Technology, RSKT 2009, Berlin: Springer Verlag. [More Information]

2017

  • Norris, D., Yang, P., Krycer, J., Fazakerley, D., James, D., Burchfield, J. (2017). An improved Akt reporter reveals intra- and inter-cellular heterogeneity and oscillations in signal transduction. Journal of Cell Science, 130, 2757-2766. [More Information]
  • Yang, P., Oldfield, A., Taiyun, K., Yang, A., Yang, J., Ho, J. (2017). Integrative analysis identifies co-dependent gene expression regulation of BRG1 and CHD7 at distal regulatory sites in embryonic stem cells. Bioinformatics, 33(3), 1916-1920. [More Information]
  • Yang, P., Oldfield, A., Kim, T., Yang, A., Yang, J., Ho, J. (2017). Integrative analysis identifies co-dependent gene expression regulation of BRG1 and CHD7 at distal regulatory sites in embryonic stem cells. Bioinformatics, 33(13), 1916-1920. [More Information]
  • Cinghu, S., Yang, P., Kosak, J., Conway, A., Kumar, D., Oldfield, A., Adelman, K., Jothi, R. (2017). Intragenic Enhancers Attenuate Host Gene Expression. Molecular Cell, 68(1), 104-117. [More Information]
  • Yang, P., Liu, W., Yang, J. (2017). Positive Unlabeled Learning via Wrapper-Based Adaptive Sampling. 26th International Joint Conference on Artificial Intelligence (IJCAI-17), Melbourne: International Joint Conferences on Artificial Intelligence.

2016

  • Zheng, X., Yang, P., Lackford, B., Bennett, B., Wang, L., Li, H., Wang, Y., Miao, Y., Foley, J., Fargo, D., et al (2016). CNOT3-Dependent mRNA Deadenylation Safeguards the Pluripotent State. Stem cell reports, 7(5), 897-910. [More Information]
  • Yang, P., Patrick, E., Humphrey, S., Ghazanfar, S., James, D., Jothi, R., Yang, J. (2016). KinasePA: Phosphoproteomics data annotation using hypothesis driven kinase perturbation analysis. Proteomics, 16(13), 1868-1871. [More Information]
  • Minard, A., Tan, S., Yang, P., Fazakerley, D., Domanova, W., Parker, B., Humphrey, S., Jothi, R., Stoeckli, J., James, D. (2016). mTORC1 Is a Major Regulatory Node in the FGF21 Signaling Network in Adipocytes. Cell Reports, 17(1), 29-36. [More Information]
  • Lu, C., Wang, J., Zhang, Z., Yang, P., Yu, G. (2016). NoisyGOA: Noisy GO annotations prediction using taxonomic and semantic similarity. Computational Biology and Chemistry, 65, 203-211. [More Information]
  • Yang, P., Humphrey, S., James, D., Yang, J., Jothi, R. (2016). Positive-unlabeled ensemble learning for kinase substrate prediction from dynamic phosphoproteomics data. Bioinformatics, 32(2), 252-259. [More Information]
  • Domanova, W., Krycer, J., Chaudhuri, R., Yang, P., Vafaee, F., Fazakerley, D., Humphrey, S., James, D., Kuncic, Z. (2016). Unraveling Kinase Activation Dynamics Using Kinase-Substrate Relationships from Temporal Large-Scale Phosphoproteomics Studies. PloS One, 11(6), 1-14. [More Information]

2015

  • Pathania, R., Ramachandran, S., Elangovan, S., Padia, R., Yang, P., Cinghu, S., Veeranan-Karmegam, R., Arjunan, P., Gnana-Prakasam, J., Sadanand, F., et al (2015). DNMT1 is essential for mammary and cancer stem cell maintenance and tumorigenesis. Nature Communications, 6, 1-11. [More Information]
  • Hoffman, N., Parker, B., Chaudhuri, R., Fisher-Wellman, K., Kleinert, M., Humphrey, S., Yang, P., Holliday, M., Trefely, S., Fazakerley, D., Stoeckli, J., Burchfield, J., James, D., et al (2015). Global Phosphoproteomic Analysis of Human Skeletal Muscle Reveals a Network of Exercise-Regulated Kinases and AMPK Substrates. Cell Metabolism, 22(5), 922-935. [More Information]
  • Yang, P., Zheng, X., Jayaswal, V., Hu, G., Yang, J., Jothi, R. (2015). Knowledge-Based Analysis for Detecting Key Signaling Events from Time-Series Phosphoproteomics Data. PLoS Computational Biology, 11(8), 1-18. [More Information]

2014

  • Yang, P., Patrick, E., Tan, S., Fazakerley, D., Burchfield, J., Gribben, C., Prior, M., James, D., Yang, J. (2014). Direction pathway analysis of large-scale proteomics data reveals novel features of the insulin action pathway. Bioinformatics, 30(6), 808-814. [More Information]
  • Lackford, B., Yao, C., Charles, G., Weng, L., Zheng, X., Choi, E., Xie, X., Wan, J., Xing, Y., Freudenberg, J., et al (2014). Fip1 regulates mRNA alternative polyadenylation to promote stem cell self-renewal. The EMBO Journal, 33(8), 878-889. [More Information]
  • Oldfield, A., Yang, P., Conway, A., Cinghu, S., Freudenberg, J., Yellaboina, S., Jothi, R. (2014). Histone-fold domain protein NF-Y promotes chromatin accessibility for cell type-specific master transcription factors. Molecular Cell, 55(5), 708-722. [More Information]
  • Ma, X., Yang, P., Kaplan, W., Lee, B., Wu, L., Yang, J., Yasunaga, M., Sato, K., Chisholm, D., James, D. (2014). ISL1 Regulates Peroxisome Proliferator-Activated Receptor gamma Activation and Early Adipogenesis via Bone Morphogenetic Protein 4-Dependent and -Independent Mechanisms. Molecular and Cellular Biology, 34(19), 3607-3617. [More Information]
  • Yang, P., Yoo, P., Fernando, J., Zhou, B., Zhang, Z., Zomaya, A. (2014). Sample Subset Optimization Techniques for Imbalanced and Ensemble Learning Problems in Bioinformatics Applications. IEEE Transactions on Cybernetics, 44(3), 445-455. [More Information]
  • Yang, P., Zhou, B., Yang, J., Zomaya, A. (2014). Stability of Feature Selection Algorithms and Ensemble Feature Selection Methods in Bioinformatics. In Mourad Elloumi, Albert Y. Zomaya (Eds.), Biological Knowledge Discovery Handbook: Preprocessing, Mining and Postprocessing of Biological Data, (pp. 333-352). New Jersey: John Wiley & Sons. [More Information]

2013

  • Humphrey, S., Yang, G., Yang, P., Fazakerley, D., Stockli, J., Yang, J., James, D. (2013). Dynamic adipocyte phosphoproteome reveals that akt directly regulates mTORC2. Cell Metabolism, 17(6), 1009-1020. [More Information]
  • Yang, P., Liu, W., Zhou, B., Chawla, S., Zomaya, A. (2013). Ensemble-Based Wrapper Methods for Feature Selection and Class Imbalance Learning. 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2013), Berlin: Springer. [More Information]

2012

  • Yang, P., Ma, J., Wang, P., Zhu, Y., Zhou, B., Yang, J. (2012). Improving X!Tandem on peptide identification from mass spectrometry by self-boosted percolator. IEEE - ACM Transactions on Computational Biology and Bioinformatics, 9(5), 1273-1280. [More Information]
  • Wang, P., Yang, P., Yang, J. (2012). OCAP: an open comprehensive analysis pipeline for iTRAQ. Bioinformatics, 28(10), 1404-1405. [More Information]
  • Yang, P., Humphrey, S., Fazakerley, D., Prior, M., Yang, G., James, D., Yang, J. (2012). Re-Fraction: A machine learning approach for deterministic identification of protein homologues and splice variants in large-scale MS-based proteomics. Journal of Proteome Research, 11(5), 3035-3045. [More Information]

2011

  • Yang, P., Ho, J., Yang, J., Zhou, B. (2011). Gene-gene interaction filtering with ensemble of filters. BMC Bioinformatics, 12(Supp 1: S10), 1-10. [More Information]
  • Yang, P., Zhang, Z., Zhou, B., Zomaya, A. (2011). Sample Subset Optimization for Classifying Imbalanced Biological Data. 15th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2011, Heidelberg, Germany: Springer. [More Information]

2010

  • Yang, P., Zhang, Z., Zhou, B., Zomaya, A. (2010). A clustering based hybrid system for biomarker selection and sample classification of mass spectrometry data. Neurocomputing, 73(13-15), 2317-2331. [More Information]
  • Wang, P., Yang, P., Arthur, J., Yang, J. (2010). A dynamic wavelet-based algorithm for pre-processing tandem mass spectrometry data. Bioinformatics, 26(18), 2242-2249. [More Information]
  • Yang, P., Ho, J., Zomaya, A., Zhou, B. (2010). A genetic ensemble approach for gene-gene interaction identification. BMC Bioinformatics, 11(524), 1-15. [More Information]
  • Yang, P., Zhou, B., Zhang, Z., Zomaya, A. (2010). A multi-filter enhanced genetic ensemble system for gene selection and sample classification of microarray data. BMC Bioinformatics, 11(Suppl 1), S5-1-S5-12. [More Information]
  • Yang, P., Yang, J., Zhou, B., Zomaya, A. (2010). A Review of Ensemble Methods in Bioinformatics. Current Bioinformatics, 5(4), 296-308. [More Information]
  • Li, L., Yang, P., Ou, L., Zhang, Z., Cheng, P. (2010). Genetic algorithm-based multi-objective optimisation for QoS-aware web services composition. 4th International Conference on Knowledge Science, Engineering and Management, KSEM 2010, Berlin: Springer. [More Information]
  • Yoo, P., Ho, Y., Ng, J., Charleston, M., Saksena, N., Yang, P., Zomaya, A. (2010). Hierarchical kernel mixture models for the prediction of AIDS disease progression using HIV structural gp120 profiles. BMC Genomics, 11 Suppl 4(S22), 1-10. [More Information]

2009

  • Yang, P., Xu, L., Zhou, B., Zhang, Z., Zomaya, A. (2009). A particle swarm based hybrid system for imbalanced medical data sampling. BMC Genomics, 10(Suppl 3), S34-1-S34-14. [More Information]
  • Zhang, Z., Yang, P., Wu, X., Zhang, C. (2009). An Agent-Based Hybrid System for Microarray Data Analysis. IEEE Intelligent Systems, 24(5), 53-63.
  • Yang, P., Zhang, Z. (2009). An embedded two-layer feature selection approach for microarray data analysis. IEEE Intelligent Informatics Bulletin, 10(1), 24-32.
  • Yang, P., Tao, L., Xu, L., Zhang, Z. (2009). Multiagent framework for bio-data mining. 4th International Conference on Rough Sets and Knowledge Technology, RSKT 2009, Berlin: Springer Verlag. [More Information]

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