Dr Pengyi Yang

ARC DECRA and USyd Robinson Fellow
Computational Systems Biology Group Leader
Children's Medical Research Institute
Senior Lecturer
School of Mathematics &
Statistics

Member of the Charles Perkins Centre

F07 - Carslaw Building
The University of Sydney


Website Lab website

Biographical details

Pengyi Yang, Ph.D., heads the Computational Trans-Regulatory Biology group at Charles Perkins Centre (CPC), the University of Sydney, and holds a conjoint appointment as Group Leader of Computational Systems Biology group at Children's Medical Research Institute (CMRI), at the Westmead Research Hub.

Research interests

Molecular trans-regulatory networks (TRNs) comprised of cell signalling, transcriptional, translational, and (epi)genomic regulations are central to health and disease. Computational approaches are instrumental in characterising TRNs of cells at the systems level. Our research lies at the interface of bioinformatics and systems biology. We develop computational and statistical models to reconstruct cell signalling, epigenomic/transcriptional, and proteomic networks, and characterise their cross-talk and trans-regulations in various cellular processes and systems. By integrating heterogeneous trans-omic data with the goal of generating testable hypotheses and predictions, we aim to tackle the following research questions:

  • How do different layers of regulations talk to each other in controlling stem cell fate?
  • Can we accurately predict stem cell differentiation trajectories based on their TRNs?
  • The mechanisms of stem/progenitor cells in establishing identities and making cell fate decisions

Teaching and supervision

Timetable

P_Yang

Current research students

Project title Research student
Single - Cell Transcriptomes for Network Analysis in Complex Disease Yue CAO
Understanding Transcriptional Networks in Naive to Primed Pluripotent Stem Cells Hani KIM
Development of statistical methods for integrative omics analysis in precision medicine Taiyun KIM

Current projects

1. Single-cell transcriptomics and its application to cell fate decisions.

2. Deep learning and its application to systems biology.

3. Reconstruct trans-regulatory networks using multi-omics profiling and data integration.

Please contact me if you are interested in any of the above projects. Projects can be tailored to fit students research plan and interest.

International links

United States

(Cornell University) Collaborating with Associate Professor Dave Lin, Department of Biomedical Sciences, on single-cell multi-omics.

United States

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

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

2019

  • Single Cell Plus; Yang J, Ho J, Patrick E, Yang P, Lo K, Wong J, Liu P, Tsia K, So H, Shum A; Office of Global Engagement/Partnership Collaboration Awards.

2017

  • 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).
  • Identification of New Mechanisms in Insulin Resistance; Larance M, Yang P, Chaudhuri R; National Health and Medical Research Council (NHMRC)/Project Grants.

2015

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

Selected publications

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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

  • Yang, P., Ormerod, J., Liu, W., Ma, C., Zomaya, A., Yang, J. (2019). AdaSampling for Positive-Unlabeled and Label Noise Learning With Bioinformatics Applications. IEEE Transactions on Cybernetics, 49(5), 1932-1943. [More Information]
  • Parker, B., Calkin, A., Seldin, M., Keating, M., Tarling, E., Yang, P., Moody, S., Liu, Y., Zerenturk, E., Needham, E., James, D., et al (2019). An integrative systems genetic analysis of mammalian lipid metabolism. Nature, 567(7747), 187-193. [More Information]
  • De Ridder, M., Klein, K., Yang, J., Yang, P., Lagopoulos, J., Hickie, I., Bennett, M., Kim, J. (2019). An Uncertainty Visual Analytics Framework for fMRI Functional Connectivity. Neuroinformatics, 17(2), 211-223. [More Information]
  • Kim, T., Chen, I., Lin, Y., Wang, A., Yang, J., Yang, P. (2019). Impact of similarity metrics on single-cell RNA-seq data clustering. Briefings in bioinformatics, Epub ahead of print, 1-11. [More Information]
  • O'Sullivan, J., Neylon, A., Fahey, E., Yang, P., McGorrian, C., Blake, G. (2019). MiR-93-5p is a novel predictor of coronary in-stent restenosis. Heart Asia, 11(1), e011134 - 1-e011134 - 4. [More Information]
  • Yang, P., Humphrey, S., Cinghu, S., Pathania, R., Oldfield, A., Kumar, D., Perera, D., Yang, J., James, D., Mann, M., et al (2019). Multi-omic profiling reveals dynamics of the phased progression of pluripotency. Cell Systems, 8(5), 427-445. [More Information]
  • Oldfield, A., Henriques, T., Kumar, D., Burkholder, A., Cinghu, S., Paulet, D., Bennett, B., Yang, P., Scruggs, B., Lavender, C., et al (2019). NF-Y controls fidelity of transcription initiation at gene promoters through maintenance of the nucleosome-depleted. Nature Communications, 10(1), Art 3072 - 1-Art 3072 - 12. [More Information]
  • Kim, T., Chen, I., Parker, B., Humphrey, S., Crossett, B., Cordwell, S., Yang, P., Yang, J. (2019). QCMAP: An Interactive Web-Tool for Performance Diagnosis and Prediction of LC-MS Systems. Proteomics, 19(13), 1900068 - 1-1900068 - 4. [More Information]
  • Lin, Y., Ghazanfar, S., Wang, K., Gagnon-Bartsch, J., Lo, K., Su, X., Han, Z., Ormerod, J., Speed, T., Yang, P., Yang, J. (2019). scMerge leverages factor analysis, stable expression, and pseudoreplication to merge multiple single-cell RNA-seq datasets. Proceedings of the National Academy of Sciences of the United States of America, 116(20), 9775-9784. [More Information]
  • Fazakerley, D., Chaudhuri, R., Yang, P., Maghazal, G., Cooke, K., Krycer, J., Humphrey, S., Parker, B., Fisher-Wellman, K., Meoli, C., Hoffman, N., Diskin, C., Burchfield, J., Yang, J., James, D., et al (2018). Mitochondrial CoQ deficiency is a common driver of mitochondrial oxidants and insulin resistance. eLife, 7(Article number e32111), 1-38. [More Information]
  • 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., 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]
  • 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. 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. [More Information]
  • 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 2017), Melbourne: International Joint Conferences on Artificial Intelligence. [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]
  • 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]

2019

  • Yang, P., Ormerod, J., Liu, W., Ma, C., Zomaya, A., Yang, J. (2019). AdaSampling for Positive-Unlabeled and Label Noise Learning With Bioinformatics Applications. IEEE Transactions on Cybernetics, 49(5), 1932-1943. [More Information]
  • Parker, B., Calkin, A., Seldin, M., Keating, M., Tarling, E., Yang, P., Moody, S., Liu, Y., Zerenturk, E., Needham, E., James, D., et al (2019). An integrative systems genetic analysis of mammalian lipid metabolism. Nature, 567(7747), 187-193. [More Information]
  • De Ridder, M., Klein, K., Yang, J., Yang, P., Lagopoulos, J., Hickie, I., Bennett, M., Kim, J. (2019). An Uncertainty Visual Analytics Framework for fMRI Functional Connectivity. Neuroinformatics, 17(2), 211-223. [More Information]
  • Kim, T., Chen, I., Lin, Y., Wang, A., Yang, J., Yang, P. (2019). Impact of similarity metrics on single-cell RNA-seq data clustering. Briefings in bioinformatics, Epub ahead of print, 1-11. [More Information]
  • O'Sullivan, J., Neylon, A., Fahey, E., Yang, P., McGorrian, C., Blake, G. (2019). MiR-93-5p is a novel predictor of coronary in-stent restenosis. Heart Asia, 11(1), e011134 - 1-e011134 - 4. [More Information]
  • Yang, P., Humphrey, S., Cinghu, S., Pathania, R., Oldfield, A., Kumar, D., Perera, D., Yang, J., James, D., Mann, M., et al (2019). Multi-omic profiling reveals dynamics of the phased progression of pluripotency. Cell Systems, 8(5), 427-445. [More Information]
  • Oldfield, A., Henriques, T., Kumar, D., Burkholder, A., Cinghu, S., Paulet, D., Bennett, B., Yang, P., Scruggs, B., Lavender, C., et al (2019). NF-Y controls fidelity of transcription initiation at gene promoters through maintenance of the nucleosome-depleted. Nature Communications, 10(1), Art 3072 - 1-Art 3072 - 12. [More Information]
  • Kim, T., Chen, I., Parker, B., Humphrey, S., Crossett, B., Cordwell, S., Yang, P., Yang, J. (2019). QCMAP: An Interactive Web-Tool for Performance Diagnosis and Prediction of LC-MS Systems. Proteomics, 19(13), 1900068 - 1-1900068 - 4. [More Information]
  • Lin, Y., Ghazanfar, S., Wang, K., Gagnon-Bartsch, J., Lo, K., Su, X., Han, Z., Ormerod, J., Speed, T., Yang, P., Yang, J. (2019). scMerge leverages factor analysis, stable expression, and pseudoreplication to merge multiple single-cell RNA-seq datasets. Proceedings of the National Academy of Sciences of the United States of America, 116(20), 9775-9784. [More Information]

2018

  • Fazakerley, D., Chaudhuri, R., Yang, P., Maghazal, G., Cooke, K., Krycer, J., Humphrey, S., Parker, B., Fisher-Wellman, K., Meoli, C., Hoffman, N., Diskin, C., Burchfield, J., Yang, J., James, D., et al (2018). Mitochondrial CoQ deficiency is a common driver of mitochondrial oxidants and insulin resistance. eLife, 7(Article number e32111), 1-38. [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., 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]
  • 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 2017), Melbourne: International Joint Conferences on Artificial Intelligence. [More Information]

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. 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. [More Information]
  • 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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