People_

Associate Professor Pengyi Yang

University of Sydney Robinson Fellow
Head, Computational Systems Biology
Children's Medical Research Institute
Charles Perkins Centre
Associate Professor, School of Mathematics &
Statistics

Email

pengyi.yang@sydney.edu.au

Address

F07 - Carslaw Building

The University of Sydney

Details

Member of the Charles Perkins Centre

Websites

Lab website

Biographical details

Pengyi Yang, Ph.D.,is an Associate Professor and a Robinson Fellow at the School of Mathematics and Statistics.He heads the Computational Trans-Regulatory Biology group at Charles Perkins Centre (CPC), the University of Sydney, and holds a conjoint appointment as Unit Head of Computational Systems Biologyat Children's Medical Research Institute (CMRI), at the Westmead Research Hub.

Research interests

Cells are the fundamental building blocks of all life on earth. In multicellular organisms, these cellular building blocks come in a plethora of types and serve distinct functions to coordinate and support the homeostasis of an organism. Intriguingly, all cell types of an organism share the same genetic code and originate from the same group of pluripotentstem cellsthat have undergone different cellular fates during development.

Research from the last few decades has established that cell identity and cell-fate decisions are determined by underlying.trans-regulatory networks (TRNs)comprised of cell signalling, transcriptional, and epigenetic regulations, and the intra- and extra-cellular networks they form. Understanding how TRNs regulate cell identity and interact through cell-cell communications in a spatial-temporal manner is critical for gaining insight into the complex nature of multicellular development. To this end, our research takes a holistic approach and seeks to reconstruct the TRNs, that cut across multiple molecular programs, for modelling cell identity and controlling cell-fate decisions.

Leveraging on recent advances in single-cell omics technologies and our experitise in machine learning, deep learning, and statistical modelling, we develop computational models to reconstruct TRNs in stem cells and model their differentiation to specialised cell types. By employing a multidisiciplinary approach that combines 'dry' (computation) and 'wet' (laboratory) studies at the systems level, we contribute to the following research aims:

Develop computational methods to reconstruct TRNs for modelling cell identity.
Develop computational methods to guide TRN modulation for controlling cell fate-decisions.
Generate knowledge on how do different layers of TRNs coordinately regulate cell identity and cell fate-decisions.
Develop computational framework to assess fidelity of cell conversion for applications such as tissue engineering and stem cell therapy.

Teaching and supervision

Timetable

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.

Associations

Editorial Board, Stem Cell Reports, Cell Press
International Society for Stem Cell Research (ISSCR)
National Stem Cell Foundation of Australia (NSCFA)
The Australian Bioinformatics and Computational Biology Society (ABACBS)
Australasian Society for Stem Cell Research (ASSCR)
Australian Academy of Science
Australian Museum

Awards and honours

2024 The University of Sydney – National University of Singapore Ignition Grant
2023 – 2024 Tianqiao and Chrissy Chen Institute (TCCI) support of development and mentorship of the Early Career Editorial Board of Stem Cell Reports, USA
2023 Sydney Research Accelerator (SOAR) prize, The University of Sydney, Australia
2021 Outstanding Mid-career Researcher Award, Australian Bioinformatics and Computational Biology Society
2021 Metcalf Prize, National Stem Cell Foundation, Australia
2020 – 2024 Investigator (Emerging Leadership Level 2), National Health and Medical Research Council
2019 Charles Perkins Centre Exceptional Contribution Award, Australia
2018 Robinson Fellowship (2025 – 2028, DVC Research), The University of Sydney, Australia
2017 J G Russell Award, Australian Academy of Science, Australia (presented to 4 top-ranked DECRAs nationwide in 2017)
2017 Finalist of Eureka Prize for Outstanding Early Career Researcher, Australian Museum
2017 – 2019 Discovery Early Career Researcher Award (DECRA), Australian Research Council (ARC)
2017 Paper of the Year Award, National Institute of Environmental Health Sciences, National Institutes of Health, USA
2015 – 2017 University of Sydney Fellowship (DVC Research), The University of Sydney, Australia
2015 Fellows Award for Research Excellence (2015), National Institutes of Health, USA
2014 Paper of the Year Award, National Institute of Environmental Health Sciences, National Institutes of Health, USA
2014 Fellows Award for Research Excellence (2014), National Institutes of Health, USA
2012 – 2016 Research Fellowship, National Institutes of Health, USA
2009 – 2012 National ICT Australia (NICTA) Research Project Award (NRPA), Australia
2009 – 2012 National ICT Australia (NICTA) International Postgraduate Award (NIPA), 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

International links

France	(Institute of Human Genetics (IHG), the French National Centre for Scientific Research (CNRS)) Collaborating with Dr. Andrew Oldfield, Team Leader, Biology of distal regulatory elements group.
Singapore	(Duke-NUS Medical School) Collaborating with Dr. Alfred Sun, Assistant Professor, on understanding how human brains use stem cell-derived brain organoids.
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 and 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 and Stem Cell Biology Laboratory.

PhD and master's project opportunities

Computational characterisation of trans-regulatory cell systems

Machine learning in cell identity, fate decision, and lineage prediction

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

Current research students

Project title	Research student
Interpretable deep learning-based approaches for precision medicine	Manoj M WAGLE
Developing Robust clustering methods for scRNA-seq data.	Elijah WILLIE

Publications

By Type

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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

Shen, S., Werner, T., Lukowski, S., Andersen, S., Sun, Y., Shim, W., Mizikovsky, D., Kobayashi, S., Outhwaite, J., Yang, P., et al (2025). Atlas of multilineage stem cell differentiation reveals TMEM88 as a developmental regulator of blood pressure. Nature Communications, 16(1), 1356-1-1356-19. [More Information]
Chen, C., Kim, H., Yang, P. (2024). Evaluating spatially variable gene detection methods for spatial transcriptomics data. Genome Biology, 25 Open Access(1), Article 18 -1-Article 18 - 21. [More Information]
Wagle, M., Long, S., Chen, C., Liu, C., Yang, P. (2024). Interpretable deep learning in single-cell omics. Bioinformatics, 40(5), 8 pages. [More Information]
Wu, Z., Zhao, Q., Kim, D., Yang, P., Hill, T., Jones, A., Fairlie, D., Pébay, A., Hewitt, A., Tam, P., et al (2024). Wnt dose escalation during the exit from pluripotency identifies tranilast as a regulator of cardiac mesoderm. Developmental Cell, 59(6), 705-722.e8. [More Information]
Cao, Y., Ghazanfar, S., Yang, P., Yang, J. (2023). Benchmarking of analytical combinations for COVID-19 outcome prediction using single-cell RNA sequencing data. Briefings in Bioinformatics, 24(3). [More Information]
Kim, H., O'Hara-Wright, M., Kim, D., Loi, T., Lim, B., Jamieson, R., Gonzalez Cordero, A., Yang, P. (2023). Comprehensive characterization of fetal and mature retinal cell identity to assess the fidelity of retinal organoids. Stem Cell Reports, 18(1), 175-189. [More Information]
Xiao, D., Chen, C., Yang, P. (2023). Computational systems approach towards phosphoproteomics and their downstream regulation. Proteomics, 23(3 - 4), Article no. 2200068. [More Information]
Yu, L., Liu, C., Yang, J., Yang, P. (2023). Ensemble deep learning of embeddings for clustering multimodal single-cell omics data. Bioinformatics, 39(6).
Huang, H., Liu, C., Wagle, M., Yang, P. (2023). Evaluation of deep learning-based feature selection for single-cell RNA sequencing data analysis. Genome Biology, 24(1), Article 259 - 1-Article 259 - 20. [More Information]
Kim, D., Tran, A., Kim, H., Lin, Y., Yang, J., Yang, P. (2023). Gene regulatory network reconstruction: harnessing the power of single-cell multi-omic data. Npj Systems Biology And Applications, 9.
Kim, D., Tran, A., Kim, H., Lin, Y., Yang, J., Yang, P. (2023). Gene regulatory network reconstruction: harnessing the power of single-cell multi-omic data. Npj Systems Biology And Applications, 9(51). [More Information]
Liu, C., Huang, H., Yang, P. (2023). Multi-task learning from multimodal single-cell omics with Matilda. Nucleic Acids Research, 51(8), e45 - 1-e45 - 14. [More Information]
Kim, T., Kim, H., Oldfield, A., Yang, P. (2023). PAD2: interactive exploration of transcription factor genomic colocalization using ChIP-seq data. STAR Protocols, 4(2), 102203-1-102203-9. [More Information]
Fazakerley, D., Van Gerwen, J., Cooke, K., Duan, X., Needham, E., Diaz-Vegas, A., Madsen, S., Norris, D., Shun-Shion, A., Krycer, J., Burchfield, J., Yang, P., James, D., Humphrey, S., et al (2023). Phosphoproteomics reveals rewiring of the insulin signaling network and multi-nodal defects in insulin resistance. Nature Communications, 14(1), 1-20. [More Information]
Fazakerley, D., Van Gerwen, J., Cooke, K., Duan, X., Needham, E., Díaz-Vegas, A., Madsen, S., Norris, D., Shun-Shion, A., Krycer, J., Burchfield, J., Yang, P., James, D., Humphrey, S., et al (2023). Phosphoproteomics reveals rewiring of the insulin signaling network and multi-nodal defects in insulin resistance. Nature Communications, 14(1), 923.
Xiao, D., Lin, M., Liu, C., Geddes, T., Burchfield, J., Parker, B., Humphrey, S., Yang, P. (2023). SnapKin: a snapshot deep learning ensemble for kinase-substrate prediction from phosphoproteomics data. NAR Genomics and Bioinformatics, 5(4), Article number Iqad099-1-Article number Iqad099-12. [More Information]
Patrick, E., Canete, N., Iyengar, S., Harman, A., Sutherland, G., Yang, P. (2023). Spatial analysis for highly multiplexed imaging data to identify tissue microenvironments. Cytometry Part A, 103, 593-599. [More Information]
Willie, E., Yang, P., Patrick, E. (2023). The impact of similarity metrics on cell-type clustering in highly multiplexed in situ imaging cytometry data. Bioinformatics Advances, 3 (Open Access)(1), Article vbad141-1-Article vbad141-12. [More Information]
Cao, Y., Tran, A., Kim, H., Robertson, N., Lin, Y., Torkel, M., Yang, P., Patrick, E., Ghazanfar, S., Yang, J. (2023). Thinking process templates for constructing data stories with SCDNEY. F1000Research, 12, 261-1-261-18. [More Information]
Ting, K., Loo, L., Neely, G., Yang, P., Götz, J., Vadas, M., Gamble, J., Coleman, P., Kim, H., Zhao, Y., Johnstone, D., et al (2023). Vascular senescence and leak are features of the early breakdown of the blood–brain barrier in Alzheimer’s disease models. GeroScience, 45(6), 3307-3331. [More Information]
Yu, L., Cao, Y., Yang, J., Yang, P. (2022). Benchmarking clustering algorithms on estimating the number of cell types from single-cell RNA-sequencing data. Genome Biology, 23(1). [More Information]
Tran, A., Yang, P., Yang, J., Ormerod, J. (2022). Computational approaches for direct cell reprogramming: from the bulk omics era to the single cell era. Briefings in Functional Genomics, 21(4), 270-279. [More Information]
Fernando, M., Lee, S., Wark, J., Xiao, D., Lim, B., O'Hara-Wright, M., Kim, H., Smith, G., Wong, T., Teber, E., Yang, P., Graham, M., Gonzalez Cordero, A., et al (2022). Differentiation of brain and retinal organoids from confluent cultures of pluripotent stem cells connected by nerve-like axonal projections of optic origin. Stem Cell Reports, 17(6), 1476-1492. [More Information]
Xiao, D., Kim, H., Pang, I., Yang, P. (2022). Functional analysis of the stable phosphoproteome reveals cancer vulnerabilities. Bioinformatics, 38(7), 1956-1963. [More Information]
Kim, H., Li, P., Kim, T., Oldfield, A., Zheng, X., Yang, P. (2022). Integrative analysis reveals histone demethylase LSD1 promotes RNA polymerase II pausing. iScience, 25 (Open access)(10), 105049-1-105049-20. [More Information]
Yang, P., Tam, P. (2022). Mouse organogenesis atlas at single-cell resolution. Cell, 185(10), 1625-1627. [More Information]
Blazev, R., Carl, C., Ng, Y., Molendijk, J., Voldstedlund, C., Zhao, Y., Xiao, D., Kueh, A., Miotto, P., Haynes, V., Lisowski, L., Yang, P., et al (2022). Phosphoproteomics of three exercise modalities identifies canonical signaling and C18ORF25 as an AMPK substrate regulating skeletal muscle function. Cell Metabolism, 34(10), 1561-1577. [More Information]
Cao, Y., Lin, Y., Patrick, E., Yang, P., Yang, J. (2022). scFeatures: multi-view representations of single-cell and spatial data for disease outcome prediction. Bioinformatics, 38(20), 4745-4753. [More Information]
Tran, A., Yang, P., Yang, J., Ormerod, J. (2022). scREMOTE: Using multimodal single cell data to predict regulatory gene relationships and to build a computational cell reprogramming model. NAR Genomics and Bioinformatics, 4(1), 1-11. [More Information]
Tu, J., Li, W., Yang, S., Yang, P., Yan, Q., Wang, S., Lai, K., Bai, X., Wu, C., Ding, W., et al (2022). Single-Cell Transcriptome Profiling Reveals Multicellular Ecosystem of Nucleus Pulposus during Degeneration Progression. Advanced Science, 9(3), 2103631. [More Information]
Xiao, D., Caldow, M., Kim, H., Blazev, R., Koopman, R., Manandi, D., Parker, B., Yang, P. (2022). Time-resolved phosphoproteome and proteome analysis reveals kinase signaling on master transcription factors during myogenesis. iScience, 25(6). [More Information]
Duan, X., Norris, D., Humphrey, S., Yang, P., Cooke, K., Bultitude, W., Parker, B., Conway, O., Burchfield, J., Krycer, J., James, D., Fazakerley, D., et al (2022). Trafficking regulator of GLUT4-1 (TRARG1) is a GSK3 substrate. Biochemical Journal, 479(11), 1237-1256. [More Information]
Cao, Y., Yang, P., Yang, J. (2021). A benchmark study of simulation methods for single-cell RNA sequencing data. Nature Communications, 12(1), 6911. [More Information]
Kim, T., Tang, O., Vernon, S., Kott, K., Koay, Y., Park, J., James, D., Grieve, S., Speed, T., Yang, P., Figtree, G., John, O., Yang, J. (2021). A hierarchical approach to removal of unwanted variation for large-scale metabolomics data. Nature Communications, 12(1), 4992-1-4992-10. [More Information]
Kearney, A., Norris, D., Ghomlaghi, M., Wong, M., Humphrey, S., Carroll, L., Yang, G., Cooke, K., Yang, P., Geddes, T., James, D., Burchfield, J., et al (2021). Akt phosphorylates insulin receptor substrate to limit PI3K-mediated PIP3 synthesis. eLife, 10, 1-32. [More Information]
Su, X., Zhao, L., Shi, Y., Zhang, R., Long, Q., Bai, S., Luo, Q., Lin, Y., Zou, X., Ghazanfar, S., Yang, P., Yang, J., et al (2021). Clonal evolution in liver cancer at single-cell and single-variant resolution. Journal of Hematology and Oncology, 14(1), 22-26. [More Information]
Kumar, D., Cinghu, S., Oldfield, A., Yang, P., Jothi, R. (2021). Decoding the function of bivalent chromatin in development and cancer. Genome Research, 31(12), 2170-2184. [More Information]
Kim, H., Tam, P., Yang, P. (2021). Defining cell identity beyond the premise of differential gene expression. Cell Regeneration, 10(1), 20-3 pages. [More Information]
Singh, R., Cottle, L., Loudovaris, T., Yang, P., Thomas, H., Kebede, M., Thorn, P. (2021). Enhanced structure and function of human pluripotent stem cell-derived beta-cells cultured on extracellular matrix. Stem Cells Translational Medicine, 10(3), 492-505. [More Information]
Yang, P., Hao, H., Liu, C. (2021). Feature selection revisited in the single-cell era. Genome Biology, 22(1), 321. [More Information]
Recasens, A., Humphrey, S., Ellis, M., Hoque, M., Abbassi, R., Chen, B., Longworth, M., Needham, E., James, D., Johns, T., Kassiou, M., Yang, P., Munoz, L., et al (2021). Global phosphoproteomics reveals DYRK1A regulates CDK1 activity in glioblastoma cells. Cell Death Discovery, 7(1), 81. [More Information]
Blazev, R., Ashwood, C., Abrahams, J., Chung, L., Francis, D., Yang, P., Watt, K., Qian, H., Quaife-Ryan, G., Hudson, J., et al (2021). Integrated glycoproteomics identifies a role of N-glycosylation and galectin-1 on myogenesis and muscle development. Molecular and Cellular Proteomics, 20, 100030. [More Information]
Kim, H., Kim, T., Hoffman, N., Xiao, D., James, D., Humphrey, S., Yang, P. (2021). PhosR enables processing and functional analysis of phosphoproteomic data. Cell Reports, 34(8), 108771-1-108771-23. [More Information]
Kim, H., Kim, T., Xiao, D., Yang, P. (2021). Protocol for the processing and downstreamanalysis of phosphoproteomic data with PhosR. STAR Protocols, 2(2), 100585. [More Information]
Norris, D., Yang, P., Shin, S., Kearney, A., Kim, H., Geddes, T., Senior, A., Fazakerley, D., Nguyen, L., James, D., Burchfield, J. (2021). Signaling Heterogeneity is Defined by Pathway Architecture and Intercellular Variability in Protein Expression. iScience, 24(2), 102118. [More Information]
Kim, H., Wang, K., Chen, C., Lin, Y., Tam, P., Lin, D., Yang, J., Yang, P. (2021). Uncovering cell identity through differential stability with Cepo. Nature Computational Science, 1(12), 784-790. [More Information]
Kim, H., Lin, Y., Geddes, T., Yang, J., Yang, P. (2020). CiteFuse enables multi-modal analysis of CITE-seq data. Bioinformatics, 36(14), 4137-4143. [More Information]
Azimi, A., Yang, P., Ali, M., Howard, V., Mann, G., Alexander, K., Fernandez Penas, P. (2020). Data Independent Acquisition Proteomic Analysis Can Discriminate between Actinic Keratosis, Bowen's Disease, and Cutaneous Squamous Cell Carcinoma. Journal of Investigative Dermatology, 140(1), 212-222. [More Information]
Cao, Y., Geddes, T., Yang, J., Yang, P. (2020). Ensemble deep learning in bioinformatics. Nature Machine Intelligence, 2(September 2020), 500-508. [More Information]
Lin, Y., Cao, Y., Kim, H., Salim, A., Speed, T., Lin, D., Yang, P., Yang, J. (2020). scClassify: sample size estimation and multiscale classification of cells using single and multiple reference. Molecular Systems Biology, 16(Open access), e9389-1-e9389-16. [More Information]
Kaur, S., Peters, T., Yang, P., Luu, L., Vuong, J., Krycer, J., O'Donoghue, S. (2020). Temporal ordering of omics and multiomic events inferred from time-series data. Npj Systems Biology And Applications, 6(1), 1-7. [More Information]
Kim, H., Osteil, P., Humphrey, S., Cinghu, S., Oldfield, A., Patrick, E., Wilkie, E., Peng, G., Suo, S., Jothi, R., Tam, P., Yang, P. (2020). Transcriptional network dynamics during the progression of pluripotency revealed by integrative statistical learning. Nucleic Acids Research, 48(4), 1828-1842. [More Information]
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]
Geddes, T., Kim, T., Nan, L., Burchfield, J., Yang, J., Tao, D., Yang, P. (2019). Autoencoder-based cluster ensembles for single-cell RNA-seq data analysis. BMC Bioinformatics, 20(Suppl 19), 1-11. [More Information]
Lin, Y., Ghazanfar, S., Strbenac, D., Wang, A., Patrick, E., Lin, D., Speed, T., Yang, J., Yang, P. (2019). Evaluating stably expressed genes in single cells. GigaScience, 8(9), 1-10. [More Information]
Su, Z., Burchfield, J., Yang, P., Humphrey, S., Yang, G., Francis, D., Yasmin, S., Shin, S., Norris, D., Kearney, A., Astore, M., Scavuzzo, J., Wang, Q., Parker, B., Neely, G., Vafaee, F., Chiu, J., Yeo, R., Hogg, P., Fazakerley, D., Kuyucak, S., James, D., et al (2019). Global redox proteome and phosphoproteome analysis reveals redox switch in Akt. Nature Communications, 10(1), 1-18. [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, 20(6), 2316-2326. [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), 1-4. [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. [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 region. Nature Communications, 10(1), 3072. [More Information]
Kim, T., Chen, R., 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), 1-4. [More Information]
Cao, Y., Lin, Y., Ormerod, J., Yang, P., Yang, J., Lo, K. (2019). scDC: single cell differential composition analysis. BMC Bioinformatics, 20(Suppl 19), 1-21. [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]
Kim, T., Lo, K., Geddes, T., Kim, H., Yang, J., Yang, P. (2019). scReClassify: post hoc cell type classification of single-cell rNA-seq data. BMC Genomics, 20(Suppl 9), 1-10. [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]
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.

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Conferences

Tang, T., Wu, H., Bao, W., Yang, P., Yuan, D., Zhou, B. (2019). New parallel algorithms for all pairwise computation on large HPC clusters. 20th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT 2019), : IEEE Computer Society. [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]
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]

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By Year

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2025

Shen, S., Werner, T., Lukowski, S., Andersen, S., Sun, Y., Shim, W., Mizikovsky, D., Kobayashi, S., Outhwaite, J., Yang, P., et al (2025). Atlas of multilineage stem cell differentiation reveals TMEM88 as a developmental regulator of blood pressure. Nature Communications, 16(1), 1356-1-1356-19. [More Information]

2024

Chen, C., Kim, H., Yang, P. (2024). Evaluating spatially variable gene detection methods for spatial transcriptomics data. Genome Biology, 25 Open Access(1), Article 18 -1-Article 18 - 21. [More Information]
Wagle, M., Long, S., Chen, C., Liu, C., Yang, P. (2024). Interpretable deep learning in single-cell omics. Bioinformatics, 40(5), 8 pages. [More Information]
Wu, Z., Zhao, Q., Kim, D., Yang, P., Hill, T., Jones, A., Fairlie, D., Pébay, A., Hewitt, A., Tam, P., et al (2024). Wnt dose escalation during the exit from pluripotency identifies tranilast as a regulator of cardiac mesoderm. Developmental Cell, 59(6), 705-722.e8. [More Information]

2023

Cao, Y., Ghazanfar, S., Yang, P., Yang, J. (2023). Benchmarking of analytical combinations for COVID-19 outcome prediction using single-cell RNA sequencing data. Briefings in Bioinformatics, 24(3). [More Information]
Kim, H., O'Hara-Wright, M., Kim, D., Loi, T., Lim, B., Jamieson, R., Gonzalez Cordero, A., Yang, P. (2023). Comprehensive characterization of fetal and mature retinal cell identity to assess the fidelity of retinal organoids. Stem Cell Reports, 18(1), 175-189. [More Information]
Xiao, D., Chen, C., Yang, P. (2023). Computational systems approach towards phosphoproteomics and their downstream regulation. Proteomics, 23(3 - 4), Article no. 2200068. [More Information]
Yu, L., Liu, C., Yang, J., Yang, P. (2023). Ensemble deep learning of embeddings for clustering multimodal single-cell omics data. Bioinformatics, 39(6).
Huang, H., Liu, C., Wagle, M., Yang, P. (2023). Evaluation of deep learning-based feature selection for single-cell RNA sequencing data analysis. Genome Biology, 24(1), Article 259 - 1-Article 259 - 20. [More Information]
Kim, D., Tran, A., Kim, H., Lin, Y., Yang, J., Yang, P. (2023). Gene regulatory network reconstruction: harnessing the power of single-cell multi-omic data. Npj Systems Biology And Applications, 9.
Kim, D., Tran, A., Kim, H., Lin, Y., Yang, J., Yang, P. (2023). Gene regulatory network reconstruction: harnessing the power of single-cell multi-omic data. Npj Systems Biology And Applications, 9(51). [More Information]
Liu, C., Huang, H., Yang, P. (2023). Multi-task learning from multimodal single-cell omics with Matilda. Nucleic Acids Research, 51(8), e45 - 1-e45 - 14. [More Information]
Kim, T., Kim, H., Oldfield, A., Yang, P. (2023). PAD2: interactive exploration of transcription factor genomic colocalization using ChIP-seq data. STAR Protocols, 4(2), 102203-1-102203-9. [More Information]
Fazakerley, D., Van Gerwen, J., Cooke, K., Duan, X., Needham, E., Diaz-Vegas, A., Madsen, S., Norris, D., Shun-Shion, A., Krycer, J., Burchfield, J., Yang, P., James, D., Humphrey, S., et al (2023). Phosphoproteomics reveals rewiring of the insulin signaling network and multi-nodal defects in insulin resistance. Nature Communications, 14(1), 1-20. [More Information]
Fazakerley, D., Van Gerwen, J., Cooke, K., Duan, X., Needham, E., Díaz-Vegas, A., Madsen, S., Norris, D., Shun-Shion, A., Krycer, J., Burchfield, J., Yang, P., James, D., Humphrey, S., et al (2023). Phosphoproteomics reveals rewiring of the insulin signaling network and multi-nodal defects in insulin resistance. Nature Communications, 14(1), 923.
Xiao, D., Lin, M., Liu, C., Geddes, T., Burchfield, J., Parker, B., Humphrey, S., Yang, P. (2023). SnapKin: a snapshot deep learning ensemble for kinase-substrate prediction from phosphoproteomics data. NAR Genomics and Bioinformatics, 5(4), Article number Iqad099-1-Article number Iqad099-12. [More Information]
Patrick, E., Canete, N., Iyengar, S., Harman, A., Sutherland, G., Yang, P. (2023). Spatial analysis for highly multiplexed imaging data to identify tissue microenvironments. Cytometry Part A, 103, 593-599. [More Information]
Willie, E., Yang, P., Patrick, E. (2023). The impact of similarity metrics on cell-type clustering in highly multiplexed in situ imaging cytometry data. Bioinformatics Advances, 3 (Open Access)(1), Article vbad141-1-Article vbad141-12. [More Information]
Cao, Y., Tran, A., Kim, H., Robertson, N., Lin, Y., Torkel, M., Yang, P., Patrick, E., Ghazanfar, S., Yang, J. (2023). Thinking process templates for constructing data stories with SCDNEY. F1000Research, 12, 261-1-261-18. [More Information]
Ting, K., Loo, L., Neely, G., Yang, P., Götz, J., Vadas, M., Gamble, J., Coleman, P., Kim, H., Zhao, Y., Johnstone, D., et al (2023). Vascular senescence and leak are features of the early breakdown of the blood–brain barrier in Alzheimer’s disease models. GeroScience, 45(6), 3307-3331. [More Information]

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2022

Yu, L., Cao, Y., Yang, J., Yang, P. (2022). Benchmarking clustering algorithms on estimating the number of cell types from single-cell RNA-sequencing data. Genome Biology, 23(1). [More Information]
Tran, A., Yang, P., Yang, J., Ormerod, J. (2022). Computational approaches for direct cell reprogramming: from the bulk omics era to the single cell era. Briefings in Functional Genomics, 21(4), 270-279. [More Information]
Fernando, M., Lee, S., Wark, J., Xiao, D., Lim, B., O'Hara-Wright, M., Kim, H., Smith, G., Wong, T., Teber, E., Yang, P., Graham, M., Gonzalez Cordero, A., et al (2022). Differentiation of brain and retinal organoids from confluent cultures of pluripotent stem cells connected by nerve-like axonal projections of optic origin. Stem Cell Reports, 17(6), 1476-1492. [More Information]
Xiao, D., Kim, H., Pang, I., Yang, P. (2022). Functional analysis of the stable phosphoproteome reveals cancer vulnerabilities. Bioinformatics, 38(7), 1956-1963. [More Information]
Kim, H., Li, P., Kim, T., Oldfield, A., Zheng, X., Yang, P. (2022). Integrative analysis reveals histone demethylase LSD1 promotes RNA polymerase II pausing. iScience, 25 (Open access)(10), 105049-1-105049-20. [More Information]
Yang, P., Tam, P. (2022). Mouse organogenesis atlas at single-cell resolution. Cell, 185(10), 1625-1627. [More Information]
Blazev, R., Carl, C., Ng, Y., Molendijk, J., Voldstedlund, C., Zhao, Y., Xiao, D., Kueh, A., Miotto, P., Haynes, V., Lisowski, L., Yang, P., et al (2022). Phosphoproteomics of three exercise modalities identifies canonical signaling and C18ORF25 as an AMPK substrate regulating skeletal muscle function. Cell Metabolism, 34(10), 1561-1577. [More Information]
Cao, Y., Lin, Y., Patrick, E., Yang, P., Yang, J. (2022). scFeatures: multi-view representations of single-cell and spatial data for disease outcome prediction. Bioinformatics, 38(20), 4745-4753. [More Information]
Tran, A., Yang, P., Yang, J., Ormerod, J. (2022). scREMOTE: Using multimodal single cell data to predict regulatory gene relationships and to build a computational cell reprogramming model. NAR Genomics and Bioinformatics, 4(1), 1-11. [More Information]
Tu, J., Li, W., Yang, S., Yang, P., Yan, Q., Wang, S., Lai, K., Bai, X., Wu, C., Ding, W., et al (2022). Single-Cell Transcriptome Profiling Reveals Multicellular Ecosystem of Nucleus Pulposus during Degeneration Progression. Advanced Science, 9(3), 2103631. [More Information]
Xiao, D., Caldow, M., Kim, H., Blazev, R., Koopman, R., Manandi, D., Parker, B., Yang, P. (2022). Time-resolved phosphoproteome and proteome analysis reveals kinase signaling on master transcription factors during myogenesis. iScience, 25(6). [More Information]
Duan, X., Norris, D., Humphrey, S., Yang, P., Cooke, K., Bultitude, W., Parker, B., Conway, O., Burchfield, J., Krycer, J., James, D., Fazakerley, D., et al (2022). Trafficking regulator of GLUT4-1 (TRARG1) is a GSK3 substrate. Biochemical Journal, 479(11), 1237-1256. [More Information]

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2021

Cao, Y., Yang, P., Yang, J. (2021). A benchmark study of simulation methods for single-cell RNA sequencing data. Nature Communications, 12(1), 6911. [More Information]
Kim, T., Tang, O., Vernon, S., Kott, K., Koay, Y., Park, J., James, D., Grieve, S., Speed, T., Yang, P., Figtree, G., John, O., Yang, J. (2021). A hierarchical approach to removal of unwanted variation for large-scale metabolomics data. Nature Communications, 12(1), 4992-1-4992-10. [More Information]
Kearney, A., Norris, D., Ghomlaghi, M., Wong, M., Humphrey, S., Carroll, L., Yang, G., Cooke, K., Yang, P., Geddes, T., James, D., Burchfield, J., et al (2021). Akt phosphorylates insulin receptor substrate to limit PI3K-mediated PIP3 synthesis. eLife, 10, 1-32. [More Information]
Su, X., Zhao, L., Shi, Y., Zhang, R., Long, Q., Bai, S., Luo, Q., Lin, Y., Zou, X., Ghazanfar, S., Yang, P., Yang, J., et al (2021). Clonal evolution in liver cancer at single-cell and single-variant resolution. Journal of Hematology and Oncology, 14(1), 22-26. [More Information]
Kumar, D., Cinghu, S., Oldfield, A., Yang, P., Jothi, R. (2021). Decoding the function of bivalent chromatin in development and cancer. Genome Research, 31(12), 2170-2184. [More Information]
Kim, H., Tam, P., Yang, P. (2021). Defining cell identity beyond the premise of differential gene expression. Cell Regeneration, 10(1), 20-3 pages. [More Information]
Singh, R., Cottle, L., Loudovaris, T., Yang, P., Thomas, H., Kebede, M., Thorn, P. (2021). Enhanced structure and function of human pluripotent stem cell-derived beta-cells cultured on extracellular matrix. Stem Cells Translational Medicine, 10(3), 492-505. [More Information]
Yang, P., Hao, H., Liu, C. (2021). Feature selection revisited in the single-cell era. Genome Biology, 22(1), 321. [More Information]
Recasens, A., Humphrey, S., Ellis, M., Hoque, M., Abbassi, R., Chen, B., Longworth, M., Needham, E., James, D., Johns, T., Kassiou, M., Yang, P., Munoz, L., et al (2021). Global phosphoproteomics reveals DYRK1A regulates CDK1 activity in glioblastoma cells. Cell Death Discovery, 7(1), 81. [More Information]
Blazev, R., Ashwood, C., Abrahams, J., Chung, L., Francis, D., Yang, P., Watt, K., Qian, H., Quaife-Ryan, G., Hudson, J., et al (2021). Integrated glycoproteomics identifies a role of N-glycosylation and galectin-1 on myogenesis and muscle development. Molecular and Cellular Proteomics, 20, 100030. [More Information]
Kim, H., Kim, T., Hoffman, N., Xiao, D., James, D., Humphrey, S., Yang, P. (2021). PhosR enables processing and functional analysis of phosphoproteomic data. Cell Reports, 34(8), 108771-1-108771-23. [More Information]
Kim, H., Kim, T., Xiao, D., Yang, P. (2021). Protocol for the processing and downstreamanalysis of phosphoproteomic data with PhosR. STAR Protocols, 2(2), 100585. [More Information]
Norris, D., Yang, P., Shin, S., Kearney, A., Kim, H., Geddes, T., Senior, A., Fazakerley, D., Nguyen, L., James, D., Burchfield, J. (2021). Signaling Heterogeneity is Defined by Pathway Architecture and Intercellular Variability in Protein Expression. iScience, 24(2), 102118. [More Information]
Kim, H., Wang, K., Chen, C., Lin, Y., Tam, P., Lin, D., Yang, J., Yang, P. (2021). Uncovering cell identity through differential stability with Cepo. Nature Computational Science, 1(12), 784-790. [More Information]

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2020

Kim, H., Lin, Y., Geddes, T., Yang, J., Yang, P. (2020). CiteFuse enables multi-modal analysis of CITE-seq data. Bioinformatics, 36(14), 4137-4143. [More Information]
Azimi, A., Yang, P., Ali, M., Howard, V., Mann, G., Alexander, K., Fernandez Penas, P. (2020). Data Independent Acquisition Proteomic Analysis Can Discriminate between Actinic Keratosis, Bowen's Disease, and Cutaneous Squamous Cell Carcinoma. Journal of Investigative Dermatology, 140(1), 212-222. [More Information]
Cao, Y., Geddes, T., Yang, J., Yang, P. (2020). Ensemble deep learning in bioinformatics. Nature Machine Intelligence, 2(September 2020), 500-508. [More Information]
Lin, Y., Cao, Y., Kim, H., Salim, A., Speed, T., Lin, D., Yang, P., Yang, J. (2020). scClassify: sample size estimation and multiscale classification of cells using single and multiple reference. Molecular Systems Biology, 16(Open access), e9389-1-e9389-16. [More Information]
Kaur, S., Peters, T., Yang, P., Luu, L., Vuong, J., Krycer, J., O'Donoghue, S. (2020). Temporal ordering of omics and multiomic events inferred from time-series data. Npj Systems Biology And Applications, 6(1), 1-7. [More Information]
Kim, H., Osteil, P., Humphrey, S., Cinghu, S., Oldfield, A., Patrick, E., Wilkie, E., Peng, G., Suo, S., Jothi, R., Tam, P., Yang, P. (2020). Transcriptional network dynamics during the progression of pluripotency revealed by integrative statistical learning. Nucleic Acids Research, 48(4), 1828-1842. [More Information]

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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]
Geddes, T., Kim, T., Nan, L., Burchfield, J., Yang, J., Tao, D., Yang, P. (2019). Autoencoder-based cluster ensembles for single-cell RNA-seq data analysis. BMC Bioinformatics, 20(Suppl 19), 1-11. [More Information]
Lin, Y., Ghazanfar, S., Strbenac, D., Wang, A., Patrick, E., Lin, D., Speed, T., Yang, J., Yang, P. (2019). Evaluating stably expressed genes in single cells. GigaScience, 8(9), 1-10. [More Information]
Su, Z., Burchfield, J., Yang, P., Humphrey, S., Yang, G., Francis, D., Yasmin, S., Shin, S., Norris, D., Kearney, A., Astore, M., Scavuzzo, J., Wang, Q., Parker, B., Neely, G., Vafaee, F., Chiu, J., Yeo, R., Hogg, P., Fazakerley, D., Kuyucak, S., James, D., et al (2019). Global redox proteome and phosphoproteome analysis reveals redox switch in Akt. Nature Communications, 10(1), 1-18. [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, 20(6), 2316-2326. [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), 1-4. [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. [More Information]
Tang, T., Wu, H., Bao, W., Yang, P., Yuan, D., Zhou, B. (2019). New parallel algorithms for all pairwise computation on large HPC clusters. 20th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT 2019), : IEEE Computer Society. [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 region. Nature Communications, 10(1), 3072. [More Information]
Kim, T., Chen, R., 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), 1-4. [More Information]
Cao, Y., Lin, Y., Ormerod, J., Yang, P., Yang, J., Lo, K. (2019). scDC: single cell differential composition analysis. BMC Bioinformatics, 20(Suppl 19), 1-21. [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]
Kim, T., Lo, K., Geddes, T., Kim, H., Yang, J., Yang, P. (2019). scReClassify: post hoc cell type classification of single-cell rNA-seq data. BMC Genomics, 20(Suppl 9), 1-10. [More Information]

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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]
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]

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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]

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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]

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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]

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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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Selected Grants

2024

Integrative statistical learning in trans-regulatory networks of stem and progenitor cells and disease, Yang P, DVC Research/Robinson Fellowship
Towards generating dopaminergic neuron containing stem cell-derived brain organoids, Sun X, Yang P, Long S, Zyner K, Chen C, Office of Global Engagement/Ignition Grants
Assembling the building blocks in the blueprint of the embryonic head, Tam P, Yang P, Australian Research Council (ARC)/Discovery Projects (DP)

2023

Evaluating human blastoids for modelling early human development, Yang P, DVC Research/Bridging Support Grant
Purification and cryopreservation of an allogeneic stem cell-derived photoreceptor cell product, Gonzalez Cordero A, Kim H, Tam P, Elwood N, Yang P, Department of Health and Aged Care (Federal)/MRFF - Stem Cell Therapies

2022

2023 SOAR - Pengyi Yang, Yang P, DVC Research/SOAR Prizes
DEVELOPMENT OF PHOTORECEPTOR CELL THERAPY TO TREAT BLINDNESS, Elwood N, Gonzalez Cordero A, Wakefield C, Yang P, Hetherington K, Jamieson R, Reddel R, Simunovic M, Tam P, Grigg J, Zreiqat H, Department of Health and Aged Care (Federal - administered by NHMRC)/2021 MRFF Stem Cell Therapies Mission

2020

Discovery of big-data-informed multi-modal risk prediction signatures - Institute of Data Discovery for Health (D24H), Yang J, Patrick E, Yang P, Tarr G, Innovation & Technology Commission, Hong Kong SAR Govt/AIR@InnoHK
Cloud-accelerated analytics for clinical omic and imaging data - Institute of Data Discovery for Health (D24H), Yang J, Simpson S, Patrick E, Yang P, Tarr G, Kim J, Innovation & Technology Commission, Hong Kong SAR Govt/AIR@InnoHK

2019

Towards machine learning-based precision stem cell therapy, Yang P, National Health and Medical Research Council (NHMRC)/Investigator Grant

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)
Trans-omic networks: a machine learning and omics integration approach, Yang P, Australian Research Council (ARC)/Discovery Early Career Researcher Award (DECRA)

2016

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

Member of International Society for Stem Cell Research (ISSCR) Momentum Award selection committee (2024)
Member of Australian Bioinformatics and Computational Biology Society (ABACBS) committee (2024-present)
Early Career Editor of Stem Cell Reports (2023-present)
Member of Organising Committee of Sydney Bioinformatics Research Symposium (2022, 2023), Sydney, Australia
Member of Program Committee of GIW/ISMB-Asia conference (2022), Tainan, Taiwan
Theme chair, Oz Single Cell conference (2022), Gold Coast, Australia
Member of Program Committee of ABACBS conference (2021), Melbourne, Australia
Co-chair of Program Committee of ABACBS conference (2019), Sydney, Australia
Member of Postgraduate Research Excellence Award (PREA) review panel, Faculty of Science,The University of Sydney (2019)
Session chair of Australasian Genomic Technologies Association (AGTA) conference (2017), Hobart, Australia
Member of Program Committee of Pattern Recognition in Bioinformatics (PRIB) conference (2014), Stockholm, Sweden

Faculty of Science

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Associate Professor Pengyi Yang

Timetable

Publications

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Selected Grants

2024

2023

2022

2020

2019

2017

2016

2015

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