Dr
Pengyi Yang
Computational analysis for biological discovery from (phospho)proteomic data
Mass spectrometry (MS) has become a well-established technology for global profiling of proteome and phosphoproteome in cells and tissues. Sophisticated computational methods are required for making sense of the data generated from MS-based proteomics and phosphoproteomics. In relation to professor Pei Wang’s talk/workshop, which covers the methods/tools for preprocessing of MS-based proteomic data, this talk/workshop will introduce computational methods/tools for identifying kinases, substrates, and signalling and gene pathways that are regulated in different experimental conditions, assays, and time-series from large-scale proteomic and phosphoproteomic data. Hands-on demonstrations will be given in the workshop in which various computational methods/tools will be introduced through example applications to several proteomic and phosphoproteomic datasets using R programming environment. To gain the most from this talk/workshop, you are encouraged to bring your own computer and follow the hands-on demonstrations step-by-step.
WORKSHOP: Computational analysis for biological discovery from (phospho)proteomic data
Mass spectrometry (MS) has become a well-established technology for global profiling of proteome and phosphoproteome in cells and tissues. Sophisticated computational methods are required for making sense of the data generated from MS-based proteomics and phosphoproteomics. In relation to professor Pei Wang’s talk/workshop, which covers the methods/tools for preprocessing of MS-based proteomic data, this talk/workshop will introduce computational methods/tools for identifying kinases, substrates, and signalling and gene pathways that are regulated in different experimental conditions, assays, and time-series from large-scale proteomic and phosphoproteomic data. Hands-on demonstrations will be given in the workshop in which various computational methods/tools will be introduced through example applications to several proteomic and phosphoproteomic datasets using R programming environment
Keywords: Proteomics, data mining
Requirements: You will need to bring your own laptop. Please make sure it has the latest version of R installed.
Relevance: This workshop will introduce advanced computational methods for anyone interested in understanding the phosphop roteome from MS data.
Dr Pengyi Yang
School of Mathematics and Statistics; Children’s Medical Research Institute; and Charles Perkins Centre, The University of Sydney
Pengyi Yang is senior lecturer at the School of Mathematics and Statistics, the University of Sydney, and an ARC DECRA Fellow and a NHMRC Investigator. He heads the Computational Systems Biology group at Children’s Medical Research Institute, and also heads the Computational Trans-Regulatory Biology group at Charles Perkins Centre. Pengyi has extensive experience in integrative analysis of proteomic, phosphoproteomic, transcriptomic, and epigenomic data. In particular, he has developed various specialised machine learning methods and statistical models for biologically guided analysis of multi-layered omic data.