Laboratory of Computational Systems Biology
Deciphering trans-omic networks in controlling cell identity and cell-fate decisions
Welcome to the Computational Systems Biology lab at Children's Medical Research Institute (CMRI), the Westmead Research Hub (view). Our research group also affiliates with the School of Mathematics and Statistics and is part of the Charles Perkins Centre (CPC) at the University of Sydney (view).
Our research aims to understand the molecular trans-omic networks, comprised of cell signalling, transcriptional, translational, and (epi)genomic regulations, in controlling cell identity and cell-fate decisions. Towards this aim, our lab develop computational and statistical models to reconstruct each layer of the trans-omic networks (e.g. signalling networks, transcriptional networks) and characterise their cross-talk in various cellular systems. By employing a multidisiciplinary approach combining 'dry' (computation) and 'wet' (laboratory) works at the systems level, we aim to address the following research questions:
- How do different layers of trans-omic networks coordinately regulate cell identity and cell fate-decisions?
- How can we accurately predict cell identity and cell fate-decisions based on their trans-omic networks?
- How can we modulate trans-omic networks to direct cell fate-decisions for applications such as stem-cell therapy?
Our lab is multi-disciplinary and combines ('dry') computational methods, statistical models, and ('wet') molecular biology approaches for understanding cell identity and cell-fate decisions and for harnessing stem and progenitor cells for stem-cell based therapies. We are located at Children's Medical Research Institute (CMRI) at the Westmead Research Hub. We also holds 'dry' space in both Charles Perkins Centre (CPC) and School of Mathematics and Statistics (Carslaw Building), the University of Sydney. Researchers and students at all levels are welcome to inquire the possibility to join us and work on either 'dry' (computational) or 'wet' (laboratory) projects or some combinations of the two.
Post-doctoral positions funded by NHMRC grant are available for conducting research on the broad area of computational systems biology in stem cells and their therapeutic application. Interested candidates are encouraged to please contact Pengyi Yang, lab head, to discuss potential projects and other details (pengyi.yang [at] sydney.edu.au)
PhD scholarships are available for both domestic and international candidates. Please see link for more details on Children's Medical Research Institute PhD Research Award. For details on scholarships offered at the University of Sydney, please see link.
Honours projects are available through either Children's Medical Research Institute, Faculty of Health and Medicine, see link; or the School of Mathematics and Statistics, Faculty of Science. For more details regarding projects, please contact Pengyi Yang.
Summer research scholarships are available for third year undergraduates at both Children's Medical Research Institute and Charles Perkins Centre. For more details regarding potential projects and scholarships, please contact Pengyi Yang.
Our lab is experienced in developing machine learning algorithms and statistical models for analysing the following types of data:
- Mass spectrometry (MS)-based:
- Redox proteomics
- Next-generation sequencing (NGS)-based:
- Bulk RNA-seq and microarray
- Single-cell RNA-seq
- ChIP-seq and RIP-seq of DNA/RNA binding proteins
- RNA Polymerase II, Histones and DNaseI
- Hi-C and ChIA-PET
Excited to have @katie_zyner joining us as a Senior Research Officer and @hani_jieun staying with us as a Research Officer at the Computational Systems Biology group at @CMRI_AUS. Looking forward to exploring together stem cell identity and fate decisions in the coming years!— Pengyi Yang (@PengyiYang82) January 18, 2022
In a recent study, Pengyi Yang (@PengyiYang82) and colleagues propose a method to uncover cell identity genes and enhance the retrieval of cellular identities from scRNA-seq data (https://t.co/3g4giWaw84). https://t.co/aX47hbFB40— Nature Computational Science (@NatComputSci) December 20, 2021
Poster prizes #OzSingleCell— OzSingleCell Omics (@ozsinglecells) July 30, 2021
First: Hani Jieun Kim