David LynnAdjunct Group Leader
About the Group
What we do
David is an adjunct Professor in UCD School of Medicine, and is a longstanding SBI collaborator with expertise in bioinformatics, immunology and microbiome research. David has an international track record (having worked in Canada, Ireland and Australia) in applying computational and experimental systems biology approaches to investigate the immune system and more recently, cancer. Following a PhD in computational immunology at University College Dublin and a postdoctoral position in population immunogenomics at Trinity College Dublin, he moved to Vancouver (SFU & UBC) where he was the lead computational biologist on a Grand Challenges in Global Health Initiative project investigating how to modulate the innate immune response to several pathogens of major importance to global health. Since 2014, David is a European Molecular Biology Laboratory (EMBL) Australia Group Leader at the South Australian Health and Medical Research Institute (SAHMRI). EMBL Australia Group Leader positions are prestigious positions (only 15 awarded in Australia) which come with up to 9 years of funding for the group. In 2019, David was promoted to Director of the Computational and Systems Biology Program at SAHMRI, one of the 16 Programs/Divisions in the Institute. He also holds a full academic faculty position as Professor at the Flinders University School of Medicine.
David’s group is a multi-disciplinary group that is equally divided between computational and experimental systems biology. On the wet-lab side, his group employs in vitro and in vivo experimental and clinical models coupled with systems biology approaches to investigate the interplay between the microbiome and the immune system. For example, we have recently shown that early life antibiotic exposure in mice leads to significantly impaired vaccine antibody responses to commercial vaccines administered to millions of infants worldwide (Cell Host Microbe, 2018). This has led to a new, NHMRC-funded (2019-2021 as CIA), clinical trial in human infants and is informing new research on microbiota-targeted interventions to boost vaccine efficacy.
On the bioinformatics side, his group has developed a wide-range of bioinformatics software and online resources, which are all open source and open access. These include InnateDB.com, an internationally recognised systems biology platform for network and pathway analysis (40,000 users worldwide; >800 citations). We have also developed a range of software in the network biology space including applications for dynamic network analysis and visualisation (DyNet). We have also developed software for proteomics (HiQuant) and recently published one of the first bioinformatics tools for the analysis of spatial transcriptomics data (published in Cell Systems). His group has also led the computational biology aspects of a €12 million European funded project investigating how to model and subsequently therapeutically target protein interaction networks in colorectal cancer.
1. Kennedy S.*, Jarboui M.*, Srihari S.*, Raso C., Bryan K., Dernayka L., Charitou T., Bernal-Llinares M., Herrera-Montavez C., Krstic A., Matallanas D., Kotlyar M., Jurisica I., Curak J., Wong V., Stagljar I., LeBihan T., Imrie L., Pillai P., Lynn M.A., Fasterius E., Al-Khalili Szigyarto C., Kiel C., Serrano L., Rauch N., Rukhlenko O., Kholodenko B.N., Iglesias-Martinez L.F., Ryan C., Pilkington R., Cammareri P., Sansom O., Shave S., Auer M., Horn N., Klose F., Ueffing M., Boldt K.^, Lynn D.J.^, Kolch W.^ (2020). Extensive Rewiring of the EGFR Network in Colorectal Cancer Cells Expressing Transforming Levels of KRASG13D. Nature Communications 11(1):499. ^Joint Senior/Corresponding Author.
2. Charitou T., Srihari S., Lynn M.A., Jarboui M., Fasterius E., Moldovan M., Shirasawa S., Tsunoda T., Ueffing M., Xie J., J. Xin, Wang X., Proud C., Boldt K., Al-Khalili Szigyarto C., Kolch W., Lynn D.J. (2019). Transcriptional and metabolic rewiring of colorectal cancer cells expressing the oncogenic KRASG13D mutation. British Journal of Cancer 121(1): 37–50. Corresponding Author.
3. Salamon J., Goenawan I.H., Lynn D.J. (2018). Analysis and visualization of dynamic networks using the DyNet App for cytoscape. Current Protocols in Bioinformatics 63(5): e55. Corresponding Author.
4. Salamon J., Qian X., Nilsson M., Lynn D.J. (2018). Network visualization and analysis of spatially aware gene expression data with InsituNet. Cell Systems 6(5):626-630. Corresponding Author.
5. Dumousseau M., Alonso-López D., Ammari M., Bradley G., Campbell N.H., Ceol A., Cesareni G., Combe C., De Las Rivas .J, Del-Toro N., Heimbach J., Hermjakob H., Jurisica I., Koch M., Licata L., Lovering R.C., Lynn D.J., Meldal B., Micklem G., Panni, S., Porras P., Ricard-Blum S., Roechert B., Salwinski L., Shrivastava A., Sullivan J., Thierry-Mieg N., Yehudi Y., Van Roey K., Orchard S. (2018). Encompassing new use cases - level 3.0 of the HUPO-PSI format for molecular interactions. BMC Bioinformatics 19(1):134.
6. Muetze T., Lynn D.J. (2017). Identification of Contextually Relevant Hubs using the Contextual Hub Analysis Tool (CHAT) in Cytoscape. Current Protocols in Bioinformatics 59 8.24.1 – 8.24.13 doi: 10.1002/cpbi.35. Corresponding Author.
7. Muetze T., Goenawan I.H., Wiencko H.L., Bernal-Llinares M., Bryan K., Lynn D.J. (2016) Contextual Hub Analysis Tool (CHAT): A Cytoscape app for identifying contextually relevant hubs in biological networks. F1000 Research 5: 1745. Corresponding Author.
8. Goenawan I., Bryan K., Lynn D.J. (2016). DyNet: visualization and analysis of dynamic molecular interaction networks. Bioinformatics 32(17):2713-5. Corresponding Author.
9. Bryan K., Jarboui M., Bernal-Llinares M., Raso C., McCann B., Rauch J., Boldt, K. Lynn D.J. (2016) HiQuant: Rapid post-quantification analysis of large-scale MS-generated proteomics data. Journal of Proteome Research. 15(6):2072-9. Corresponding Author.