PhD, Cold Spring Harbor Laboratory
At a Glance
- Precision oncology; developing general-purpose computational algorithms and software to integrate multi-modal patient data for disease subtyping and to predict clinical outcome
- Developing biologically-interpretable predictive models using prior knowledge of tissue- and cell-specific gene regulation
- Genomics and epigenomics of neurodevelopmental disorders, including pediatric brain cancers
- Interdisciplinary collaborations for computational method development, genomic research, pre-clinical and clinical applications in cancer and other diseases
- Keywords: Precision oncology; Machine learning; Gene regulation; Genomics; Epigenomics; Systems biology; Networks; Neurodevelopmental disorders
Dr. Pai’s lab aims to improve data-driven clinical decision-making, through a better understanding of how the genome impacts phenotype at various levels of system organization. Dr. Pai received her B.Math. in Hon. Computer Science (Bioinformatics) from the University of Waterloo. She received her PhD in Biological Sciences from Cold Spring Harbor Laboratory in NY, USA, using experimental and analytic approaches to identify the brain-basis of short-term memory in the rat model. Dr. Pai’s first postdoctoral fellowship was in epigenetics of human brain and mental illness at the Centre for Addiction and Mental Health in Toronto. Her second postdoctoral fellowship was at the Donnelly Centre for Cellular and Biomolecular Research in Toronto, developing machine learning methods for precision medicine. Dr. Pai is a recipient of the 2014 NARSAD Young Investigator Award, 2014 CIHR Fellowship Award, and the 2019 Donnelly Centre Research Excellence Award for Postdoctoral Fellows and Research Associates, and is a member of the Temerty Centre for AI Research and Education in Medicine (TCAIREM).
Cancer is a group of related-but-different diseases with various underlying molecular networks that complicate treatment. Dr. Shraddha Pai’s research goal is to improve data-driven clinical decision-making by finding genomic and multi-omic signatures that match cancer patients to the most effective treatments with the fewest side effects. Her team uses population-scale data with multiple layers of information (e.g. transcriptomic, DNA methylation, proteomic, brain imaging, clinical), and develops algorithms and software that incorporate prior knowledge of genotype-phenotype impact and systems-level organization for predictive modeling.
As a postdoctoral fellow, Dr. Pai led the development of netDx, a general-purpose patient classifier algorithm that integrates heterogenous patient data into a single model to predict clinical outcome. It adapts a recommender system model similar to that used by Netflix (“find movies like this one”) to precision medicine (“find patients like non-responders”), and uses prior knowledge of cellular pathways to organize genomic data as well as machine learning. The lab is currently building on this work to create predictive modelling workflows for application to pre-clinical patient data.
Dr. Pai’s work and expertise in genomics and precision medicine apply to cancer as well as other diseases with genomic contribution. The lab collaborates broadly with clinical, genomic and computational scientists for method development and translational research.
Genomics and epigenomics of neurodevelopmental disorders
Dr. Pai’s lab also studies the role of developmental epigenetics in altering the risk of childhood- and adult-onset disease. This includes the study of neurodevelopmental disorders such as schizophrenia and cancers of neurodevelopmental origin, such as pediatric brain malignancies. Dr. Pai co-led the first epigenome-wide association study in neurons isolated from post-mortem brain samples in major psychosis. This study led to the identification of a novel biomarker that unifies two distinctive features of psychosis: dopaminergic increase and reduced synaptic structure. The study of genomics of pediatric brain malignancies is a new and fast-evolving research area in the lab, so Contact Dr. Pai for further details.
For more information please see the Pai Lab website.
- Pai S, Li P, Killinger B, Marshall L, Jia P, Liao J, Petronis A, Szabó PE, Labrie V (2019). Differential methylation of enhancer at IGF2 is associated with abnormal dopamine synthesis in major psychosis. Nature Comms. 10:2046.
- Pai S, Hui S, Isserlin R, Shah MA, Kaka H, Bader GD. (2019). netDx: interpretable patient classification using integrated patient similarity networks. Mol Sys Biol 15:e8497
- Pai S and Bader GD. (2018). Patient Similarity Networks for Precision Medicine. Invited review. J Mol Biol. 430 (18 Pt A); 2924.
- Khare T, Pai S, Koncevicius K, Pal M, Kriukiene E, Liutkeviciute Z, Irimia M, Jia P, Ptak C, Xia M, Tice R, Tochigi M, Moréra S, Nazarians A, Belsham D, Wong AH, Blencowe BJ, Wang SC, Kapranov P, Kustra R, Labrie V, Klimasauskas S, Petronis A. (2012). 5-hmC in the brain is abundant in synaptic genes and shows differences at the exon-intron boundary. Nat Struct Mol Biol. 19 (10): 1037-43. Co-lead author.
- Labrie V, Pai S, Petronis A. (2012) Epigenetics of major psychosis: progress, problems and perspectives. TiGs, invited review. 28 (9): 427-35. Co-lead author.
Honours and Awards
2019 Donnelly Centre Research Excellence award
2014 NARSAD Young Investigator award
2014 CIHR Postdoctoral Fellowship
2004-2008 Dana Foundation Fellow, WSBS
2004 NSERC Canada Graduate Scholarship