Research Publications

Research

Currently, I am working on leveraging large language models for phenotyping of rare disease patients.

During my PhD, I tackled a variety of phenomic and genomic problems. On the genomics side, I worked on:

Identifying epistatic mechanisms driving complex diseases
Multiomic data integration to study Alzheimer's disease using gene and pathway burden scores
Genome-wide association study and polygenic risk score development of neuroimaging phenotypes to identify genetic predictors of schizophrenia, autism, and major depressive disorder

On the phenomic and ML side, I worked on:

Implementing unsupervised clustering to subphenotype heart failure patient population using EHR and cardiac echo data
Elucidating comorbidity architecture of complex diseases using network medicine
Developing method DETECT to identify probabilistic disease trajectories and early indicators of severe cardiac clinical events

During my bachelors at Northeastern University, I researched the genetic mechanisms underlying limb regeneration in the axolotl model. Additionally, I did 2 co-op stints (2015, 2016) at Editas Medicine developing CRISPR based therapeutics for HSV1.

Research interest keywords: precision medicine, prognostics, EHR statistical genetics, machine learning, network science, time series, predictive modeling, patient-facing tool development

Publications

[14] Singhal P, Kumar R, Kumar N, Becker M, Hanish A, Xapakhdy K, Verma A. Leveraging GPT models to intuitively structure free-text clinical notes. (2023). Accepted to AMIA Informatics Summit 2024.

[13] Lee DSM, Cardone K, Zhang D, …, Singhal P, …, Damrauer SM. Common- and rare-variant genetic architecture of heart failure across the allele frequency spectrum. (2023). Nature Medicine. 10.1101/2023.07.16.23292724

[12] Singhal P, Tan A, Drivas T, Ritchie MD, Beaulieu-Jones B. Opportunities and Challenges for Biomarker Discovery Using Electronic Health Record Data. (2023) 18 July 2023. Trends in Molecular Medicine. https://doi.org/10.1016/j.molmed.2023.06.006

[11] Singhal P, Verma SS, Ritchie MD. (2023) Gene Interactions in Human Disease Studies – Evidence is Mounting. 17 May 2023. Annual Review of Biomedical Data Science. https://www.annualreviews.org/doi/10.1146/annurev-biodatasci-102022-120818

[10] Singhal P, Guare L, Morse C, et al. (2023) DETECT: Feature extraction method for disease trajectory modeling. 16 June 2023. American Medical Informatics Association Joint Summits on Translational Science. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10283148/

[9] Singhal P, Veturi S, Dudek SM, et al. (2023) Evidence of epistasis in regions of long-range linkage disequilibrium across five complex diseases in the UK Biobank and eMERGE datasets. 6 Apr 2023. American Journal for Human Genetics. https://doi.org/10.1016/j.ajhg.2023.03.007

[8] Singhal P, Veturi Y, Judy R, Park Y, Vujkovic M, Veatch O, Kember R, Verma SS. (2023) session Introduction: SALUD: Scalable Applications of cLinical risk Utility and preDiction. Pacific Sym on Biocomputing. https://doi.org/10.1142/9789811270611_0037

[7] Nam Y, Jung S, Yun J, Sriram V, Singhal P, et al. (2023) Discovering comorbid diseases using an inter-disease interactivity network based on biobank-scale PheWAS data. Bioinformatics. https://doi.org/10.1093/bioinformatics/btac822

[6] Hwang G, Wen J, Sotardi S, Brodkin ES, Chand GB, Dwyer DB, Erus G, Doshi J, Singhal P, et al. (2023) Assessment of Neuroanatomical Endophenotypes of Autism Spectrum Disorder and Association With Characteristics of Individuals With Schizophrenia and the General Population. JAMA Psychiatry. doi:10.1001/jamapsychiatry.2023.0409

[5] Levin MG, Tsao NL, Singhal P, et al. (2022) Genome-wide association and multi-train analyses characterize the common genetic architecture of heart failure. Nature Communications. https://doi.org/10.1038/s41467-022-34216-6

[4] Chand G, Singhal P, Dwyer D, et al. (2022) Schizophrenia imaging signatures and their associations with cognition, psychopathology, and genetics in the general population. American Journal of Psychiatry. https://doi.org/10.1176/appi.ajp.21070686

[3] Reza N, Bone WP, Yang Y, Singhal P, et al. (2022) A supervised learning method for classification of electronic health-record based phenotypes. Preprint. https://doi.org/10.1101/2022.10.31.22281772

[2] Nguyen M, Singhal P, Monaghan JR, et al. (2017) Retinoic acid receptor regulation of epimorphic and homeostatic regeneration in the axolotl. Development. 144: 601-611. https://doi.org/10.1242/dev.139873

[1] Friedland AE, Baral R, Singhal P, et al. (2015) Characterization of Staphylococcus aureus Cas9: a smaller Cas9 for all-in-one adeno-associated virus delivery and paired nickase applications. Genome Biology 16: 257. https://doi.org/10.1186/s13059-015-0817-8

Pankhuri Singhal

Uni. of Pennsylvania Institute for Biomedical Informatics Dept. of Medicine

Research

Publications

Pankhuri Singhal

Uni. of Pennsylvania Institute for Biomedical Informatics Dept. of Medicine

Research

Publications

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