Justin P. Whalley, PhD

Dr. Justin P. Whalley is an Assistant Professor of Bioinformatics at the Chicago Medical School, Rosalind Franklin University of Medicine and Science. He earned his M.Sci. in Mathematics from the University of Bristol and his Ph.D. in Bioinformatics from the University of Évry, France.

He began his research career at the National Center for Genomic Analysis (CNAG) in Barcelona, Spain, where he led the Quality Control working group for the Pan-Cancer Analysis of Whole Genomes (PCAWG) project. In this role, he coordinated genome data integration across 25 tumor types and multiple international centers, working with teams at the Broad Institute, the Wellcome Sanger Institute, and the German Cancer Research Center.

Dr. Whalley later returned to the UK as a Senior Bioinformatician at the University of Oxford, where he contributed to the COVID-19 Multi-Omics Blood Atlas (COMBAT) consortium. As co-lead of the Integration (Tensor) working group, he developed unsupervised decomposition methods to unify transcriptomic, proteomic, and immune cell data, linking molecular dysregulation to disease severity and patient outcomes.

Since joining Rosalind Franklin University in 2023, his research has expanded to include integrative analysis of neurodegenerative and inflammatory disease datasets, with a focus on mapping multi-layered data, including single-cell, spatial, and 3D genome structure, to clinical phenotypes. He is also beginning to explore how quantum computing-inspired optimization techniques could further enhance the scalability of these integrative models.

Dr. Whalley was recently selected as an inaugural member of the NSF NCEMS working groups, with in-kind support to advance AI-driven epigenomic analysis across complex human diseases.

Research

We can produce large, detailed datasets detailing genes’ expression, protein abundance, epigenetic profiles and cell populations. I work on the computational and mathematical challenge of reducing these multidimensional datasets to a set of quintessential features. Using tensor decomposition, we can integrate this multilevel data and uncover the importance of interaction between these different layers in understanding biological systems. The work is in support of a long term research goal to understand clinical symptoms or biological phenomena at the molecular level.

Key techniques in my work include tensor and matrix decomposition, deep learning for 3D genome architecture, and other dimension reduction methods for linking multi-modal data across patients. I am increasingly interested in incorporating optimization methods inspired by quantum computing to tackle the computational challenges of these large and heterogeneous datasets.

Much of this work is carried out in collaboration with faculty at Rosalind Franklin University and international partners, drawing on diverse expertise in molecular biology, immunology, and computer science.

Publications

• Calôba C, Sturtz AJ, Lyons TA, John L, Ramachandran A, Minns AM, Cannon AM, et al. Systemic 4-1BB stimulation augments extrafollicular memory B cell formation and recall responses during Plasmodium infection. (2025). Cell Reports. doi:10.1016/j.celrep.2025.115528 PMID:40215168
• Kanellakis NI, Antoun E, Cano-Gamez K, Chu J, Manoharan N, Berridge G, Vendrell I, et al. Pleural fluid proteomics from patients with pleural infection shows signatures of diverse neutrophilic responses: The Oxford Pleural Infection Endotyping Study (TORPIDS-2). (2025). The European Respiratory Journal. doi:10.1183/13993003.00010-2025 PMID:40246538
• Mi Y, Burnham KL, Charles PD, Heilig R, Vendrell I, Whalley J, Torrance HD, et al. High-throughput mass spectrometry maps the sepsis plasma proteome and differences in patient response. (2024). Science Translational Medicine. doi:10.1126/scitranslmed.adh0185 PMID:38838133
• Torrance HD, Zhang P, Longbottom ER, Mi Y, Whalley JP, Allcock A, Kwok AJ, et al. A Transcriptomic Approach to Understand Patient Susceptibility to Pneumonia After Abdominal Surgery. (2024). Annals of Surgery. doi:10.1097/SLA.0000000000006050 PMID:37497667
• Weeratunga P, Denney L, Bull JA, Repapi E, Sergeant M, Etherington R, Vuppussetty C, et al. Single cell spatial analysis reveals inflammatory foci of immature neutrophil and CD8 T cells in COVID-19 lungs. (2023). Nature Communications. doi:10.1038/s41467-023-42421-0 PMID:37940670
• Amarasinghe HE, Zhang P, Whalley JP, Allcock A, Migliorini G, Brown AC, Scozzafava G, Knight JC. Mapping the epigenomic landscape of human monocytes following innate immune activation reveals context-specific mechanisms driving endotoxin tolerance. (2023). BMC Genomics. doi:10.1186/s12864-023-09663-0 PMID:37805492
• Zhang JY, Whalley JP, Knight JC, Wicker LS, Todd JA, Ferreira RC. SARS-CoV-2 infection induces a long-lived pro-inflammatory transcriptional profile. (2023). Genome Medicine. doi:10.1186/s13073-023-01227-x PMID:37700317
• Fish M, Rynne J, Jennings A, Lam C, Lamikanra AA, Ratcliff J, Cellone-Trevelin S, et al. Coronavirus disease 2019 subphenotypes and differential treatment response to convalescent plasma in critically ill adults: secondary analyses of a randomized clinical trial. (2022). Intensive Care Medicine. doi:10.1007/s00134-022-06869-w PMID:36102943
• Kotanidis CP, Xie C, Alexander D, Rodrigues JCL, Burnham K, Mentzer A, O’Connor D, et al. Constructing custom-made radiotranscriptomic signatures of vascular inflammation from routine CT angiograms: a prospective outcomes validation study in COVID-19. (2022). The Lancet. Digital Health. doi:10.1016/S2589-7500(22)00132-7 PMID:36038496
• Gilchrist JJ, Makino S, Naranbhai V, Sharma PK, Koturan S, Tong O, Taylor CA, et al. Natural Killer cells demonstrate distinct eQTL and transcriptome-wide disease associations, highlighting their role in autoimmunity. (2022). Nature Communications. doi:10.1038/s41467-022-31626-4 PMID:35835762
• Zhang P, Amarasinghe HE, Whalley JP, Tay C, Fang H, Migliorini G, Brown AC, et al. Epigenomic analysis reveals a dynamic and context-specific macrophage enhancer landscape associated with innate immune activation and tolerance. (2022). Genome Biology. doi:10.1186/s13059-022-02702-1 PMID:35751107
• COvid-19 Multi-omics Blood ATlas (COMBAT) Consortium. A blood atlas of COVID-19 defines hallmarks of disease severity and specificity. (2022). Cell. doi:10.1016/j.cell.2022.01.012 PMID:35216673
• Zhang JY, Roberts H, Flores DSC, Cutler AJ, Brown AC, Whalley JP, Mielczarek O, et al. Using de novo assembly to identify structural variation of eight complex immune system gene regions. (2021). PLoS Computational Biology. doi:10.1371/journal.pcbi.1009254 PMID:34343164
• Navarro-Guerrero E, Tay C, Whalley JP, Cowley SA, Davies B, Knight JC, Ebner D. Genome-wide CRISPR/Cas9-knockout in human induced Pluripotent Stem Cell (iPSC)-derived macrophages. (2021). Scientific Reports. doi:10.1038/s41598-021-82137-z PMID:33608581
• Whalley JP, Buchhalter I, Rheinbay E, Raine KM, Stobbe MD, Kleinheinz K, Werner J, et al. Framework for quality assessment of whole genome cancer sequences. (2020). Nature Communications. doi:10.1038/s41467-020-18688-y PMID:33028839
• Bailey MH, Meyerson WU, Dursi LJ, Wang LB, Dong G, Liang WW, Weerasinghe A, et al. Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples. (2020). Nature Communications. doi:10.1038/s41467-020-18151-y PMID:32958763
• Li CH, Prokopec SD, Sun RX, Yousif F, Schmitz N, PCAWG Tumour Subtypes and Clinical Translation, Boutros PC, PCAWG Consortium. Sex differences in oncogenic mutational processes. (2020). Nature Communications. doi:10.1038/s41467-020-17359-2 PMID:32859912
• Cortés-Ciriano I, Lee JJ, Xi R, Jain D, Jung YL, Yang L, Gordenin D, et al. Comprehensive analysis of chromothripsis in 2,658 human cancers using whole-genome sequencing. (2020). Nature Genetics. doi:10.1038/s41588-019-0576-7 PMID:32025003
• Akdemir KC, Le VT, Chandran S, Li Y, Verhaak RG, Beroukhim R, Campbell PJ, et al. Disruption of chromatin folding domains by somatic genomic rearrangements in human cancer. (2020). Nature Genetics. doi:10.1038/s41588-019-0564-y PMID:32024999
• Rodriguez-Martin B, Alvarez EG, Baez-Ortega A, Zamora J, Supek F, Demeulemeester J, Santamarina M, et al. Pan-cancer analysis of whole genomes identifies driver rearrangements promoted by LINE-1 retrotransposition. (2020). Nature Genetics. doi:10.1038/s41588-019-0562-0 PMID:32024998
• Zapatka M, Borozan I, Brewer DS, Iskar M, Grundhoff A, Alawi M, Desai N, et al. The landscape of viral associations in human cancers. (2020). Nature Genetics. doi:10.1038/s41588-019-0558-9 PMID:32025001
• Yakneen S, Waszak SM, PCAWG Technical Working Group, Gertz M, Korbel JO, PCAWG Consortium. Butler enables rapid cloud-based analysis of thousands of human genomes. (2020). Nature Biotechnology. doi:10.1038/s41587-019-0360-3 PMID:32024987
• Yuan Y, Ju YS, Kim Y, Li J, Wang Y, Yoon CJ, Yang Y, et al. Comprehensive molecular characterization of mitochondrial genomes in human cancers. (2020). Nature Genetics. doi:10.1038/s41588-019-0557-x PMID:32024997
• Gerstung M, Jolly C, Leshchiner I, Dentro SC, Gonzalez S, Rosebrock D, Mitchell TJ, et al. The evolutionary history of 2,658 cancers. (2020). Nature. doi:10.1038/s41586-019-1907-7 PMID:32025013
• ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium. Pan-cancer analysis of whole genomes. (2020). Nature. doi:10.1038/s41586-020-1969-6 PMID:32025007
• PCAWG Transcriptome Core Group, Calabrese C, Davidson NR, Demircioğlu D, Fonseca NA, He Y, Kahles A, et al. Genomic basis for RNA alterations in cancer. (2020). Nature. doi:10.1038/s41586-020-1970-0 PMID:32025019
• Alexandrov LB, Kim J, Haradhvala NJ, Huang MN, Tian Ng AW, Wu Y, Boot A, et al. The repertoire of mutational signatures in human cancer. (2020). Nature. doi:10.1038/s41586-020-1943-3 PMID:32025018
• Rheinbay E, Nielsen MM, Abascal F, Wala JA, Shapira O, Tiao G, Hornshøj H, et al. Analyses of non-coding somatic drivers in 2,658 cancer whole genomes. (2020). Nature. doi:10.1038/s41586-020-1965-x PMID:32025015
• Li Y, Roberts ND, Wala JA, Shapira O, Schumacher SE, Kumar K, Khurana E, et al. Patterns of somatic structural variation in human cancer genomes. (2020). Nature. doi:10.1038/s41586-019-1913-9 PMID:32025012
• Carlevaro-Fita J, Lanzós A, Feuerbach L, Hong C, Mas-Ponte D, Pedersen JS, PCAWG Drivers and Functional Interpretation Group, Johnson R, PCAWG Consortium. Cancer LncRNA Census reveals evidence for deep functional conservation of long noncoding RNAs in tumorigenesis. (2020). Communications Biology. doi:10.1038/s42003-019-0741-7 PMID:32024996
• Reyna MA, Haan D, Paczkowska M, Verbeke LPC, Vazquez M, Kahraman A, Pulido-Tamayo S, et al. Pathway and network analysis of more than 2500 whole cancer genomes. (2020). Nature Communications. doi:10.1038/s41467-020-14367-0 PMID:32024854
• Jiao W, Atwal G, Polak P, Karlic R, Cuppen E, PCAWG Tumor Subtypes and Clinical Translation Working Group, Danyi A, et al. A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns. (2020). Nature Communications. doi:10.1038/s41467-019-13825-8 PMID:32024849
• Paczkowska M, Barenboim J, Sintupisut N, Fox NS, Zhu H, Abd-Rabbo D, Mee MW, et al. Integrative pathway enrichment analysis of multivariate omics data. (2020). Nature Communications. doi:10.1038/s41467-019-13983-9 PMID:32024846
• Cmero M, Yuan K, Ong CS, Schröder J, PCAWG Evolution and Heterogeneity Working Group, Corcoran NM, Papenfuss T, et al. Inferring structural variant cancer cell fraction. (2020). Nature Communications. doi:10.1038/s41467-020-14351-8 PMID:32024845
• Rubanova Y, Shi R, Harrigan CF, Li R, Wintersinger J, Sahin N, Deshwar AG, et al. Reconstructing evolutionary trajectories of mutation signature activities in cancer using TrackSig. (2020). Nature Communications. doi:10.1038/s41467-020-14352-7 PMID:32024834
• Zhang Y, Chen F, Fonseca NA, He Y, Fujita M, Nakagawa H, Zhang Z, et al. High-coverage whole-genome analysis of 1220 cancers reveals hundreds of genes deregulated by rearrangement-mediated cis-regulatory alterations. (2020). Nature Communications. doi:10.1038/s41467-019-13885-w PMID:32024823
• Bhandari V, Li CH, Bristow RG, Boutros PC, PCAWG Consortium. Divergent mutational processes distinguish hypoxic and normoxic tumours. (2020). Nature Communications. doi:10.1038/s41467-019-14052-x PMID:32024819
• Shuai S, PCAWG Drivers and Functional Interpretation Working Group, Gallinger S, Stein LD, PCAWG Consortium. Combined burden and functional impact tests for cancer driver discovery using DriverPower. (2020). Nature Communications. doi:10.1038/s41467-019-13929-1 PMID:32024818
• Sieverling L, Hong C, Koser SD, Ginsbach P, Kleinheinz K, Hutter B, Braun DM, et al. Genomic footprints of activated telomere maintenance mechanisms in cancer. (2020). Nature Communications. doi:10.1038/s41467-019-13824-9 PMID:32024817
• Stobbe MD, Thun GA, Diéguez-Docampo A, Oliva M, Whalley JP, Raineri E, Gut IG. Recurrent somatic mutations reveal new insights into consequences of mutagenic processes in cancer. (2019). PLoS Computational Biology. doi:10.1371/journal.pcbi.1007496 PMID:31765368