See also my google scholar profile.
2025
Aung, T.N.*, Monkman, J.*, Warrell, J.*, Bates, K., Gavrielatou, N., Trontzas, I., Tan, C.W., Vathiotis, I., Fernandez, A., Moutafi, M., O’ Byrne, K., Schalper, K.A., Herbst, R.S., Kulasinghe K. and Rimm, D.L., 2025. Enhancing Immunotherapy Outcomes: Spatial Multi-Omics Models for Non-Small Cell Lung Cancer. (*equal contribution, accepted to Nature Genetics)
Wang, G.*, Warrell, J.*, Emani, P.S. and Gerstein, M., 2025. Quantum variational autoencoder utilizing regularized mixed-state latent representations. Physical Review A. (*equal contribution)
Aung, T.N., … Warrell, J., Saenger, Y., Hartman, J., Plummer, J., Osman, I., Rimm, D.L. and Acs, B. Analytical and Clinical Validity of Pathologist-read versus AI-Driven Assessments of Tumor- Infiltrating Lymphocytes in Melanoma: A Multi-Operator and Multi-Institutional Study. (accepted at Journal of the American Medical Association Network Open)
2024
Song, T., Cosatto, E., Wang, G., Kuang, R., Gerstein, M., Min, M.R. and Warrell, J.*, 2024. Predicting spatially resolved gene expression via tissue morphology using adaptive spatial GNNs. Bioinformatics, 40(Supplement_2), pp.ii111-ii119. (*corresponding author, oral presentation at ECCB)
Aung, T.N.*, Warrell, J.*, Martinez-Morilla, S., Gavrielatou, N., Vathiotis, I., Yaghoobi, V., Kluger, H.M., Gerstein, M. and Rimm, D.L., 2024. Spatially informed gene signatures for response to immunotherapy in melanoma. Clinical Cancer Research. (*equal contribution)
J. Warrell,*, Salichos, L.*, Gancz, M.* and Gerstein, M.B., 2024. Latent evolutionary signatures: a general framework for analysing music and cultural evolution. Journal of the Royal Society Interface, 21(212), p.20230647. (*equal contribution)
Wang, G.*, Warrell, J.*, Zheng, S. and Gerstein, M., 2024. A variational graph-partitioning approach to modeling protein liquid-liquid phase separation. Cell Reports Physical Science, 5(11). (*equal contribution)
Prashant S. Emani*, Jason J. Liu*, Declan Clarke*, Matthew Jensen*, Jonathan Warrell*, Chirag Gupta*, Ran Meng*, Che Yu Lee*, Siwei Xu*, Cagatay Dursun*, Shaoke Lou*, Yuhang Chen, Zhiyuan Chu, Timur Galeev, Ahyeon Hwang, Yunyang Li, Pengyu Ni, Xiao Zhou, PsychENCODE Consortium, Trygve E. Bakken, Jaroslav Bendl, Lucy Bicks, Tanima Chatterjee, Lijun Cheng, Yuyan Cheng, Yi Dai, Ziheng Duan, Mary Flaherty, John F. Fullard, Michael Gancz, Diego Garrido-Martín, Sophia Gaynor-Gillett, Jennifer Grundman, Natalie Hawken, Ella Henry, Gabriel E. Hoffman, Ao Huang, Yunzhe Jiang, Ting Jin, Nikolas L. Jorstad, Riki Kawaguchi, Saniya Khullar, Jianyin Liu, Junhao Liu, Shuang Liu, Shaojie Ma, Michael Margolis, Samantha Mazariegos, Jill Moore, Jennifer R. Moran, Eric Nguyen, Nishigandha Phalke, Milos Pjanic, Henry Pratt, Diana Quintero, Ananya S. Rajagopalan, Tiernon R. Riesenmy, Nicole Shedd, Manman Shi, Megan Spector, Rosemarie Terwilliger, Kyle J. Travaglini, Brie Wamsley, Gaoyuan Wang, Yan Xia, Shaohua Xiao, Andrew C. Yang, Suchen Zheng, Michael J. Gandal, Donghoon Lee, Ed S. Lein, Panos Roussos, Nenad Sestan, Zhiping Weng, Kevin P. White, Hyejung Won, Matthew J. Girgenti, Jing Zhang, Daifeng Wang, Daniel Geschwind, Mark Gerstein. 2024. Single-cell genomics and regulatory networks for 388 human brains. Science, 384(6698), p.eadi5199. (* equal contribution)
2023
Meredith, L.G., Goertzel, B., Warrell, J. and Vandervorst, A., 2023. Meta-MeTTa: an operational semantics for MeTTa. arXiv preprint arXiv:2305.17218.
Salichos, L.*, Warrell, J.*, Cevasco, H., Chung, A. and Gerstein, M., 2023. Genetic determination of regional connectivity in modelling the spread of COVID-19 outbreak for more efficient mitigation strategies. Scientific Reports, 13(1), p.8470. (* equal contribution)
Lau, B., Emani, P.S., Chapman, J., Yao, L., Lam, T., Merrill, P., Warrell, J., Gerstein, M.B. and Lam, H.Y., 2023. Insights from incorporating quantum computing into drug design workflows. Bioinformatics, 39(1), p.btac789.
2022
J. Warrell, A. Potapov, A. Vandervorst and B. Goertzel, 2022. A meta-probabilistic-programming language for bisimulation of probabilistic and non-well-founded type systems. In International Conference on Artificial General Intelligence. (oral presentation at AGI 2022) (slides) (code) (paper)
J. Warrell, and M. B. Gerstein, 2022. Higher-Order Generalization Bounds: Learning Deep Probabilistic Programs via PAC-Bayes Objectives. arXiv preprint arXiv:2203.15972.
J. Warrell, Emani, P. and Gerstein, M. 2022. Hybrid Quantum-Classical Stochastic Networks with Boltzmann Layers. Preprint.
Gavrielatou, N., Warrell, J., Aung, T., Vathiotis, L., Economopoulou, P., Burtness, B., Psyrri, A. and Rimm, D., 2022. Spatially defined gene signatures uncover the association of extracellular matrix genes with immunotherapy resistance in head and neck squamous cell carcinoma. Journal for ImmunoTherapy of Cancer 10 (Suppl 2)
2021
Emani, P.S.*, Warrell, J.*, Anticevic, A., Bekiranov, S., Gandal, M., McConnell, M.J., Sapiro, G., Aspuru-Guzik, A., Baker, J., Bastiani, M., McClure, P., Murray, J., Sotiropoulos, S.N., Taylor, J., Senthil, J., Lehner, T., Gerstein, M., Aram W. Harrow, A.W., 2021. Quantum Computing at the Frontiers of Biological Sciences. Nature Methods. (* equal contribution)
Savulescu, A.F., Brackin, R., Bouilhol, E., Dartigues, B., Warrell, J.H., Pimentel, M.R., Beaume, N., Fortunato, I.C., Dallongeville, S., Boulle, M. and Soueidan, H. ... Mhlanga, M., 2021. Interrogating RNA and protein spatial subcellular distribution in smFISH data with DypFISH. Cell Reports Methods, 1(5), p.100068.
Aung, T.N., Acs, B., Warrell, J., Bai, Y., Gaule, P., Martinez-Morilla, S., Vathiotis, I., Shafi, S., Moutafi, M., Gerstein, M. and Freiberg, B., 2021. A new tool for technical standardization of the Ki67 immunohistochemical assay. Modern Pathology, pp.1-10.
2020
Kumar S*, Warrell J*, Li S, McGillivray P, Meyerson W, Salichos L, Harmanci A, Martinez-Fundichely A, Chan CW, Nielsen M, Lochovsky L., ... , Gerstein, M.B. Passenger mutations in more than 2500 cancer genomes: Overall molecular functional impact and consequences. Cell, 2020. (* equal contribution)
Salichos, L., Meyerson, W.U., Warrell, J. and Gerstein. Estimating growth patterns and driver effects in tumor evolution from individual samples. Nature Communications, 2020.
Rheinbay, E., Nielsen, M.M., Abascal, F., Wala, J.A., Shapira, O., Tiao, G., Hornshøj, H., Hess, J.M., Juul, R.I., Lin, Z., Feuerbach, L., … Warrell, J., … Zamora, J. 2020. Analyses of non-coding somatic drivers in 2,658 cancer whole genomes. Nature, 578(7793), pp.102-111.
J. Warrell, H. Mohsen and M. B. Gerstein, M. 2020. Compression based network interpretability schemes. bioRxiv.
Zhang, J., Lee, D., Dhiman, V., Jiang, P., Xu, J., McGillivray, P., Yang, H., Liu, J., Meyerson, W., Clarke, D. and Gu, M., Li, S., Lou, S., Xu, J., Lochovsky, L., Ung, M., Ma, L., Yu, S., Cao, Q., Harmanci, A., Yan, K., Sethi, A., Gursoy, G., Schoenberg, M.R., Rozowsky, J., Warrell, J., … Gerstein, M., 2020. An integrative ENCODE resource for cancer genomics. Nature communications, 11(1), pp.1-11.
2019
Warrell, J., and Gerstein, M. B., 2019. Cyclic and Multilevel Causality in Evolutionary Processes. Biology & Philosophy, 35(5), pp.1-36.
Warrell, J., and Gerstein, M., 2019. Hierarchical PAC-Bayes Bounds via Deep Probabilistic Programming. In Bayesian Deep Learning Workshop at NeurIPS.
Warrell, J., and Gerstein, M., 2019. PAC-Bayes Objectives for Meta-Learning using Deep Probabilistic Programs. In NeurIPS Workshop on Meta-Learning.
Rozowsky, J., Kitchen, R.R., Park, J.J., Galeev, T.R., Diao, J., Warrell, J., Thistlethwaite, W., Subramanian, S.L., Milosavljevic, A. and Gerstein, M., 2019. exceRpt: A Comprehensive Analytic Platform for Extracellular RNA Profiling. Cell systems, 8(4), pp.352-357.
Murillo, O.D., Thistlethwaite, W., Rozowsky, J., Subramanian, S.L., Lucero, R., Shah, N., Jackson, A.R., Srinivasan, S., Chung, A., Laurent, C.D., Kitchen, R.R., Galeev, T., Warrell, J., … and Milosavljevic, A., 2019. exRNA Atlas Analysis Reveals Distinct Extracellular RNA Cargo Types and Their Carriers Present across Human Biofluids. Cell, 177(2), pp.463-477.
2018
D Wang*, S Liu*, J Warrell*, H Won*, X Shi*, FCP Navarro*, D Clarke*, M Gu*, P Emani*, YT Yang, M Xu, MJ Gandal, S Lou, J Zhang, JJ Park, C Yan, SK Rhie, K Manakongtreecheep, H Zhou, A Nathan, M Peters, E Mattei, D Fitzgerald, T Brunetti, J Moore, Y Jiang, K Girdhar, GE Hoffman, S Kalayci, ZH Gumus, GE Crawford, PsychENCODE Consortium, P Roussos, S Akbarian, AE Jaffe, KP White, Z Weng, N Sestan, DH Geschwind, JA Knowles, MB Gerstein. “Comprehensive functional genomic resource and integrative model for the human brain”, Science, 2018. (* equal contribution)
MJ Gandal, P Zhang, E Hadjimichael, RL Walker, C Chen, S Liu, H Won, H van Bakel, M Varghese, Y Wang, AW Shieh, J Haney, S Parhami, J Belmont, M Kim, P Moran Losada, Z Khan, J Mleczko, Y Xia, R Dai, D Wang, YT Yang, M Xu, K Fish, PR Hof, J Warrell, D Fitzgerald, K White, AE Jaffe, PsychENCODE Consortium, MA Peters, M Gerstein, C Liu, LM Iakoucheva, D Pinto, DH Geschwind. “Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder” Science, 2018.
Warrell J, Mohsen H, Gerstein M. “Rank Projection Trees for Multilevel Neural Network Interpretation”, NeurIPS Workshop on Machine Learning for Health, 2018.
Warrell J, Gerstein M. “Dependent Type Networks: A Probabilistic Logic via the Curry-Howard Correspondence in a System of Probabilistic Dependent Types”, Uncertainty in Artificial Intelligence Workshop on Uncertainty in Deep Learning, 2018.
Rozowsky, J., Kitchen, R.R., Park, J., Galeev, T., Diao, J., Warrell, J., Thistlethwaite, W., Subramanian, S.L., Milosavljevic, A. and Gerstein, M.B. The extracellular RNA-Seq processing pipeline of the Extracellular RNA Communication Consortium. Journal of Extracellular Vesicles, 2018.
Murillo, O.D., Thistlethwaite, W., Lucero, R., Subramanian, S.L., Shah, N., Jackson, A.R., Rozowsky, J., Kitchen, R.R., Diao, J., Galeev, T. and Warrell, J. ExRNA Atlas analysis provides an exRNA census and reveals six types of vesicular and non-vesicular exRNA carrier profiles detectable across human body fluids. Journal of Extracellular Vesicles, 2018.
2017
J. Warrell and M. M. Mhlanga. “Stability and Structural Properties of Gene Regulation Networks with Coregulation Rules”, Journal of Theoretical Biology, 420:304-317, 2017.
2016
J. Rozowsky, R. Kitchen, T. Galeev, J. H. Warrell, S. Subramanian, W. Thistlewaite, M. Roth, A. Milosavljevic and M. Gerstein. “Phylogenetic Analysis of Exogenous Sequences from Extracellular RNA-seq Data using the excerpt Pipeline”, NIH Extracellular RNA Communication Consortium 7th Investigators’ Meeting, 2016. (oral)
J. H. Warrell, A. F. Savulescu, R. Brackin and M. M. Mhlanga. “Generalized Statistical Tests for mRNA and Protein Subcellular Spatial Patterning against Complete Spatial Randomness”, arXiv preprint arXiv:1602.06429, 2016.
J. H. Warrell. “A Probabilistic Dependent Type System based on Non-Deterministic Beta Reduction”, arXiv preprint arXiv:1602.06420, 2016.
2015
R. Brackin*, A. F. Savulescu*, J. H. Warrell*, S. Dallongeville, J. Schmoranzer, J. C. Olivio-Marin and M. M. Mhlanga. “A High Content Imaging Method for the De-novo Identification of Subcellular Localization of mRNAs and Proteins”, European Molecular Biology Organization Conference on RNA Localization and Local Translation, 2015. (* equal contribution)
J. H. Warrell and M. M. Mhlanga. “Effects of Stochastic Coregulation and Hierarchy on Attractor and Steady-state Distributions in in silico Gene Regulatory Networks”, Cold Spring Harbor Conference on Probabilistic Modeling in Genomics, 2015.
J. H. Warrell*, A. F. Savulescu*, R. Brackin* and M. M. Mhlanga. “A Random Measure Based Framework for Identifying Patterns of Clustering in Localized mRNA and Protein Distributions”, Cold Spring Harbor Conference on Probabilistic Modeling in Genomics, 2015. (* equal contribution)
2014
V. Vineet*, J. H. Warrell*, and P. H. S. Torr. “Filter-based Mean-field Inference for Random Fields with Higher-order Terms and Product Label-Spaces”, International Journal of Computer Vision (ICCV) 110(3):290-307, 2014. (* equal contribution)
S. Zheng, M. Cheng, J. H. Warrell, P. Sturgess, V. Vineet, C. Rother and P. H. S. Torr. “Dense Semantic Image Segmentation with Objects and Attributes”, In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3214-3221, 2014.
V. Vineet, J. H. Warrell and P. H. S. Torr. “A Tiered Move-making Algorithm for General Non-submodular Pairwise Energies”, arXiv preprint arXiv:1403.6275, 2014.
R. Brackin, A. F. Savulescu, J. H. Warrell, S. Dallongeville, J. C. Olivio-Marin and M. M. Mhlanga. “An Integrated Systems Biology Approach to Single Cell RNA Distribution Analysis”, Cold Spring Harbor Asia Conference on RNA Biology, 2014.
A. F. Savulescu, R. Brackin, J. H. Warrell, D. Whitney, S. Utete and M. M. Mhlanga. “Determination of Sub-Cellular Localization of mRNA and Proteins in Patterned Cells”, Cold Spring Harbor Asia Conference on RNA Biology, 2014.
2013
J. P. C. Valentin, S. Sengupta, J. H. Warrell, A. Shahroknia and P. H. S. Torr. “Mesh Based Semantic Modelling for Indoor and Outdoor Scenes”, In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2067-2074, 2013.
V. Vineet, G. Sheasby, J. H. Warrell and P. H. S. Torr. “PoseField: An Efficient Mean-Field Based Method for Joint Estimation of Human Pose, Segmentation, and Depth”, In Energy Minimization Methods in Computer Vision and Pattern Recognition, pp. 180-194, Springer Berlin Heidelberg. 2013.
M. Cheng, J. H. Warrell, W. Lin, S. Zheng, V. Vineet and N. Crook. “Efficient Salient Region Detection with Soft Image Abstraction”, In Proceedings of the IEEE International Conference on Computer Vision, pp. 1529-1536, 2013.
N. Govender*, J. H. Warrell*, P. H. S. Torr and F. Nicolls. “Probabilistic Object and Viewpoint Models for Active Object Recognition”, In Proceedings of the IEEE AFRICON Conference, 2013. (* equal contribution) (oral)
M. Cheng, S. Zheng, W. Lin, J. H. Warrell, V. Vineet, P. Sturgess, N. Crook, N. J. Mitra and P. H. S. Torr. “ImageSpirit: Verbal Guided Image Parsing”, arXiv preprint arXiv:1310.4389, 2013.
2012
V. Vineet*, J. H. Warrell*, and P. H. S. Torr. “Filter-based Mean-field Inference for Random Fields with Higher-order Terms and Product Label-Spaces”, In Proceedings of the European Conference on Computer Vision, pp. 31-44, 2012. (* equal contribution, oral)
V. Vineet, J. H. Warrell, and P. H. S. Torr. “Improved Initialization and Gaussian Mixture Pairwise Terms for Dense Random Fields with Mean-field Inference”, In Proceedings of the British Machine Vision Conference, 2012. (oral)
V. Vineet, J. H. Warrell, and P. H. S. Torr. “A Tiered Move-making Algorithm for General Pairwise MRFs”, In Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition, pp. 1632-1639, 2012.
2011
J. H. Warrell and P. H. S. Torr. “Multiple-Instance Learning with Structured Bag Models”, In Energy Minimization Methods in Computer Vision and Pattern Recognition, Springer Berlin Heidelberg, 2011. (oral)
V. Vineet, J. H. Warrell, L. Ladick´y, and P. H. S. Torr. “Human Instance Segmentation from Video using Detector-based Conditional Random Fields”, In Proceedings of the British Machine Vision Conference, 2011.
Z. Zhang, J. H. Warrell and P. H. S. Torr. “Proposal Generation for Object Detection using Cascaded Ranking SVMs”, In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1497-1504, 2011.
2010
J. H. Warrell, S. Prince, and P. H. S. Torr. “StyP-Boost: A Bilinear Boosting Algorithm for Learning Style-Parameterized Classifiers”, In Proceedings of the British Machine Vision Conference, 2010. (oral)
P. Li, J. H. Warrell, J. Aghajanian, and S. J. D. Prince. “Context Based Additive Logistic Models for Facial Keypoint Localization”, In Proceedings of the British Machine Vision Conference, 2010.
A. Moore, S. J. D. Prince, and J. H. Warrell. “Lattice Cut – Constructing Superpixels using Layer Constraints”, In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2117-2124, 2010.
Y. Mizukami, K. Tadamura, J. H. Warrell, P. Li, S. J. D. Prince. “CUDA Implementation of Deformable Pattern Recognition and its Application to MNIST Handwritten Digit Database”, In Proceedings of the IEEE International Conference on Pattern Recognition, pp. 2001-2004, 2010.
2009
J. H. Warrell*, A.P. Moore* and S.J.D. Prince. “Vistas: Hierarchical Boundary Priors using Multiscale Conditional Random Fields”, In Proceedings of the British Machine Vision Conference, 2009. (* equal contribution)
J. Aghajanian, J. H. Warrell, S. J. D. Prince, P. Li, J. L. Rohn, B. Baum:. “Patch based Within-Object Classification”, In Proceedings of the IEEE International Conference on Computer Vision, pp. 1125-1132, 2009.
J. H. Warrell and S. J. D. Prince. “LabelFaces: Parsing Facial Features by Multiclass Labeling with an Epitome Prior”, In Proceedings of the IEEE International Conference on Image Processing, 2481-2484, 2009.
J. H. Warrell, S. J. D. Prince and A. P. Moore. “Epitomized Priors for Multi-labeling Problems”, In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2812-2819, 2009.
A. P. Moore, S. J. D. Prince, J. H. Warrell, U. Mohammed, G. Jones. “Scene shape priors for superpixel segmentation”, In Proceedings of the IEEE International Conference on Computer Vision, 771-778, 2009.
2008
A. P. Moore, S. J. D. Prince, J. H. Warrell, U. Mohammed and G. Jones. “Superpixel Lattices”, In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2008.
S. J. D. Prince, J. H. Elder, J. H. Warrell and F. Felisberti. “Tied Factor Analysis for Face Recognition Across Large Pose Differences”, In IEEE Transactions on Pattern Analysis and Machine Intelligence, 30(6):970-984, 2008.
2007
J. Warrell, 2007. Music Classification, Generation, Inpainting and Analogies. M.Sc. thesis, University College London.
2006
J. Warrell, 2006. Repetition in the Music of Arnold Schoenberg. Ph.D. thesis, King's College London.