A more up-to-date list of publications may be found on my Google Scholar page.

Journal Articles

  1. GPseudoClust: deconvolution of shared pseudo-profiles at single-cell resolution
    Strauss, Magdalena E.; Kirk, Paul D. W.; Reid, John E.; Wernisch, Lorenz;
    Bioinformatics 2020, 36, 1484-1491.
    https://academic.oup.com/bioinformatics/article/36/5/1484/5586890
  2. Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen
    Menden, Michael P.; Wang, Dennis; Mason, Mike J.; Szalai, Bence; Bulusu, Krishna C.; Guan, Yuanfang; Yu, Thomas; Kang, Jaewoo; Jeon, Minji; Wolfinger, Russ; Nguyen, Tin; Zaslavskiy, Mikhail; Jang, In Sock; Ghazoui, Zara; Ahsen, Mehmet Eren; Vogel, Robert; Neto, Elias Chaibub; Norman, Thea; Tang, Eric K. Y.; Garnett, Mathew J.; Veroli, Giovanni Y. Di; Fawell, Stephen; Stolovitzky, Gustavo; Guinney, Justin; Dry, Jonathan R.; Saez-Rodriguez, Julio;
    Nature Communications 2019, 10, 2674.
    https://www.nature.com/articles/s41467-019-09799-2
  3. Integration of Multiple Epigenomic Marks Improves Prediction of Variant Impact in Saturation Mutagenesis Reporter Assay
    Shigaki, Dustin; Adato, Orit; Adhikar, Aashish N.; Dong, Shengcheng; Hawkins‐Hooker, Alex; Inoue, Fumitaka; Juven‐Gershon, Tamar; Kenlay, Henry; Martin, Beth; Patra, Ayoti; Penzar, Dmitry P.; Schubach, Max; Xiong, Chenling; Yan, Zhongxia; Boyle, Alan P.; Kreimer, Anat; Kulakovskiy, Ivan V.; Reid, John; Unger, Ron; Yosef, Nir; Shendure, Jay; Ahituv, Nadav; Kircher, Martin; Beer, Michael A.;
    Human Mutation , 0, .
    https://onlinelibrary.wiley.com/doi/abs/10.1002/humu.23797
  4. Branch-recombinant Gaussian processes for analysis of perturbations in biological time series
    Penfold, Christopher A.; Sybirna, Anastasiya; Reid, John E.; Huang, Yun; Wernisch, Lorenz; Ghahramani, Zoubin; Grant, Murray; Surani, M. Azim;
    Bioinformatics 2018, 34, i1005-i1013.
    https://academic.oup.com/bioinformatics/article/34/17/i1005/5093256
  5. Machine learning based classification of cells into chronological stages using single-cell transcriptomics
    Singh, Sumeet Pal; Janjuha, Sharan; Chaudhuri, Samata; Reinhardt, Susanne; Kränkel, Annekathrin; Dietz, Sevina; Eugster, Anne; Bilgin, Halil; Korkmaz, Selçuk; Zararsız, Gökmen; Ninov, Nikolay; Reid, John E.;
    Scientific Reports 2018, 8, 17156.
    https://www.nature.com/articles/s41598-018-35218-5
  6. Metabolic regulation of pluripotency and germ cell fate through α‐ketoglutarate
    Tischler, Julia; Gruhn, Wolfram H.; Reid, John; Allgeyer, Edward; Buettner, Florian; Marr, Carsten; Theis, Fabian; Simons, Ben D.; Wernisch, Lorenz; Surani, M. Azim;
    The EMBO Journal 2018, , e99518.
    http://emboj.embopress.org/content/early/2018/09/25/embj.201899518
  7. GPseudoRank: a permutation sampler for single cell orderings
    Strauß, Magdalena E.; Reid, John E.; Wernisch, Lorenz;
    Bioinformatics 2018, , .
    https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/bty664/5059496
  8. Clusternomics: Integrative context-dependent clustering for heterogeneous datasets
    Gabasova, Evelina; Reid, John; Wernisch, Lorenz;
    PLOS Computational Biology 2017, 13, e1005781.
    http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005781
  9. Pseudotime estimation: deconfounding single cell time series
    Reid, John E.; Wernisch, Lorenz;
    Bioinformatics 2016, , btw372.
    http://bioinformatics.oxfordjournals.org/content/early/2016/07/14/bioinformatics.btw372
  10. Conserved cis-regulatory modules control robustness in Msx1 expression at single cell resolution
    Vance, Keith W.; Woodcock, Dan J.; Reid, John E.; Bretschneider, Till; Ott, Sascha; Koentges, Georgy;
    Genome Biology and Evolution 2015, , evv179.
    http://gbe.oxfordjournals.org/content/early/2015/09/04/gbe.evv179
  11. STEME: A Robust, Accurate Motif Finder for Large Data Sets
    Reid, John E.; Wernisch, Lorenz;
    PLoS ONE 2014, 9, e90735.
    http://dx.doi.org/10.1371/journal.pone.0090735
  12. Nodal cis-regulatory elements reveal epiblast and primitive endoderm heterogeneity in the peri-implantation mouse embryo
    Granier, Céline; Gurchenkov, Vasily; Perea-Gomez, Aitana; Camus, Anne; Ott, Sascha; Papanayotou, Costis; Iranzo, Julian; Moreau, Anne; Reid, John; Koentges, Georgy; Sabéran-Djoneidi, Délara; Collignon, Jérôme;
    Developmental Biology 2011, 349, 350-362.
    http://www.sciencedirect.com/science/article/pii/S0012160610011747
  13. STEME: efficient EM to find motifs in large data sets
    Reid, J.E.; Wernisch, L.;
    Nucleic Acids Research 2011, 39, e126–e126.
    https://academic.oup.com/nar/article/39/18/e126/1094881
  14. An alignment-free model for comparison of regulatory sequences
    Koohy, H.; Dyer, N.P.; Reid, J.E.; Koentges, G.; Ott, S.;
    Bioinformatics 2010, 26, 2391.
    https://academic.oup.com/bioinformatics/article/26/19/2391/229951
  15. Variable structure motifs for transcription factor binding sites
    Reid, J.; Evans, K.; Dyer, N.; Wernisch, L.; Ott, S.;
    BMC Genomics 2010, 11, 30.
    https://bmcgenomics.biomedcentral.com/articles/10.1186/1471-2164-11-30
  16. Transcriptional programs: Modelling higher order structure in transcriptional control
    Reid, J.; Ott, S.; Wernisch, L.;
    BMC Bioinformatics 2009, 10, 218.
    https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-10-218
  17. Evolutionarily conserved regulatory motifs in the promoter of the Arabidopsis clock gene LATE ELONGATED HYPOCOTYL
    Spensley, M.; Kim, J.Y.; Picot, E.; Reid, J.; Ott, S.; Helliwell, C.; Carré, I.A.;
    The Plant Cell Online 2009, 21, 2606–2623.
    http://www.plantcell.org/content/21/9/2606

Preprints

  1. SCRAM: Spatially Coherent Randomized Attention Maps
    Calian, Dan A.; Roelants, Peter; Cali, Jacques; Carr, Ben; Dubba, Krishna; Reid, John E.; Zhang, Dell;
    ArXiv 2019, 1905.10308, .
    http://arxiv.org/abs/1905.10308
  2. Projection layers improve deep learning models of regulatory DNA function
    Hawkins-Hooker, Alex; Kenlay, Henry; Reid, John;
    bioRxiv 2018, , 412734.
    https://www.biorxiv.org/content/early/2018/09/10/412734
  3. Nonparametric Bayesian inference of transcriptional branching and recombination identifies regulators of early human germ cell development
    Penfold, Christopher Andrew; Sybirna, Anastasiya; Reid, John; Huang, Yun; Wernisch, Lorenz; Ghahramani, Zoubin; Grant, Murray; Surani, M. Azim;
    bioRxiv 2017, , 167684.
    http://www.biorxiv.org/content/early/2017/07/24/167684
  4. Mutual Information Estimation For Transcriptional Regulatory Network Inference
    Ish-Horowicz, Jonathan; Reid, John;
    bioRxiv 2017, , 132647.
    http://biorxiv.org/content/early/2017/05/01/132647

Theses

  1. Probabilistic models of transcriptional regulation
    John Reid
    PhD, Cambridge University, 2013.
  2. A comparison of various neural network architectures for learning context-dependent game strategies
    John Reid
    Diploma in Computer Science, Cambridge University, 1994.