| Decoding the regulatory network of early blood development from single-cell gene expression measurements V Moignard, S Woodhouse, L Haghverdi, AJ Lilly, Y Tanaka, ... Nature biotechnology 33 (3), 269-276, 2015 | 439 | 2015 |
| BTR: training asynchronous Boolean models using single-cell expression data CY Lim, H Wang, S Woodhouse, N Piterman, L Wernisch, J Fisher, ... BMC bioinformatics 17, 1-18, 2016 | 102 | 2016 |
| Single-cell antigen-specific landscape of CAR T infusion product identifies determinants of CD19-positive relapse in patients with ALL Z Bai, S Woodhouse, Z Zhao, R Arya, K Govek, D Kim, S Lundh, A Baysoy, ... Science advances 8 (23), eabj2820, 2022 | 97 | 2022 |
| SCNS: a graphical tool for reconstructing executable regulatory networks from single-cell genomic data S Woodhouse, N Piterman, CM Wintersteiger, B Göttgens, J Fisher BMC systems biology 12, 1-7, 2018 | 89 | 2018 |
| Single-cell analysis of CD4+ T-cell differentiation reveals three major cell states and progressive acceleration of proliferation V Proserpio, A Piccolo, L Haim-Vilmovsky, G Kar, T Lönnberg, ... Genome biology 17, 1-15, 2016 | 69 | 2016 |
| Single-cell multiomics dissection of basal and antigen-specific activation states of CD19-targeted CAR T cells Z Bai, S Lundh, D Kim, S Woodhouse, DM Barrett, RM Myers, SA Grupp, ... Journal for ImmunoTherapy of Cancer 9 (5), 2021 | 46 | 2021 |
| Single-cell transcriptomic analysis of mIHC images via antigen mapping KW Govek, EC Troisi, Z Miao, RG Aubin, S Woodhouse, PG Camara Science Advances 7 (10), eabc5464, 2021 | 40 | 2021 |
| Mapping Rora expression in resting and activated CD4+ T cells L Haim-Vilmovsky, J Henriksson, JA Walker, Z Miao, E Natan, G Kar, ... PloS one 16 (5), e0251233, 2021 | 38* | 2021 |
| Transcriptional hierarchies regulating early blood cell development V Moignard, S Woodhouse, J Fisher, B Göttgens Blood Cells, Molecules, and Diseases 51 (4), 239-247, 2013 | 31 | 2013 |
| Synthesising executable gene regulatory networks from single-cell gene expression data J Fisher, AS Köksal, N Piterman, S Woodhouse Computer Aided Verification: 27th International Conference, CAV 2015, San …, 2015 | 30 | 2015 |
| Single-cell analyses of regulatory network perturbations using enhancer-targeting TALEs suggest novel roles for PU.1 during haematopoietic specification AC Wilkinson, VKS Kawata, J Schütte, X Gao, S Antoniou, C Baumann, ... Development 141 (20), 4018-4030, 2014 | 29 | 2014 |
| Processing, visualising and reconstructing network models from single‐cell data S Woodhouse, V Moignard, B Göttgens, J Fisher Immunology and Cell Biology 94 (3), 256-265, 2016 | 19 | 2016 |
| Building an ENCODE-style data compendium on a shoestring D Ruau, FSL Ng, NK Wilson, R Hannah, E Diamanti, P Lombard, ... Nature methods 10 (10), 926-926, 2013 | 15 | 2013 |
| Developmental trajectories of thalamic progenitors revealed by single-cell transcriptome profiling and Shh perturbation KW Govek, S Chen, P Sgourdou, Y Yao, S Woodhouse, T Chen, ... Cell reports 41 (10), 2022 | 10 | 2022 |
| Using state space exploration to determine how gene regulatory networks constrain mutation order in cancer evolution MA Clarke, S Woodhouse, N Piterman, BA Hall, J Fisher Automated reasoning for systems biology and medicine, 133-153, 2019 | 8 | 2019 |
| AIRIVA: a deep generative model of adaptive immune repertoires MF Pradier, N Prasad, P Chapfuwa, S Ghalebikesabi, M Ilse, ... Machine Learning for Healthcare Conference, 588-611, 2023 | 7 | 2023 |
| Program synthesis meets deep learning for decoding regulatory networks J Fisher, S Woodhouse Current Opinion in Systems Biology 4, 64-70, 2017 | 6 | 2017 |
| Synthesising executable gene regulatory networks in haematopoiesis from single-cell gene expression data S Woodhouse University of Cambridge, 2017 | 3 | 2017 |
| Identifying immune signatures of common exposures through co-occurrence of T-cell receptors in tens of thousands of donors DH May, S Woodhouse, HJ Zahid, R Elyanow, K Doroschak, MT Noakes, ... bioRxiv, 2024.03. 26.583354, 2024 | 1 | 2024 |
| Seq2MAIT: A Novel Deep Learning Framework for Identifying Mucosal Associated Invariant T (MAIT) Cells H ElAbd, R Byron, S Woodhouse, B Robinett, J Sulc, A Franke, M Pesesky, ... bioRxiv, 2024.03. 12.584395, 2024 | 1 | 2024 |
Jasmin FisherProfessor of Computational Biology, UCL Cancer InstituteVerified email at ucl.ac.uk
