Synthesising executable gene regulatory networks from single-cell gene expression data

Metabolic stability and epigenesis in randomly constructed genetic nets

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Stochastic Modelling for Systems Biology

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Decoding the regulatory network of early blood development from single-cell gene expression measurements

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Defining an essential transcription factor program for naïve pluripotency

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Stochastic Modelling for Systems Biology

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Synchronous versus asynchronous modeling of gene regulatory networks

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From program verification to program synthesis

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Mapping cellular hierarchy by single cell analysis of the cell surface repertoire

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Programming by sketching for bit-streaming programs

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Hierarchical Differentiation of Myeloid Progenitors Is Encoded in the Transcription Factor Network

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Programming by sketching for bit-streaming programs

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Inferring rules of lineage commitment in haematopoiesis

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Characterisation of transcriptional networks in blood stem and progenitor cells using high-throughput single cell gene expression analysis

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Construction and Validation of a Regulatory Network for Pluripotency and Self-Renewal of Mouse Embryonic Stem Cells

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Hard-wired heterogeneity in blood stem cells revealed using a dynamic regulatory network model

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Template-based program verification and program synthesis

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A constraint-based approach to solving games on infinite graphs

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An Efficient Algorithm for Computing Attractors of Synchronous And Asynchronous Boolean Networks

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Reconstructing Boolean Models of Signaling

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Synthesis of biological models from mutation experiments

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Proving stabilization of biological systems

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Boolean Model of Yeast Apoptosis as a Tool to Study Yeast and Human Apoptotic Regulations

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Proving Stabilization of Biological Systems

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Transcriptional mechanisms of cell fate decisions revealed by single cell expression profiling

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Analyzing and Synthesizing Genomic Logic Functions

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Model-Checking Signal Transduction Networks through Decreasing Reachability Sets

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Qualitative modeling identifies IL-11 as a novel regulator in maintaining self-renewal in human pluripotent stem cells

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Finding Instability in Biological Models

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Synthesis of biological models from mutation experiments

Koksal, A. S., Pu, Y., Srivastava, S., Bodik, R., Fisher, J., & Piterman, N. (2013) · ACM SIGPLAN Notices · doi:10.1145/2480359.2429125

Revealing the vectors of cellular identity with single-cell genomics

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Mapping gene regulatory networks from single-cell omics data

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SCNS: a graphical tool for reconstructing executable regulatory networks from single-cell genomic data

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Review and assessment of Boolean approaches for inference of gene regulatory networks

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Learning regulatory models for cell development from single cell transcriptomic data

Babtie, A. C., Chan, T. E., & Stumpf, M. P. H. (2017) · Current Opinion in Systems Biology · doi:10.1016/j.coisb.2017.07.013 · Cited by 30 · see citing works

AEON: Attractor Bifurcation Analysis of Parametrised Boolean Networks

Beneš, N., Brim, L., Kadlecaj, J., Pastva, S., & Šafránek, D. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-53288-8_28 · Cited by 30 · see citing works

Processing, visualising and reconstructing network models from single‐cell data

Woodhouse, S., Moignard, V., Göttgens, B., & Fisher, J. (2015) · Immunology and Cell Biology · doi:10.1038/icb.2015.102 · Cited by 18 · see citing works

Automated Synthesis and Analysis of Switching Gene Regulatory Networks

Shavit, Y., Yordanov, B., Dunn, S.-J., Wintersteiger, C. M., Otani, T., Hamadi, Y., Livesey, F. J., & Kugler, H. (2016) · Biosystems · doi:10.1016/j.biosystems.2016.03.012 · Cited by 13 · see citing works

Exploring attractor bifurcations in Boolean networks

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Probabilistic boolean networks predict transcription factor targets to induce transdifferentiation

Tercan, B., Aguilar, B. H., Huang, S., Dougherty, E. R., & Shmulevich, I. (2022) · iScience · doi:10.1016/j.isci.2022.104951 · Cited by 7 · see citing works

Unsupervised logic-based mechanism inference for network-driven biological processes

Prugger, M., Einkemmer, L. D., Beik, S. P., Wasdin, P. T., Harris, L. A., & Lopez, C. F. (2021) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1009035 · Cited by 5 · see citing works

Program synthesis meets deep learning for decoding regulatory networks

Fisher, J., & Woodhouse, S. (2017) · Current Opinion in Systems Biology · doi:10.1016/j.coisb.2017.07.006 · Cited by 5 · see citing works

Formal modeling of biological systems

Wang, Q., & Clarke, E. M. (2016) · Proceedings · doi:10.1109/hldvt.2016.7748273 · Cited by 4 · see citing works

Program Synthesis Meets Deep Learning for Decoding Regulatory Networks

Fisher, J., & Woodhouse, S. (2017) · Apollo (University of Cambridge) · doi:10.17863/cam.11799 · Cited by 2 · see citing works

A formal methods approach to predicting new features of the eukaryotic vesicle traffic system

Bhattacharyya, A., Gupta, A., Kuppusamy, L., Mani, S., Shukla, A., Srivas, M. K., & Thattai, M. (2019) · Acta Informatica · doi:10.1007/s00236-019-00357-3 · Cited by 2 · see citing works

Synthesis for Vesicle Traffic Systems

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Algebraic polynomial-based synthesis for abstract Boolean network analysis

Backeman, P., Dunn, S.-J., Yordanov, B., & Wintersteiger, C. M. (2016) · International Workshop on Satisfiability Modulo Theories

Automatic mechanistic inference from large families of Boolean models generated by Monte Carlo tree search

Glazer, B. J., Lifferth, J., & Lopez, C. F. (2023) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2023.1198359

Synthesising executable gene regulatory networks in haematopoiesis from single-cell gene expression data

Woodhouse, S. (2016) · Apollo (University of Cambridge) · doi:10.17863/cam.15516 · Cited by 2 · see citing works

BTR: training asynchronous Boolean models using single-cell expression data

Lim, C., Wang, H., Woodhouse, S., Piterman, N., Wernisch, L., Fisher, J., & Göttgens, B. (2016) · Apollo (University of Cambridge) · doi:10.17863/cam.4701

Learning Asynchronous Boolean Networks From Single-Cell Data Using Multiobjective Cooperative Genetic Programming

Gao, S., Sun, C., Xiang, C., Qin, K., & Lee, T. H. (2020) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2020.3022430 · Cited by 22 · see citing works

LogicSR: prior-guided symbolic regression for gene regulatory network inference from single-cell transcriptomics data

Zhang, D., Liu, Z., & Gao, R. (2025) · Briefings in Bioinformatics · doi:10.1093/bib/bbaf621 · Cited by 3 · see citing works

Ingres : from single-cell RNA-seq data to single-cell probabilistic Boolean networksPreprint

Victori, P., & Buffa, F. M. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.09.04.506528