Now showing items 1-11 of 11

    • Bringing LTL Model Checking to Biologists 

      Ahmed, Z; Benque, D; Berezin, S; Dahl, ACE; Fisher, Jasmin; Hall, Benjamin Andrew; Ishtiaq, S et al.
      The BioModelAnalyzer (BMA) is a web based tool for the development of discrete models of biological systems. Through a graphical user interface, it allows rapid development of complex models of gene and protein interaction ...
    • BTR: training asynchronous Boolean models using single-cell expression data 

      Lim, Chee Yee; Wang, Huange; Woodhouse, Steven; Piterman, Nir; Wernisch, Lorenz; Fisher, Jasmin; Göttgens, Berthold (BioMed Central, 2016-09-06)
      Background Rapid technological innovation for the generation of single-cell genomics data presents new challenges and opportunities for bioinformatics analysis. One such area lies in the development of new ways to train ...
    • BTR: training asynchronous Boolean models using single-cell expression data 

      Lim, Chee; Wang, Huange; Woodhouse, Steven; Piterman, Nir; Wernisch, Lorenz; Fisher, Jasmin; Göttgens, Berthold (2016-09-06)
      BACKGROUND: Rapid technological innovation for the generation of single-cell genomics data presents new challenges and opportunities for bioinformatics analysis. One such area lies in the development of new ways to train ...
    • Cell-Specific Computational Modeling of the PIM Pathway in Acute Myeloid Leukemia. 

      Silverbush, Dana; Grosskurth, Shaun; Wang, Dennis; Powell, Francoise; Gottgens, Berthold; Dry, Jonathan; Fisher, Jasmin (American Association for Cancer Research, 2017-02)
      Personalized therapy is a major goal of modern oncology, as patient responses vary greatly even within a histologically defined cancer subtype. This is especially true in acute myeloid leukemia (AML), which exhibits striking ...
    • Computational modeling of the EGFR network elucidates control mechanisms regulating signal dynamics 

      Wang, Dennis YQ; Cardelli, Luca; Phillips, Andrew; Piterman, Nir; Fisher, Jasmin (2009-12-22)
    • Decoding the Regulatory Network for Blood Development from Single-Cell Gene Expression Measurements 

      Moignard, Victoria Rachel; Woodhouse, Steven; Haghverdi, Laleh; Lilly, Andrew J; Tanaka, Yosuke; Wilkinson, Adam; Buettner, Florian et al. (2015-02-09)
      Reconstruction of the molecular pathways controlling organ development has been hampered by a lack of methods to resolve embryonic progenitor cells. Here we describe a strategy to address this problem that combines gene ...
    • Drug Target Optimization in Chronic Myeloid Leukemia Using Innovative Computational Platform 

      Chuang, Ryan; Hall, Benjamin Andrew; Benque, David; Cook, Byron; Ishtiaq, Samin; Piterman, Nir; Taylor, Alex et al. (2015-02-03)
      Chronic Myeloid Leukemia (CML) represents a paradigm for the wider cancer field. Despite the fact that tyrosine kinase inhibitors have established targeted molecular therapy in CML, patients often face the risk of developing ...
    • Linear Temporal Logic for Biologists in BMA 

      Hall, Benjamin Andrew; Piterman, Nir; Fisher, Jasmin (Springer, 2016-09)
    • Processing, visualising and reconstructing network models from single cell data 

      Woodhouse, Steven; Moignard, Victoria Rachel; Göttgens, Berthold; Fisher, Jasmin (2015-11-18)
      New single-cell technologies readily permit gene expression profiling of thousands of cells at single-cell resolution. In this review we will discuss methods for visualisation and interpretation of single-cell gene expression ...
    • Program Synthesis Meets Deep Learning for Decoding Regulatory Networks 

      Fisher, Jasmin; Woodhouse, S
      With ever growing data sets spanning DNA sequencing all the way to single-cell transcriptomics, we are now facing the question of how can we turn this vast amount of information into knowledge. How do we integrate these ...
    • Single cell analyses of regulatory network perturbations using enhancer targeting TAL Effectors suggest novel roles for PU.1 during haematopoietic specification 

      Wilkinson, Adam; Kawata, Viviane KS; Schütte, Judith; Gao, Xuefei; Antoniou, Stella; Baumann, Claudia; Woodhouse, Steven et al. (2014-09-24)
      Transcription factors (TFs) act within wider regulatory networks to control cell identity and fate. Numerous TFs, including Scl (Tal1) and PU.1 (Spi1), are known regulators of developmental and adult haematopoiesis, but ...