Jeffrey Saucerman

Publications

• Graphical approach to model reduction for nonlinear biochemical networks
• Robustness portraits of diverse biological networks conserved despite order-of-magnitude parameter uncertainty
• Multi-scale model of phospholamban mutations in the mouse heart
• Regulation of nuclear PKA revealed by spatiotemporal manipulation of cyclic AMP
• PKA catalytic subunit compartmentation regulates contractile and hypertrophic responses to β-adrenergic signaling
• Multiscale model of heart growth during pregnancy: integrating mechanical and hormonal signaling
• Local plantar pressure relief in therapeutic footwear: Design guidelines from finite element models
• Mechanistic systems models of cell signaling networks: A case study of myocyte adrenergic regulation
• Modeling cardiac β-adrenergic signaling with normalized-Hill differential equations: Comparison with a biochemical model
• Multiscale modeling in rodent ventricular myocytes
• Network reconstruction and systems analysis of cardiac myocyte hypertrophy signaling
• Synergy between CaMKII substrates and β-adrenergic signaling in regulation of cardiac myocyte Ca2 handling
• Whole-genome metabolic network reconstruction and constraint-based modeling
• Logic-based mechanistic machine learning on high-content images reveals how drugs differentially regulate cardiac fibroblasts
• Network model integrated with multi-omic data predicts MBNL1 signals that drive myofibroblast activation
• Bigger, better, faster: Principles and models of AKAP anchoring protein signaling
• Cardiac β-adrenergic signaling: From subcellular microdomains to heart failure
• Endotoxin depresses heart rate variability in mice: Cytokine and steroid effects
• Calmodulin binding proteins provide domains of local Ca 2+ signaling in cardiac myocytes
• Computational models reduce complexity and accelerate insight into cardiac signaling networks
• Differential integration of Ca2+-calmodulin signal in intact ventricular myocytes at low and high affinity Ca2+-calmodulin targets
• Phospholemman is a negative feed-forward regulator of Ca 2+ in β-adrenergic signaling, accelerating β-adrenergic inotropy
• Systems analysis of small signaling modules relevant to eight human diseases
• Development and assessment of a novel systems bioengineering course integrating modeling and experimentation
• A kinetic model of beta-adrenergic control in cardiac myocytes
• Network analysis reveals a distinct axis of macrophage activation in response to conflicting inflammatory cues
• Benchmarking of protein interaction databases for integration with manually reconstructed signalling network models
• Virtual drug screen reveals context-dependent inhibition of cardiomyocyte hypertrophy
• Dynamic map illuminates Hippo to cMyc module crosstalk driving cardiomyocyte proliferation
• Signaling network model of cardiomyocyte morphological changes in familial cardiomyopathy
• Benchmarking of protein interaction databases for integration with manually reconstructed signaling network models
• Network Analysis Reveals a Distinct Axis of Macrophage Activation in Response to Conflicting Inflammatory Cues
• Automated image analysis identifies signaling pathways regulating distinct signatures of cardiac myocyte hypertrophy
• Cardiac biexcitability: Two ways to catch a wave
• Identification and characterization of Poly(I:C)-induced molecular responses attenuated by nicotine in mouse macrophages
• Erratum: Regulation of nuclear PKA revealed by spatiotemporal manipulation of cyclic AMP (Nature Chemical Biology (2012) 8 (375-382))
• Cytokine screening identifies NICU patients with Gram-negative bacteremia
• Automated image analysis of cardiac myocyte Ca 2+ dynamics
• Cardiac Models in Drug Discovery and Development: A Review
• Calmodulin mediates differential sensitivity of CaMKII and calcineurin to local Ca2+ in cardiac myocytes
• Systems analysis of PKA-mediated phosphorylation gradients in live cardiac myocytes
• Modeling regulation of cardiac KATP and L-type Ca2+ currents by ATP, ADP, and Mg2+
• A computational model of cardiac fibroblast signaling predicts context-dependent drivers of myofibroblast differentiation
• Computational Model Predicts Paracrine and Intracellular Drivers of Fibroblast Phenotype After Myocardial Infarction
• Computational model predicts paracrine and intracellular drivers of fibroblast phenotype after myocardial infarction
• Quantification of model and data uncertainty in a network analysis of cardiac myocyte mechanosignalling
• Multiscale model of heart growth during pregnancy: Integrating mechanical and hormonal signaling
• Context-specific network modeling identifies new crosstalk in β-adrenergic cardiac hypertrophy
• High-content live-cell imaging reveals co-regulation of cardiomyocyte decisions of hypertrophy and apoptosis
• A kinetic model of beta-adrenergic control in cardiac myocytes
• Modeling biochemical networks and excitation-contraction coupling
• Modeling β-Adrenergic Control of Cardiac Myocyte Contractility in Silico
• Proarrhythmic consequences of a KCNQ1 AKAP-binding domain mutation: Computational models of whole cells and heterogeneous tissue
• Modeling cardiomyocyte signaling and metabolism predicts genotype-to-phenotype mechanisms in hypertrophic cardiomyopathy
• Contributions of mechanical loading and hormonal changes to eccentric hypertrophy during volume overload: a Bayesian analysis using logic-based network models.
• Contributions of mechanical loading and hormonal changes to eccentric hypertrophy during volume overload: a Bayesian analysis using logic-based network models
• Single-cell dynamics reveal a stress-induced decision between cardiomyocyte hypertrophy and apoptosis
• Logic-based machine learning predicts how escitalopram inhibits cardiomyocyte hypertrophy
• Multiscale computational model predicts how environmental changes and treatments affect microvascular remodeling in fibrotic disease
• Logic-based machine learning predicts how escitalopram attenuates cardiomyocyte hypertrophy
• Dynamic map illuminates Hippo-cMyc module crosstalk driving cardiomyocyte proliferation
• Logic-based modeling of biological networks with Netflux