Khalilimeybodi, A., Saucerman, J. J., & Rangamani, P. (2024). Modeling cardiomyocyte signaling and metabolism predicts genotype-to-phenotype mechanisms in hypertrophic cardiomyopathy.. Computers in biology and medicine, 175, 108499. doi:10.1016/j.compbiomed.2024.108499

Nelson, A. R., Christiansen, S. L., Naegle, K. M., & Saucerman, J. J. (2024). Logic- based mechanistic machine learning on high- content images reveals how drugs differentially regulate cardiac fibroblasts. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 121(5). doi:10.1073/pnas.2303513121

Woo, L. A., Wintruba, K. L., Wissmann, B., Tkachenko, S., Kubicka, E., Farber, E., . . . Saucerman, J. J. (2024). Multi-omic analysis reveals VEGFR2, PI3K, and JNK mediate the small molecule induction of human iPSC-derived cardiomyocyte proliferation. ISCIENCE, 27(8). doi:10.1016/j.isci.2024.110485

Cao, S., Buchholz, K. S., Tan, P., Stowe, J. C., Wang, A., Fowler, A., . . . Mcculloch, A. D. (2024). Differential sensitivity to longitudinal and transverse stretch mediates transcriptional responses in mouse neonatal ventricular myocytes. AMERICAN JOURNAL OF PHYSIOLOGY-HEART AND CIRCULATORY PHYSIOLOGY, 326(2), H370-H384. doi:10.1152/ajpheart.00562.2023

Nelson, A. R., Christiansen, S. L., Naegle, K. M., & Saucerman, J. J. (2023). Logic-based mechanistic machine learning on high-content images reveals how drugs differentially regulate cardiac fibroblasts.. bioRxiv. doi:10.1101/2023.03.01.530599

Van de Graaf, M. W., Eggertsen, T. G., Zeigler, A. C., Tan, P. M., & Saucerman, J. J. (2023). Benchmarking of protein interaction databases for integration with manually reconstructed signalling network models. JOURNAL OF PHYSIOLOGY-LONDON. doi:10.1113/JP284616

Nelson, A. R., Bugg, D., Davis, J., & Saucerman, J. J. (2023). Network model integrated with multi-omic data predicts MBNL1 signals that drive myofibroblast activation. ISCIENCE, 26(4). doi:10.1016/j.isci.2023.106502

Khalilimeybodi, A., Riaz, M., Campbell, S. G., Omens, J. H., McCulloch, A. D., Qyang, Y., & Saucerman, J. J. (2023). Signaling network model of cardiomyocyte morphological changes in familial cardiomyopathy. JOURNAL OF MOLECULAR AND CELLULAR CARDIOLOGY, 174, 1-14. doi:10.1016/j.yjmcc.2022.10.006

Chowkwale, M., Lindsey, M. L., & Saucerman, J. J. (2023). Intercellular model predicts mechanisms of inflammation-fibrosis coupling after myocardial infarction. JOURNAL OF PHYSIOLOGY-LONDON, 601(13), 2635-2654. doi:10.1113/JP283346

Yoshida, K., Saucerman, J. J., & Holmes, J. W. (2022). Multiscale model of heart growth during pregnancy: integrating mechanical and hormonal signaling. BIOMECHANICS AND MODELING IN MECHANOBIOLOGY, 21(4), 1267-1283. doi:10.1007/s10237-022-01589-y

Young, A., Bradley, L. A., Farrar, E., Bilcheck, H. O., Tkachenko, S., Saucerman, J. J., . . . Wolf, M. J. (2022). Inhibition of DYRK1a Enhances Cardiomyocyte Cycling After Myocardial Infarction. CIRCULATION RESEARCH, 130(9), 1345-1361. doi:10.1161/CIRCRESAHA.121.320005

Hota, S. K., Rao, K. S., Blair, A. P., Khalilimeybodi, A., Hu, K. M., Thomas, R., . . . Bruneau, B. G. (2022). Brahma safeguards canalization of cardiac mesoderm differentiation. NATURE, 602(7895), 129-+. doi:10.1038/s41586-021-04336-y

Harris, A. R., Esparza, S., Azimi, M. S., Cornelison, R., Azar, F. N., Llaneza, D. C., . . . Munson, J. M. (2022). Platinum Chemotherapy Induces Lymphangiogenesis in Cancerous and Healthy Tissues That Can be Prevented With Adjuvant Anti-VEGFR3 Therapy. FRONTIERS IN ONCOLOGY, 12. doi:10.3389/fonc.2022.801764

Gorick, C. M., Saucerman, J. J., & Price, R. J. (2022). Computational model of brain endothelial cell signaling pathways predicts therapeutic targets for cerebral pathologies. JOURNAL OF MOLECULAR AND CELLULAR CARDIOLOGY, 164, 17-28. doi:10.1016/j.yjmcc.2021.11.005

Chavkin, N. W., Sano, S., Wang, Y., Oshima, K., Ogawa, H., Horitani, K., . . . Walsh, K. (2021). The Cell Surface Receptors Ror1/2 Control Cardiac Myofibroblast Differentiation. JOURNAL OF THE AMERICAN HEART ASSOCIATION, 10(13). doi:10.1161/JAHA.120.019904

Grabowska, M. E., Chun, B., Moya, R., & Saucerman, J. J. (2021). Computational model of cardiomyocyte apoptosis identifies mechanisms of tyrosine kinase inhibitor-induced cardiotoxicity. JOURNAL OF MOLECULAR AND CELLULAR CARDIOLOGY, 155, 66-77. doi:10.1016/j.yjmcc.2021.02.014

Zeigler, A. C., Chandrabhatla, A. S., Christiansen, S. L., Nelson, A. R., Holmes, J. W., & Saucerman, J. J. (2021). Network model-based screen for FDA-approved drugs affecting cardiac fibrosis. CPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY, 10(4), 377-388. doi:10.1002/psp4.12599

McCulloch, A. D., Grandi, E., & Saucerman, J. J. (2021). Computational models of cardiovascular regulatory mechanisms. JOURNAL OF MOLECULAR AND CELLULAR CARDIOLOGY, 155, 111. doi:10.1016/j.yjmcc.2021.01.009

Liu, X., Zhang, J., Zeigler, A. C., Nelson, A. R., Lindsey, M. L., & Saucerman, J. J. (2021). Network Analysis Reveals a Distinct Axis of Macrophage Activation in Response to Conflicting Inflammatory Cues. JOURNAL OF IMMUNOLOGY, 206(4), 883-891. doi:10.4049/jimmunol.1901444

Rogers, J. D., Holmes, J. W., Saucerman, J. J., & Richardson, W. J. (2021). Mechano-chemo signaling interactions modulate matrix production by cardiac fibroblasts.. Matrix biology plus, 10, 100055. doi:10.1016/j.mbplus.2020.100055

Khalilimeybodi, A., Paap, A. M., Christiansen, S. L. M., & Saucerman, J. J. (2020). Context-specific network modeling identifies new crosstalk in β-adrenergic cardiac hypertrophy. PLOS COMPUTATIONAL BIOLOGY, 16(12). doi:10.1371/journal.pcbi.1008490

Estrada, A. C., Yoshida, K., Saucerman, J. J., & Holmes, J. W. (2021). A multiscale model of cardiac concentric hypertrophy incorporating both mechanical and hormonal drivers of growth. BIOMECHANICS AND MODELING IN MECHANOBIOLOGY, 20(1), 293-307. doi:10.1007/s10237-020-01385-6

Cao, S., Aboelkassem, Y., Wang, A., Valdez-Jasso, D., Saucerman, J. J., Omens, J. H., & McCulloch, A. D. (2020). Quantification of model and data uncertainty in a network analysis of cardiac myocyte mechanosignalling. PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 378(2173). doi:10.1098/rsta.2019.0336

Zeigler, A. C., Nelson, A. R., Chandrabhatla, A. S., Brazhkina, O., Holmes, J. W., & Saucerman, J. J. (2020). Computational model predicts paracrine and intracellular drivers of fibroblast phenotype after myocardial infarction. MATRIX BIOLOGY, 91-92, 136-151. doi:10.1016/j.matbio.2020.03.007

Yoshida, K., Saucerman, J., & Holmes, J. (2020). Multiscale model of heart growth during pregnancy: Integrating mechanical and hormonal signaling. doi:10.1101/2020.09.18.302067

Zeigler, A., Nelson, A., Chandrabhatla, A., Brazhkina, O., Holmes, J., & Saucerman, J. (2019). Computational Model Predicts Paracrine and Intracellular Drivers of Fibroblast Phenotype After Myocardial Infarction. doi:10.1101/840017

Saucerman, J. J., Tan, P. M., Buchholz, K. S., McCulloch, A. D., & Omens, J. H. (2019). Mechanical regulation of gene expression in cardiac myocytes and fibroblasts. NATURE REVIEWS CARDIOLOGY, 16(6), 361-378. doi:10.1038/s41569-019-0155-8

Liu, X., Zhang, J., Zeigler, A., Nelson, A., Lindsey, M., & Saucerman, J. (2019). Network analysis reveals a distinct axis of macrophage activation in response to conflicting inflammatory cues. doi:10.1101/844464

Rikard, S. M., Athey, T. L., Nelson, A. R., Christiansen, S. L. M., Lee, J. -J., Holmes, J. W., . . . Saucerman, J. J. (2019). Multiscale Coupling of an Agent-Based Model of Tissue Fibrosis and a Logic-Based Model of Intracellular Signaling. FRONTIERS IN PHYSIOLOGY, 10. doi:10.3389/fphys.2019.01481

Woo, L. A., Tkachenko, S., Ding, M., Plowright, A. T., Engkvist, O., Andersson, H., . . . Saucerman, J. J. (2019). High-content phenotypic assay for proliferation of human iPSC-derived cardiomyocytes identifies L-type calcium channels as targets. JOURNAL OF MOLECULAR AND CELLULAR CARDIOLOGY, 127, 204-214. doi:10.1016/j.yjmcc.2018.12.015

Xu, P., Damschroder, D., Zhang, M., Ryall, K. A., Adler, P. N., Saucerman, J. J., . . . Yan, Z. (2019). Atg2, Atg9 and Atg18 in mitochondrial integrity, cardiac function and healthspan in Drosophila. JOURNAL OF MOLECULAR AND CELLULAR CARDIOLOGY, 127, 116-124. doi:10.1016/j.yjmcc.2018.12.006

Frank, D. U., Sutcliffe, M. D., & Saucerman, J. J. (2018). Network-based predictions of in vivo cardiac hypertrophy. JOURNAL OF MOLECULAR AND CELLULAR CARDIOLOGY, 121, 180-189. doi:10.1016/j.yjmcc.2018.07.243

Mouton, A. J., DeLeon-Pennell, K. Y., Gonzalez, O. J. R., Flynn, E. R., Freeman, T. C., Saucerman, J. J., . . . Lindsey, M. L. (2018). Mapping macrophage polarization over the myocardial infarction time continuum. BASIC RESEARCH IN CARDIOLOGY, 113(4). doi:10.1007/s00395-018-0686-x

Sutcliffe, M. D., Tan, P. M., Fernandez-Perez, A., Nam, Y. -J., Munshi, N. V., & Saucerman, J. J. (2018). High content analysis identifies unique morphological features of reprogrammed cardiomyocytes. SCIENTIFIC REPORTS, 8. doi:10.1038/s41598-018-19539-z

Santolini, M., Romay, M. C., Yukhtman, C. L., Rau, C. D., Ren, S., Saucerman, J. J., . . . Karma, A. (2018). A personalized, multiomics approach identifies genes involved in cardiac hypertrophy and heart failure. NPJ SYSTEMS BIOLOGY AND APPLICATIONS, 4. doi:10.1038/s41540-018-0046-3

Tan, P. M., Buchholz, K. S., Omens, J. H., McCulloch, A. D., & Saucerman, J. J. (2017). Predictive model identifies key network regulators of cardiomyocyte mechano-signaling. PLOS COMPUTATIONAL BIOLOGY, 13(11). doi:10.1371/journal.pcbi.1005854

Laker, R. C., Drake, J. C., Wilson, R. J., Lira, V. A., Lewellen, B. M., Ryall, K. A., . . . Yan, Z. (2017). Ampk phosphorylation of Ulk1 is required for targeting of mitochondria to lysosomes in exercise-induced mitophagy. NATURE COMMUNICATIONS, 8. doi:10.1038/s41467-017-00520-9

Shim, J. V., Chun, B., van Hasselt, J. G. C., Birtwistle, M. R., Saucerman, J. J., & Sobie, E. A. (2017). Mechanistic Systems Modeling to Improve Understanding and Prediction of Cardiotoxicity Caused by Targeted Cancer Therapeutics. FRONTIERS IN PHYSIOLOGY, 8. doi:10.3389/fphys.2017.00651

Janes, K. A., Chandran, P. L., Ford, R. M., Lazzara, M. J., Papin, J. A., Peirce, S. M., . . . Lauffenburger, D. A. (2017). An engineering design approach to systems biology. INTEGRATIVE BIOLOGY, 9(7), 574-583. doi:10.1039/c7ib00014f

Lindsey, M. L., Saucerman, J. J., & DeLeon-Pennell, K. Y. (2016). Knowledge gaps to understanding cardiac macrophage polarization following myocardial infarction. BIOCHIMICA ET BIOPHYSICA ACTA-MOLECULAR BASIS OF DISEASE, 1862(12), 2288-2292. doi:10.1016/j.bbadis.2016.05.013

Zeigler, A. C., Richardson, W. J., Holmes, J. W., & Saucerman, J. J. (2016). A computational model of cardiac fibroblast signaling predicts context-dependent drivers of myofibroblast differentiation. JOURNAL OF MOLECULAR AND CELLULAR CARDIOLOGY, 94, 72-81. doi:10.1016/j.yjmcc.2016.03.008

Zeigler, A. C., Richardson, W. J., Holmes, J. W., & Saucerman, J. J. (2016). Computational modeling of cardiac fibroblasts and fibrosis. JOURNAL OF MOLECULAR AND CELLULAR CARDIOLOGY, 93, 73-83. doi:10.1016/j.yjmcc.2015.11.020

Ryall, K. A., & Saucerman, J. J. (2015). Automated Microscopy of Cardiac Myocyte Hypertrophy: A Case Study on the Role of Intracellular α-Adrenergic Receptors. NUCLEAR G-PROTEIN COUPLED RECEPTORS: METHODS AND PROTOCOLS, 1234, 123-134. doi:10.1007/978-1-4939-1755-6_11

Amanfu, R. K., & Saucerman, J. J. (2014). Modeling the Effects of β₁-Adrenergic Receptor Blockers and Polymorphisms on Cardiac Myocyte Ca²⁺ Handling. MOLECULAR PHARMACOLOGY, 86(2), 222-230. doi:10.1124/mol.113.090951

Laker, R. C., Xu, P., Ryall, K. A., Sujkowski, A., Kenwood, B. M., Chain, K. H., . . . Yan, Z. (2014). A Novel MitoTimer Reporter Gene for Mitochondrial Content, Structure, Stress, and Damage in Vivo. JOURNAL OF BIOLOGICAL CHEMISTRY, 289(17), 12005-12015. doi:10.1074/jbc.M113.530527

Ryall, K. A., Bezzerides, V. J., Rosenzweig, A., & Saucerman, J. J. (2014). Phenotypic screen quantifying differential regulation of cardiac myocyte hypertrophy identifies CITED4 regulation of myocyte elongation. JOURNAL OF MOLECULAR AND CELLULAR CARDIOLOGY, 72, 74-84. doi:10.1016/j.yjmcc.2014.02.013

Saucerman, J. J., Greenwald, E. C., & Polanowska-Grabowska, R. (2014). Mechanisms of cyclic AMP compartmentation revealed by computational models. JOURNAL OF GENERAL PHYSIOLOGY, 143(1), 39-48. doi:10.1085/jgp.201311044

Greenwald, E. C., Redden, J. M., Dodge-Kafka, K. L., & Saucerman, J. J. (2014). Scaffold State Switching Amplifies, Accelerates, and Insulates Protein Kinase C Signaling. JOURNAL OF BIOLOGICAL CHEMISTRY, 289(4), 2353-2360. doi:10.1074/jbc.M113.497941

Kenwood, B. M., Weaver, J. L., Bajwa, A., Poon, I. K., Byrne, F. L., Murrow, B. A., . . . Hoehn, K. L. (2014). Identification of a novel mitochondria! uncoupler that does not depolarize the plasma membrane. MOLECULAR METABOLISM, 3(2), 114-123. doi:10.1016/j.molmet.2013.11.005

Yang, J. H., Polanowska-Grabowska, R. K., Smith, J. S., Shields, C. W., & Saucerman, J. J. (2014). PKA catalytic subunit compartmentation regulates contractile and hypertrophic responses to β-adrenergic signaling. JOURNAL OF MOLECULAR AND CELLULAR CARDIOLOGY, 66, 83-93. doi:10.1016/j.yjmcc.2013.11.001

Saucerman, J. J. (2013). Modeling Mitochondrial ROS: A Great Balancing Act. BIOPHYSICAL JOURNAL, 105(6), 1287-1288. doi:10.1016/j.bpj.2013.08.013

Greenwald, E. C., Polanowska-Grabowska, R. K., & Saucerman, J. J. (2014). Integrating Fluorescent Biosensor Data Using Computational Models. FLUORESCENT PROTEIN-BASED BIOSENSORS: METHODS AND PROTOCOLS, 1071, 227-248. doi:10.1007/978-1-62703-622-1_18

Sample, V., DiPilato, L. M., Yang, J. H., Ni, Q., Saucerman, J. J., & Zhang, J. (2013). Regulation of nuclear PKA revealed by spatiotemporal manipulation of cyclic AMP (vol 8, pg 375, 2012). NATURE CHEMICAL BIOLOGY, 9(6), 406. doi:10.1038/nchembio0613-406b

Saucerman, J. J. (2013). Modeling Mitochondrial ROS: A Great Balancing Act (vol 105, pg 1287, 2013). BIOPHYSICAL JOURNAL, 105(11), 2606. doi:10.1016/j.bpj.2013.11.001

Ryall, K. A., Holland, D. O., Delaney, K. A., Kraeutler, M. J., Parker, A. J., & Saucerman, J. J. (2012). Network Reconstruction and Systems Analysis of Cardiac Myocyte Hypertrophy Signaling. JOURNAL OF BIOLOGICAL CHEMISTRY, 287(50), 42259-42268. doi:10.1074/jbc.M112.382937

Cui, W. -Y., Zhao, S., Polanowska-Grabowska, R., Wang, J., Wei, J., Dash, B., . . . Li, M. D. (2013). Identification and Characterization of Poly(I:C)-induced Molecular Responses Attenuated by Nicotine in Mouse Macrophages. MOLECULAR PHARMACOLOGY, 83(1), 61-72. doi:10.1124/mol.112.081497

Ryall, K. A., & Saucerman, J. J. (2012). Automated imaging reveals a concentration dependent delay in reversibility of cardiac myocyte hypertrophy. JOURNAL OF MOLECULAR AND CELLULAR CARDIOLOGY, 53(2), 282-290. doi:10.1016/j.yjmcc.2012.04.016

Sample, V., DiPilato, L. M., Yang, J. H., Ni, Q., Saucerman, J. J., & Zhang, J. (2012). Regulation of nuclear PKA revealed by spatiotemporal manipulation of cyclic AMP. NATURE CHEMICAL BIOLOGY, 8(4), 375-382. doi:10.1038/NCHEMBIO.799

Raynor, L. L., Saucerman, J. J., Akinola, M. O., Lake, D. E., Moorman, J. R., & Fairchild, K. D. (2012). Cytokine screening identifies NICU patients with Gram-negative bacteremia. PEDIATRIC RESEARCH, 71(3), 261-266. doi:10.1038/pr.2011.45

Yang, J. H., & Saucerman, J. J. (2012). Phospholemman is a negative feed-forward regulator of Ca²⁺ in β-adrenergic signaling, accelerating β-adrenergic inotropy. JOURNAL OF MOLECULAR AND CELLULAR CARDIOLOGY, 52(5), 1048-1055. doi:10.1016/j.yjmcc.2011.12.015

Cui, W. Y., Chang, S. L., Polanowska-Grabowska, R., Saucerman, J. J., & Li, M. D. (2012). Nicotine Suppresses TLR3-mediated Inflammation Through a Calcium Signaling Mechanism. JOURNAL OF NEUROIMMUNE PHARMACOLOGY, 7, S35. Retrieved from https://www.webofscience.com/

Bass, G. T., Ryall, K. A., Katikapalli, A., Taylor, B. E., Dang, S. T., Acton, S. T., & Saucerman, J. J. (2012). Automated image analysis identifies signaling pathways regulating distinct signatures of cardiac myocyte hypertrophy. JOURNAL OF MOLECULAR AND CELLULAR CARDIOLOGY, 52(5), 923-930. doi:10.1016/j.yjmcc.2011.11.009

Greenwald, E. C., & Saucerman, J. J. (2011). Bigger, Better, Faster: Principles and Models of AKAP Anchoring Protein Signaling. JOURNAL OF CARDIOVASCULAR PHARMACOLOGY, 58(5), 462-469. doi:10.1097/FJC.0b013e31822001e3

Saucerman, J. J. (2012). Cardiac biexcitability: Two ways to catch a wave. HEART RHYTHM, 9(1), 123-124. doi:10.1016/j.hrthm.2011.09.001

Soltis, A. R., & Saucerman, J. J. (2011). Robustness portraits of diverse biological networks conserved despite order-of-magnitude parameter uncertainty. BIOINFORMATICS, 27(20), 2888-2894. doi:10.1093/bioinformatics/btr496

Saucerman, J. J., & Bers, D. M. (2012). Calmodulin binding proteins provide domains of local Ca²⁺ signaling in cardiac myocytes. JOURNAL OF MOLECULAR AND CELLULAR CARDIOLOGY, 52(2), 312-316. doi:10.1016/j.yjmcc.2011.06.005

Yang, J. H., & Saucerman, J. J. (2011). Computational Models Reduce Complexity and Accelerate Insight Into Cardiac Signaling Networks. CIRCULATION RESEARCH, 108(1), 85-97. doi:10.1161/CIRCRESAHA.110.223602

Soltis, A. R., & Saucerman, J. J. (2011). Robustness Portraits of Diverse Biological Networks Conserved Despite Order-Of-Magnitude Parameter Variation. BIOPHYSICAL JOURNAL, 100(3), 165. Retrieved from https://www.webofscience.com/

Polanowska-Grabowska, R., Park, S. R., & Saucerman, J. J. (2011). Validating a Model of Nitric Oxide-Ca²⁺ Crosstalk in Cardiac Myocytes. BIOPHYSICAL JOURNAL, 100(3), 82. Retrieved from https://www.webofscience.com/

Dang, S. T., & Saucerman, J. J. (2011). Netflux: Biological Network Modeling for Biologists and Students. BIOPHYSICAL JOURNAL, 100(3), 324-325. Retrieved from https://www.webofscience.com/

Amanfu, R. K., Muller, J. B., & Saucerman, J. J. (2011). Automated Image Analysis of Cardiac Myocyte Ca²⁺ Dynamics. 2011 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 4661-4664. Retrieved from https://www.webofscience.com/

Amanfu, R. K., & Saucerman, J. J. (2011). Cardiac models in drug discovery and development: a review.. Critical reviews in biomedical engineering, 39(5), 379-395. doi:10.1615/critrevbiomedeng.v39.i5.30

Raynor, L. L., Saucerman, J. J., Akinola, M. O., Lake, D. E., Moorman, J. R., & Fairchild, K. D. (2011). CYTOKINE SCORE IDENTIFIES NICU PATIENTS WITH GRAM-NEGATIVE BACTEREMIA. PEDIATRIC RESEARCH, 70, 688. doi:10.1038/pr.2011.913

Holland, D. O., Krainak, N. C., & Saucerman, J. J. (2011). Graphical Approach to Model Reduction for Nonlinear Biochemical Networks. PLOS ONE, 6(8). doi:10.1371/journal.pone.0023795

Haggart, C. R., Bartell, J. A., Saucerman, J. J., & Papin, J. A. (2011). WHOLE-GENOME METABOLIC NETWORK RECONSTRUCTION AND CONSTRAINT-BASED MODELING. METHODS IN ENZYMOLOGY, VOL 500, 500, 411-433. doi:10.1016/B978-0-12-385118-5.00021-9

Benedict, K. F., Mac Gabhann, F., Amanfu, R. K., Chavali, A. K., Gianchandani, E. P., Glaw, L. S., . . . Skalak, T. C. (2011). Systems Analysis of Small Signaling Modules Relevant to Eight Human Diseases. ANNALS OF BIOMEDICAL ENGINEERING, 39(2), 621-635. doi:10.1007/s10439-010-0208-y

Kraeutler, M. J., Soltis, A. R., & Saucerman, J. J. (2010). Modeling cardiac β-adrenergic signaling with normalized-Hill differential equations: comparison with a biochemical model. BMC SYSTEMS BIOLOGY, 4. doi:10.1186/1752-0509-4-157

Soltis, A. R., & Saucerman, J. J. (2010). Synergy between CaMKII Substrates and β-Adrenergic Signaling in Regulation of Cardiac Myocyte Ca²⁺ Handling. BIOPHYSICAL JOURNAL, 99(7), 2038-2047. doi:10.1016/j.bpj.2010.08.016