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1. Watson, Shana R., Liu, Piaomu, Pea, Edsel A., Sutton, Michael A., Eberth, John F., Lessner, Susan M., (2016), "Comparison of Aortic Collagen Fiber Angle Distribution in Mouse Models of Atherosclerosis Using Second-Harmonic Generation (SHG) Microscopy", Microscopy and Microanalysis, 22, 01: pg: 55--62, 1431-9276, (DOI: 10.1017/S1431927615015585).
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2. Sacerdoti, F. D. and Katz, M. J. and Papadopoulos, P. M., (2016), "411 on Scalable Password Service", HPDC-14. Proceedings. 14th IEEE International Symposium on High Performance Distributed Computing, 2005., HPDC-14. Proceedings. 14th IEEE International Symposium on High Performance Distributed Computing, 2005., January 2005: pg: 211--221, 0-7803-9037-7, (DOI: 10.1109/HPDC.2005.1520963).
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3. Krishnamurthy, Adarsh and Coppola, Benjamin and Tangney, Jared and Kerckhoffs, Roy C. P. and Omens, Jeffrey H. and McCulloch, Andrew D., (2016), "A Microstructurally Based Multi-Scale Constitutive Model of Active Myocardial Mechanics": pg: 439--460, (DOI: 10.1007/978-1-4899-7630-7_22).
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4. Kadam, Pratima Datta, Chuan, Han How, (2016), "Erratum to: Rectocutaneous fistula with transmigration of the suture: a rare delayed complication of vault fixation with the sacrospinous ligament.", International urogynecology journal, 27, 3: pg: 505, 1433-3023, (DOI: 10.1007/s00192-016-2952-5).
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5. Zhou S., Sun H., Cheng L. T., Dzubiella J., Li B., McCammon J. A., (2016), "Stochastic level-set variational implicit-solvent approach to solute-solvent interfacial fluctuations", J Chem Phys, 145, 5: pg: 054114, (DOI: 10.1063/1.4959971).
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6. Zhang, Y. H. and Barocas, V. H. and Berceli, S. A. and Clancy, C. E. and Eckmann, D. M. and Garbey, M. and Kassab, G. S. and Lochner, D. R. and Mcculloch, A. D. and Tran-Son-Tay, R. and Trayanova, N. A., (2016), "Multi-scale Modeling of the Cardiovascular System: Disease Development, Progression, and Clinical Intervention", Ann Biomed Eng, 44, 9: pg: 2642-60, (DOI: 10.1007/s10439-016-1628-0).
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7. Yang, P. C. and Boras, B. W. and Jeng, M. T. and Docken, S. S. and Lewis, T. J. and McCulloch, A. D. and Harvey, R. D. and Clancy, C. E., (2016), "A Computational Modeling and Simulation Approach to Investigate Mechanisms of Subcellular cAMP Compartmentation", PLoS Comput Biol, 12, 7: pg: e1005005, (DOI: 10.1371/journal.pcbi.1005005).
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8. Yang, L. and Skjevik, A. A. and Han Du, W. G. and Noodleman, L. and Walker, R. C. and Gotz, A. W., (2016), "Data for molecular dynamics simulations of B-type cytochrome c oxidase with the Amber force field", Data Brief, 8: pg: 1209-14, (DOI: 10.1016/j.dib.2016.07.043).
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9. Yang, L. and Skjevik, A. A. and Han Du, W. G. and Noodleman, L. and Walker, R. C. and Gotz, A. W., (2016), "Water exit pathways and proton pumping mechanism in B-type cytochrome c oxidase from molecular dynamics simulations", Biochim Biophys Acta, 1857, 9: pg: 1594-606, (DOI: 10.1016/j.bbabio.2016.06.005).
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10. Wang, N. and McCammon, J. A., (2016), "Substrate channeling between the human dihydrofolate reductase and thymidylate synthase", Protein Science, 25, 1: pg: 79-86, (DOI: 10.1002/pro.2720).
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11. Wagner, J. R. and Lee, C. T. and Durrant, J. D. and Malmstrom, R. D. and Feher, V. A. and Amaro, R. E., (2016), "Emerging Computational Methods for the Rational Discovery of Allosteric Drugs", Chem Rev, 116, 11: pg: 6370-90, (DOI: 10.1021/acs.chemrev.5b00631).
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12. Votapka, L. W. and Lee, C. T. and Amaro, R. E., (2016), "Two Relations to Estimate Membrane Permeability Using Milestoning", J Phys Chem B, 120, 33: pg: 8606-16, (DOI: 10.1021/acs.jpcb.6b02814).
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13. Villongco, C. T. and Krummen, D. E. and Omens, J. H. and McCulloch, A. D., (2016), "Non-invasive, model-based measures of ventricular electrical dyssynchrony for predicting CRT outcomes", Europace, 18, suppl 4: pg: iv104-iv112, (DOI: 10.1093/europace/euw356).
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14. Tveito, A. and Lines, G. T. and Edwards, A. G. and McCulloch, A., (2016), "Computing rates of Markov models of voltage-gated ion channels by inverting partial differential equations governing the probability density functions of the conducting and non-conducting states", Math Biosci, 277: pg: 126-35, (DOI: 10.1016/j.mbs.2016.04.011).
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15. Swift, R. V. and Jusoh, S. A. and Offutt, T. L. and Li, E. S. and Amaro, R. E., (2016), "Knowledge-Based Methods To Train and Optimize Virtual Screening Ensembles", J Chem Inf Model, 56, 5: pg: 830-42, (DOI: 10.1021/acs.jcim.5b00684).
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16. Soman, S. and Keatinge, M. and Moein, M. and Da Costa, M. and Mortiboys, H. and Skupin, A. and Sugunan, S. and Bazala, M. and Kuznicki, J. and Bandmann, O., (2016), "Inhibition of the mitochondrial calcium uniporter rescues dopaminergic neurons in pink1-/- zebrafish", Eur J Neurosci: (DOI: 10.1111/ejn.13473).
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17. Shi, K. and Carpenter, M. A. and Banerjee, S. and Shaban, N. M. and Kurahashi, K. and Salamango, D. J. and McCann, J. L. and Starrett, G. J. and Duffy, J. V. and Demir, O. and Amaro, R. E. and Harki, D. A. and Harris, R. S. and Aihara, H., (2016), "Structural basis for targeted DNA cytosine deamination and mutagenesis by APOBEC3A and APOBEC3B", Nat Struct Mol Biol: (DOI: 10.1038/nsmb.3344).
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18. Schilling, J. M. and Horikawa, Y. T. and Zemljic-Harpf, A. E. and Vincent, K. P. and Tyan, L. and Yu, J. K. and McCulloch, A. D. and Balijepalli, R. C. and Patel, H. H. and Roth, D. M., (2016), "Electrophysiology and metabolism of caveolin-3-overexpressing mice", Basic Res Cardiol, 111, 3: pg: 28, (DOI: 10.1007/s00395-016-0542-9).
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19. Schiffer, J. M. and Malmstrom, R. D. and Parnell, J. and Ramirez-Sarmiento, C. and Reyes, J. and Amaro, R. E. and Komives, E. A., (2016), "Model of the Ankyrin and SOCS Box Protein, ASB9, E3 Ligase Reveals a Mechanism for Dynamic Ubiquitin Transfer", Structure, 24, 8: pg: 1248-56, (DOI: 10.1016/j.str.2016.05.016).
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20. Schiffer, J. M. and Feher, V. A. and Malmstrom, R. D. and Sida, R. and Amaro, R. E., (2016), "Capturing Invisible Motions in the Transition from Ground to Rare Excited States of T4 Lysozyme L99A", Biophys J, 111, 8: pg: 1631-1640, (DOI: 10.1016/j.bpj.2016.08.041).
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21. Ravindranath, P. A. and Sanner, M. F., (2016), "AutoSite: an automated approach for pseudo-ligands prediction-from ligand-binding sites identification to predicting key ligand atoms", Bioinformatics, 32, 20: pg: 3142-3149, (DOI: 10.1093/bioinformatics/btw367).
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22. Rajappa-Titu, L. and Suematsu, T. and Munoz-Tello, P. and Long, M. and Demir, O. and Cheng, K. J. and Stagno, J. R. and Luecke, H. and Amaro, R. E. and Aphasizheva, I. and Aphasizhev, R. and Thore, S., (2016), "RNA Editing TUTase 1: structural foundation of substrate recognition, complex interactions and drug targeting", Nucleic Acids Res, 44, 22: pg: 10862-10878, (DOI: 10.1093/nar/gkw917).
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23. Purvine, E. and Monson, K. and Jurrus, E. and Star, K. and Baker, N. A., (2016), "Energy Minimization of Discrete Protein Titration State Models Using Graph Theory", J Phys Chem B, 120, 33: pg: 8354-60, (DOI: 10.1021/acs.jpcb.6b02059).
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24. Purawat, S. and Cowart, C. and Amaro, R. E. and Altintas, I., (2016), "Biomedical Big Data Training Collaborative (BBDTC): An effort to bridge the talent gap in biomedical science and research", Procedia Comput Sci, 80: pg: 1791-1800, (DOI: 10.1016/j.procs.2016.05.454).
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25. Palermo, G. and Miao, Y. and Walker, R. C. and Jinek, M. and McCammon, J. A., (2016), "Striking Plasticity of CRISPR-Cas9 and Key Role of Non-target DNA, as Revealed by Molecular Simulations", ACS Cent Sci, 2, 10: pg: 756-763, (DOI: 10.1021/acscentsci.6b00218).
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26. Ottilie, S. and Goldgof, G. M. and Calvet, C. M. and Jennings, G. K. and LaMonte, G. and Schenken, J. and Vigil, E. and Kumar, P. and McCall, L. I. and Lopes, E. S. and Gunawan, F. and Yang, J. and Suzuki, Y. and Siqueira-Neto, J. L. and McKerrow, J. H. and Amaro, R. E. and Podust, L. M. and Durrant, J. D. and Winzeler, E. A., (2016), "Rapid Chagas Disease Drug Target Discovery Using Directed Evolution in Drug-Sensitive Yeast", ACS Chem Biol: (DOI: 10.1021/acschembio.6b01037).
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27. Offutt, T. L. and Swift, R. V. and Amaro, R. E., (2016), "Enhancing Virtual Screening Performance of Protein Kinases with Molecular Dynamics Simulations", J Chem Inf Model: (DOI: 10.1021/acs.jcim.6b00261).
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28. Muzic, Mathieu Le and Mindek, Peter and Sorger, Johannes and Autin, Ludovic and Goodsell, David and Viola, Ivan, (2016), "Visibility Equalizer: Cutaway Visualization of Mesoscopic Biological Models", Computer Graphics Forum, 35: pg: --
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29. Mouchlis, V. D. and Morisseau, C. and Hammock, B. D. and Li, S. and McCammon, J. A. and Dennis, E. A., (2016), "Computer-aided drug design guided by hydrogen/deuterium exchange mass spectrometry: A powerful combination for the development of potent and selective inhibitors of Group VIA calcium-independent phospholipase A2", Bioorg Med Chem, 24, 20: pg: 4801-4811, (DOI: 10.1016/j.bmc.2016.05.009).
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30. Mouchlis, V. D. and Limnios, D. and Kokotou, M. G. and Barbayianni, E. and Kokotos, G. and McCammon, J. A. and Dennis, E. A., (2016), "Development of Potent and Selective Inhibitors for Group VIA Calcium-Independent Phospholipase A2 Guided by Molecular Dynamics and Structure-Activity Relationships", J Med Chem, 59, 9: pg: 4403-14, (DOI: 10.1021/acs.jmedchem.6b00377).
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31. Mohan, R. R. and Huber, G. A. and Morikis, D., (2016), "Electrostatic Steering Accelerates C3d:CR2 Association", J Phys Chem B, 120, 33: pg: 8416-23, (DOI: 10.1021/acs.jpcb.6b02095).
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32. Miao, Y. and McCammon, J. A., (2016), "Graded activation and free energy landscapes of a muscarinic G-protein-coupled receptor", Proc Natl Acad Sci U S A, 113, 43: pg: 12162-12167, (DOI: 10.1073/pnas.1614538113).
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33. Miao, Y. and McCammon, J. A., (2016), "G-protein coupled receptors: advances in simulation and drug discovery", Curr Opin Struct Biol, 41: pg: 83-89, (DOI: 10.1016/j.sbi.2016.06.008).
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34. Miao, Y. and Goldfeld, D. A. and Moo, E. V. and Sexton, P. M. and Christopoulos, A. and McCammon, J. A. and Valant, C., (2016), "Accelerated structure-based design of chemically diverse allosteric modulators of a muscarinic G protein-coupled receptor", Proc Natl Acad Sci U S A, 113, 38: pg: E5675-84, (DOI: 10.1073/pnas.1612353113).
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35. Miao, Y. and Baudry, J. and Smith, J. C. and McCammon, J. A., (2016), "General trends of dihedral conformational transitions in a globular protein", Proteins, 84, 4: pg: 501-14, (DOI: 10.1002/prot.24996).
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36. McCulloch, A. D., (2016), "Systems Biophysics: Multiscale Biophysical Modeling of Organ Systems", Biophys J, 110, 5: pg: 1023-7, (DOI: 10.1016/j.bpj.2016.02.007).
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37. Lee, C. T. and Comer, J. and Herndon, C. and Leung, N. and Pavlova, A. and Swift, R. V. and Tung, C. and Rowley, C. N. and Amaro, R. E. and Chipot, C. and Wang, Y. and Gumbart, J. C., (2016), "Simulation-Based Approaches for Determining Membrane Permeability of Small Compounds", J Chem Inf Model, 56, 4: pg: 721-33, (DOI: 10.1021/acs.jcim.6b00022).
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38. Krishnamurthy, A. and Gonzales, M. J. and Sturgeon, G. and Segars, W. P. and McCulloch, A. D., (2016), "Biomechanics Simulations Using Cubic Hermite Meshes with Extraordinary Nodes for Isogeometric Cardiac Modeling", Comput Aided Geom Des, 43: pg: 27-38, (DOI: 10.1016/j.cagd.2016.02.016).
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39. Kim, M. O. and McCammon, J. A., (2016), "Computation of pH-dependent binding free energies", Biopolymers, 105, 1: pg: 43-9, (DOI: 10.1002/bip.22702).
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40. Im, W. and Liang, J. and Olson, A. and Zhou, H. X. and Vajda, S. and Vakser, I. A., (2016), "Challenges in structural approaches to cell modeling", J Mol Biol, 428, 15: pg: 2943-64, (DOI: 10.1016/j.jmb.2016.05.024).
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41. Huber, G. A. and Miao, Y. and Zhou, S. and Li, B. and McCammon, J. A., (2016), "Hybrid finite element and Brownian dynamics method for charged particles", J Chem Phys, 144, 16: pg: 164107, (DOI: 10.1063/1.4947086).
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42. Huang, Y. M. and Miao, Y. and Munguia, J. and Lin, L. and Nizet, V. and McCammon, J. A., (2016), "Molecular dynamic study of MlaC protein in Gram-negative bacteria: conformational flexibility, solvent effect and protein-phospholipid binding", Protein Sci, 25, 8: pg: 1430-7, (DOI: 10.1002/pro.2939).
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43. Gorska, A. and Markowska-Zagrajek, A. and Rownicki, M. and Trylska, J., (2016), "Scanning of 16S Ribosomal RNA for Peptide Nucleic Acid Targets", J Phys Chem B, 120, 33: pg: 8369-78, (DOI: 10.1021/acs.jpcb.6b02081).
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44. Goldgof, G. M. and Durrant, J. D. and Ottilie, S. and Vigil, E. and Allen, K. E. and Gunawan, F. and Kostylev, M. and Henderson, K. A. and Yang, J. and Schenken, J. and LaMonte, G. M. and Manary, M. J. and Murao, A. and Nachon, M. and Stanhope, R. and Prescott, M. and McNamara, C. W. and Slayman, C. W. and Amaro, R. E. and Suzuki, Y. and Winzeler, E. A., (2016), "Comparative chemical genomics reveal that the spiroindolone antimalarial KAE609 (Cipargamin) is a P-type ATPase inhibitor", Sci Rep, 6: pg: 27806, (DOI: 10.1038/srep27806).
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45. Gathiaka, S. and Liu, S. and Chiu, M. and Yang, H. and Stuckey, J. A. and Kang, Y. N. and Delproposto, J. and Kubish, G. and Dunbar, J. B., Jr. and Carlson, H. A. and Burley, S. K. and Walters, W. P. and Amaro, R. E. and Feher, V. A. and Gilson, M. K., (2016), "D3R grand challenge 2015: Evaluation of protein-ligand pose and affinity predictions", J Comput Aided Mol Des, 30, 9: pg: 651-668, (DOI: 10.1007/s10822-016-9946-8).
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46. Farrar, Genevieve and Suinesiaputra, Avan and Gilbert, Kathleen and Perry, James C. and Hegde, Sanjeet and Marsden, Alison and Young, Alistair A. and Omens, Jeffrey H. and McCulloch, Andrew D., (2016), "Atlas-based ventricular shape analysis for understanding congenital heart disease", Progress in Pediatric Cardiology, 43: pg: 61-69, (DOI: http://dx.doi.org/10.1016/j.ppedcard.2016.07.010).
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47. Durrant, J. D. and Bush, R. M. and Amaro, R. E., (2016), "Microsecond Molecular Dynamics Simulations of Influenza Neuraminidase Suggest a Mechanism for the Increased Virulence of Stalk-Deletion Mutants", J Phys Chem B, 120, 33: pg: 8590-9, (DOI: 10.1021/acs.jpcb.6b02655).
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48. Demir, O. and Ieong, P. U. and Amaro, R. E., (2016), "Full-length p53 tetramer bound to DNA and its quaternary dynamics", Oncogene: (DOI: 10.1038/onc.2016.321).
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49. Crawl, Daniel and Singh, Alok and Altintas, Ilkay, (2016), "Kepler WebView: A Lightweight, Portable Framework for Constructing Real-time Web Interfaces of Scientific Workflows", Procedia Computer Science, 80: pg: 673-679, (DOI: http://dx.doi.org/10.1016/j.procs.2016.05.361).
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50. Cheng, Y. and Lindert, S. and Oxenford, L. and Tu, A. Y. and McCulloch, A. D. and Regnier, M., (2016), "Effects of Cardiac Troponin I Mutation P83S on Contractile Properties and the Modulation by PKA-Mediated Phosphorylation", J Phys Chem B, 120, 33: pg: 8238-53, (DOI: 10.1021/acs.jpcb.6b01859).
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