Relevant bibliographies by topics / Protein simulation

Academic literature on the topic 'Protein simulation'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Protein simulation"

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Daggett, Valerie. "Protein Folding−Simulation." Chemical Reviews 106, no. 5 (May 2006): 1898–916. http://dx.doi.org/10.1021/cr0404242.

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Velesinović, Aleksandar, and Goran Nikolić. "Protein-protein interaction networks and protein-ligand docking: Contemporary insights and future perspectives." Acta Facultatis Medicae Naissensis 38, no. 1 (2021): 5–17. http://dx.doi.org/10.5937/afmnai38-28322.

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Traditional research means, such as in vitro and in vivo models, have consistently been used by scientists to test hypotheses in biochemistry. Computational (in silico) methods have been increasingly devised and applied to testing and hypothesis development in biochemistry over the last decade. The aim of in silico methods is to analyze the quantitative aspects of scientific (big) data, whether these are stored in databases for large data or generated with the use of sophisticated modeling and simulation tools; to gain a fundamental understanding of numerous biochemical processes related, in particular, to large biological macromolecules by applying computational means to big biological data sets, and by computing biological system behavior. Computational methods used in biochemistry studies include proteomics-based bioinformatics, genome-wide mapping of protein-DNA interaction, as well as high-throughput mapping of the protein-protein interaction networks. Some of the vastly used molecular modeling and simulation techniques are Monte Carlo and Langevin (stochastic, Brownian) dynamics, statistical thermodynamics, molecular dynamics, continuum electrostatics, protein-ligand docking, protein-ligand affinity calculations, protein modeling techniques, and the protein folding process and enzyme action computer simulation. This paper presents a short review of two important methods used in the studies of biochemistry - protein-ligand docking and the prediction of protein-protein interaction networks.
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Elcock, Adrian H., David Sept, and J. Andrew McCammon. "Computer Simulation of Protein−Protein Interactions." Journal of Physical Chemistry B 105, no. 8 (March 2001): 1504–18. http://dx.doi.org/10.1021/jp003602d.

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Yun, R. H., and Jan Hermans. "Conformation equilibria of valine studies by dynamics simulation." "Protein Engineering, Design and Selection" 4, no. 7 (1991): 761–66. http://dx.doi.org/10.1093/protein/4.7.761.

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Arnold, Gregory E., and Rick L. Ornstein. "A molecular dynamics simulation of bacteriophage T4 lysozyme." "Protein Engineering, Design and Selection" 5, no. 7 (1992): 703–14. http://dx.doi.org/10.1093/protein/5.7.703.

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van Gunsteren, W. F. "The role of computer simulation techniques in protein engineering." "Protein Engineering, Design and Selection" 2, no. 1 (1988): 5–13. http://dx.doi.org/10.1093/protein/2.1.5.

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Cherfils, Jacqueline, Stéphane Duquerroy, and Joël Janin. "Protein-protein recognition analyzed by docking simulation." Proteins: Structure, Function, and Genetics 11, no. 4 (December 1991): 271–80. http://dx.doi.org/10.1002/prot.340110406.

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Helms, Volkhard, Mazen Ahmad, Alexander Spaar, and Wei Gu. "Computer Simulation of Protein-Protein Association Processes." Biophysical Journal 96, no. 3 (February 2009): 75a. http://dx.doi.org/10.1016/j.bpj.2008.12.288.

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Komeiji, Yuto, Masami Uebayasi, Jun-ichiro Someya, and Ichiro Yamato. "Molecular dynamics simulation of trp-aporepressor in a solvent." "Protein Engineering, Design and Selection" 4, no. 8 (1991): 871–75. http://dx.doi.org/10.1093/protein/4.8.871.

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KHAIRUDIN, NURUL BAHIYAH AHMAD, and HABIBAH A. WAHAB. "PROTEIN STRUCTURE PREDICTION USING GAS PHASE MOLECULAR DYNAMICS SIMULATION: EOTAXIN-3 CYTOKINE AS A CASE STUDY." International Journal of Modern Physics: Conference Series 09 (January 2012): 193–98. http://dx.doi.org/10.1142/s2010194512005259.

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In the current work, the structure of the enzyme CC chemokine eotaxin-3 (1G2S) was chosen as a case study to investigate the effects of gas phase on the predicted protein conformation using molecular dynamics simulation. Generally, simulating proteins in the gas phase tend to suffer from various drawbacks, among which excessive numbers of protein-protein hydrogen bonds. However, current results showed that the effects of gas phase simulation on 1G2S did not amplify the protein-protein hydrogen bonds. It was also found that some of the hydrogen bonds which were crucial in maintaining the secondary structural elements were disrupted. The predicted models showed high values of RMSD, 11.5 Å and 13.5 Å for both vacuum and explicit solvent simulations, respectively, indicating that the conformers were very much different from the native conformation. Even though the RMSD value for the in vacuo model was slightly lower, it somehow suffered from lower fraction of native contacts, poor hydrogen bonding networks and fewer occurrences of secondary structural elements compared to the solvated model. This finding supports the notion that water plays a dominant role in guiding the protein to fold along the correct path.
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Dissertations / Theses on the topic "Protein simulation"

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Park, Changmoon Goddard William A. "Protein design and simulation Part I. Protein design. Part II. Protein simulation /." Diss., Pasadena, Calif. : California Institute of Technology, 1993. http://resolver.caltech.edu/CaltechTHESIS:11112009-114142428.

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Thesis (Ph. D.)--California Institute of Technology, 1993. UM #93-25,374.
Advisor names found in the Acknowledgements pages of the thesis. Title from home page. Viewed 01/15/2010. Includes bibliographical references.
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Flöck, Dagmar. "Protein-protein docking and Brownian dynamics simulation of electron transfer proteins." [S.l. : s.n.], 2003. http://deposit.ddb.de/cgi-bin/dokserv?idn=969418736.

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Baskaran, Preetisri. "Computer simulation of protein superabsorbents." Thesis, Högskolan i Borås, Institutionen Ingenjörshögskolan, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:hb:diva-20927.

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The aim of this project is to develop superabsorbents from proteins in our case it is azygomycetes fungus, where the process of this fungus is studied experimentally in Universityof Borås. As a result of this experiment by-products of protein are produced and this project isabout the study to make use of such proteins as superabsorbing materials.The water absorbing capacity is computationally studied using Gibbs ensemble Monte Carlo(GEMC) simulations to determine the absorbing properties and to effectively improve theabsorbing capacity by using specific treatments, where this project focuses in using mesoscaleforce fields such as the MARTINI force field instead of atomistic force fields which wereused in studying the structure of the superabsorbents.For this purpose, the program code GEMMS is modified to make it read the desirable fileformats in order to perform the simulations. C++ is used here to code the program to read theGROMACS topology file (.top) for MARTINI force field instead of, as currently reading theatom type file (.atp) and the residue type file (.rtp) for the AMBER99 atomistic force field.
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Mellor, Brett Lee. "Liquid Dielectric Spectroscopy and Protein Simulation." BYU ScholarsArchive, 2012. https://scholarsarchive.byu.edu/etd/3661.

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Protein electrical properties have been studied using dielectric relaxation measurements throughout the past century. These measurements have advanced both the theory and practice of liquid dielectric spectroscopy and have contributed to understanding of protein structure and function. In this dissertation, the relationship between permittivity measurements and underlying molecular mechanisms is explored. Also presented is a method to take molecular structures from the Protein Data Bank and subsequently estimate the charge distribution and dielectric relaxation properties of the proteins in solution. This process enables screening of target compounds for analysis by dielectric spectroscopy as well as better interpretation of protein relaxation data. For charge estimation, the shifted pKa values for amino acid residues are calculated using Poisson-Boltzmann solutions of the protein electrostatics over varying pH conditions. The estimated internal permittivity and estimated dipole moments through shifted pKa values are then calculated. Molecular dynamics simulations are additionally used to refine and approximate the solution-state conformation of the proteins. These calculations and simulations are verified with laboratory experiments over a large pH and frequency range (40 Hz to 110 MHz). The measurement apparatus is improved over previous designs by controlling temperature and limiting the electrode polarization effect through electrode surface preparation and adjustment of the cell's physical dimensions. The techniques developed in this dissertation can be used to analyze a wide variety of molecular phenomena experimentally and computationally, as demonstrated through various interactions amongst avidin, biotin, biotin-labeled and unlabeled bovine serum albumin, beta-lactoglobulin, and hen-lysozyme.
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Naser, Md Abu. "Molecular dynamics simulation of protein adsorption." Thesis, Heriot-Watt University, 2008. http://hdl.handle.net/10399/2187.

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Mitchell, Felicity. "Modelling protein flexibility using molecular simulation methods." Thesis, University of Manchester, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.525167.

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Dantas, Gautam. "In silico protein evolution by intelligent design : creating new and improved protein structures /." Thesis, Connect to this title online; UW restricted, 2005. http://hdl.handle.net/1773/9236.

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Badcoe, Ian Geoffrey. "Computer studies of protein folding." Thesis, University of Bristol, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.385585.

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Zhang, Wei. "Computational simulation of biological systems studies on protein folding and protein structure prediction /." Access to citation, abstract and download form provided by ProQuest Information and Learning Company; downloadable PDF file 2.84Mb, 184 p, 2005. http://wwwlib.umi.com/dissertations/fullcit/3181881.

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Carpenter, Timothy S. "Simulation studies of the influenza M2 channel protein." Thesis, University of Oxford, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.504314.

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Books on the topic "Protein simulation"

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Fraga, Serafin. Computer simulations of protein structures and interactions. Berlin: Springer-Verlag, 1995.

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Protein architecture: A practical approach. Oxford [England]: IRL Press, 1991.

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Filizola, Marta, ed. G Protein-Coupled Receptors - Modeling and Simulation. Dordrecht: Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-007-7423-0.

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Protein modelling with bioinformatics and biophysics. New York: Springer, 2006.

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Zimmermann, Karl-Heinz. An introduction to protein informatics. Dordrecht: Springer-Science+Business Media, B.V., 2003.

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Zimmermann, Karl-Heinz. An introduction to protein informatics. Boston: Kluwer Academic Publishers, 2003.

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Zimmermann, Karl-Heinz. An introduction to protein informatics. Boston: Kluwer Academic Publishers, 2003.

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Livesay, Dennis R. Protein dynamics: Methods and protocols. New York: Humana Press, 2013.

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Rangwala, Huzefa, G. Karypis, and G. Karypis. Introduction to protein structure prediction: Methods and algorithms. Hoboken, N.J: Wiley, 2010.

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Dimitrievski, Kristian. Monte Carlo simulations of supported biomembranes and protein folding. Göteborg: Göteborg University, Department of Physics, 2006.

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Book chapters on the topic "Protein simulation"

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Wells, Stephen A. "Geometric Simulation of Flexible Motion in Proteins." In Protein Dynamics, 173–92. Totowa, NJ: Humana Press, 2013. http://dx.doi.org/10.1007/978-1-62703-658-0_10.

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Shao, Qing, and Carol K. Hall. "A Discontinuous Potential Model for Protein–Protein Interactions." In Foundations of Molecular Modeling and Simulation, 1–20. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-1128-3_1.

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Dal Palù, Alessandro, Agostino Dovier, and Federico Fogolari. "Protein Folding Simulation in CCP." In Logic Programming, 452–53. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-27775-0_34.

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Gruia, Andreea Daniela, Stefan Fischer, and Jeremy C. Smith. "Computer Simulation of Protein Unfolding." In High Performance Computing in Science and Engineering ’01, 260–68. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-642-56034-7_25.

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Janin, Joël, and Jacqueline Cherfils. "Protein-Protein Recognition: An Analysis by Docking Simulation." In NATO ASI Series, 331–37. Boston, MA: Springer US, 1994. http://dx.doi.org/10.1007/978-1-4899-1349-4_28.

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Duquerroy, Stéphane, Jacqueline Cherfils, and Joël Janin. "Protein-Protein Interaction: An Analysis by Computer Simulation." In Ciba Foundation Symposium 161 - Protein Conformation, 237–59. Chichester, UK: John Wiley & Sons, Ltd., 2007. http://dx.doi.org/10.1002/9780470514146.ch15.

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Shukla, Rohit, and Timir Tripathi. "Molecular Dynamics Simulation of Protein and Protein–Ligand Complexes." In Computer-Aided Drug Design, 133–61. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-6815-2_7.

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Petuya, V., M. Diez, M. Urizar, and A. Hernández. "Kinematics Study of Protein Chains and Protein Motion Simulation." In Mechanisms and Machine Science, 85–99. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-2721-2_9.

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Rao, V. S. R., B. V. S. Reddy, C. Mukhopadhyay, and M. Biswas. "Computer Simulation of Protein—Carbohydrate Complexes." In ACS Symposium Series, 361–76. Washington, DC: American Chemical Society, 1990. http://dx.doi.org/10.1021/bk-1990-0430.ch022.

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Hong, Min, David Osguthorpe, and Min-Hyung Choi. "Protein Simulation Using Fast Volume Preservation." In Computational Science – ICCS 2006, 308–15. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11758501_44.

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Conference papers on the topic "Protein simulation"

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Akkoyun, Emrah, and Tolga Can. "Parallelization of the functional flow algorithm for prediction of protein function using protein-protein interaction networks." In Simulation (HPCS). IEEE, 2011. http://dx.doi.org/10.1109/hpcsim.2011.5999807.

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Evans, Perry, Ted Sandler, and Lyle Ungar. "Protein-Protein Interaction Network Alignment by Quantitative Simulation." In 2008 IEEE International Conference on Bioinformatics and Biomedicine. IEEE, 2008. http://dx.doi.org/10.1109/bibm.2008.72.

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Voglis, C., P. E. Hadjidoukas, V. V. Dimakopoulos, I. E. Lagaris, and D. G. Papageorgiou. "Task-parallel global optimization with application to protein folding." In Simulation (HPCS). IEEE, 2011. http://dx.doi.org/10.1109/hpcsim.2011.5999823.

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Yu, Meng, Wei Si, and Jingjie Sha. "Molecular Dynamics Simulation for Protein Unfolding." In 2020 IEEE 15th International Conference on Nano/Micro Engineered and Molecular System (NEMS). IEEE, 2020. http://dx.doi.org/10.1109/nems50311.2020.9265552.

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Lee, Ling Wei, and Andrzej Bargiela. "Space-Partition Based Identification Of Protein Docksites." In 23rd European Conference on Modelling and Simulation. ECMS, 2009. http://dx.doi.org/10.7148/2009-0848-0854.

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Bahamish, Hesham Awadh Abdallah, Rosni Abdullah, and Rosalina Abdul Salam. "Protein Conformational Search Using Bees Algorithm." In 2008 Second Asia International Conference on Modelling & Simulation (AMS). IEEE, 2008. http://dx.doi.org/10.1109/ams.2008.65.

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Othman, Fazilah, Rosni Abdullah, and Rosalina Abdul Salam. "Bipartite Graph for Protein Structure Matching." In 2008 Second Asia International Conference on Modelling & Simulation (AMS). IEEE, 2008. http://dx.doi.org/10.1109/ams.2008.89.

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Sallim, Jamaludin, Rosni Abdullah, and Ahamad Tajudin Khader. "ACOPIN: An ACO Algorithm with TSP Approach for Clustering Proteins from Protein Interaction Network." In 2008 Second UKSIM European Symposium on Computer Modeling and Simulation (EMS). IEEE, 2008. http://dx.doi.org/10.1109/ems.2008.94.

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Schulze-Kremer and Tiedemann. "Parameterizing genetic algorithms for protein folding simulation." In Proceedings of the Twenty-Seventh Annual Hawaii International Conference on System Sciences. IEEE, 1994. http://dx.doi.org/10.1109/hicss.1994.323562.

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Maftouni, Negin, Mehriar Amininasab, MohammadReza Ejtehadi, and Farshad Kowsari. "Multiscale Molecular Dynamics Simulation of Nanobio Membrane in Interaction With Protein." In ASME 2013 2nd Global Congress on NanoEngineering for Medicine and Biology. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/nemb2013-93054.

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One of the most important biological components is lipid nanobio membrane. The lipid membranes of alive cells and their mechanical properties play an important role in biophysical investigations. Some proteins affect the shape and properties of the nanobio membrane while interacting with it. In this study a multiscale approach is experienced: first a 100ns all atom (fine-grained) molecular dynamics simulation is done to investigate the binding of CTX A3, a protein from snake venom, to a phosphatidylcholine lipid bilayer, second, a 5 micro seconds coarse-grained molecular dynamics simulation is carried out to compute the pressure tensor, lateral pressure, surface tension, and first moment of lateral pressure. Our simulations reveal that the insertion of CTX A3 into one monolayer results in an asymmetrical change in the lateral pressure and distribution of surface tension of the individual bilayer leaflets. The relative variation in the surface tension of the two monolayers as a result of a change in the contribution of the various intermolecular forces may be expressed morphologically and lead to deformation of the lipid membrane.
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Reports on the topic "Protein simulation"

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Muthukumar, Murugappan, and C. Y. Kong. Simulation of Polymer Translocation through Protein Channels. Fort Belvoir, VA: Defense Technical Information Center, September 2005. http://dx.doi.org/10.21236/ada437798.

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Daggett, Valerie. Simulation of Protein and Peptide-Based Biomaterials. Fort Belvoir, VA: Defense Technical Information Center, February 2002. http://dx.doi.org/10.21236/ada399142.

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Straatsma, TP, J. A. McCammon, John H. Miller, Paul E. Smith, Erich R. Vorpagel, Chung F. Wong, and Martin W. Zacharias. Biomolecular Simulation of Base Excision Repair and Protein Signaling. Office of Scientific and Technical Information (OSTI), March 2006. http://dx.doi.org/10.2172/877558.

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Pratt, L. R., A. E. Garcia, and G. Hummer. Computer simulation of protein solvation, hydrophobic mapping, and the oxygen effect in radiation biology. Office of Scientific and Technical Information (OSTI), August 1997. http://dx.doi.org/10.2172/524859.

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Geist, GA. Report on three Genomes to Life Workshops: Data Infrastructure, Modeling and Simulation, and Protein Structure Prediction. Office of Scientific and Technical Information (OSTI), September 2003. http://dx.doi.org/10.2172/885580.

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Mehlhorn, D. Guidelines for Computer Haptics Protein Simulations. Office of Scientific and Technical Information (OSTI), December 2000. http://dx.doi.org/10.2172/773840.

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Zhang S. Y. Simulation of Booster Proton Injection - Longitudinal. Office of Scientific and Technical Information (OSTI), August 1998. http://dx.doi.org/10.2172/1151377.

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Thompson, Aidan Patrick, Kunwoo Han, and David M. Ford. Molecular simulations of beta-amyloid protein near hydrated lipids (PECASE). Office of Scientific and Technical Information (OSTI), December 2005. http://dx.doi.org/10.2172/876519.

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Gregory A. Voth. Mechanism of Proton Transport in Proton Exchange Membranes: Insights from Computer Simulation. Office of Scientific and Technical Information (OSTI), November 2010. http://dx.doi.org/10.2172/993502.

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Lee, Chang-ho, Yeon Sang Jung, and Hyoung Kyu Cho. Micro Reactor Simulation Using the PROTEUS Suite in FY19. Office of Scientific and Technical Information (OSTI), September 2019. http://dx.doi.org/10.2172/1571248.

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