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Relevant bibliographies by topics / Biological Simulations

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Academic literature on the topic 'Biological Simulations'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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Journal articles on the topic "Biological Simulations"

1

Noble, Denis, Jeremy Levin, and William Scott. "Biological simulations in drug discovery." Drug Discovery Today 4, no. 1 (1999): 10–16. http://dx.doi.org/10.1016/s1359-6446(98)01277-x.

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Tobochnik, Jan, and Harvey Gould. "Lattice simulations of biological membranes." Computers in Physics 10, no. 6 (1996): 542. http://dx.doi.org/10.1063/1.168587.

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Hayot, F. "Simulations of Stochastic Biological Phenomena." Science Signaling 4, no. 192 (2011): tr13. http://dx.doi.org/10.1126/scisignal.2001973.

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Read, Mark N., Kieran Alden, Louis M. Rose, and Jon Timmis. "Automated multi-objective calibration of biological agent-based simulations." Journal of The Royal Society Interface 13, no. 122 (2016): 20160543. http://dx.doi.org/10.1098/rsif.2016.0543.

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Computational agent-based simulation (ABS) is increasingly used to complement laboratory techniques in advancing our understanding of biological systems. Calibration, the identification of parameter values that align simulation with biological behaviours, becomes challenging as increasingly complex biological domains are simulated. Complex domains cannot be characterized by single metrics alone, rendering simulation calibration a fundamentally multi-metric optimization problem that typical calibration techniques cannot handle. Yet calibration is an essential activity in simulation-based scienc

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Dallakyan, Gurgen. "Numerical Simulations for Chemotaxis Models." Biomath Communications 6, no. 1 (2019): 16. http://dx.doi.org/10.11145/bmc.2019.04.277.

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In the paper, we study the usage of numerical methods in solution of mathematical models of biological problems. More specifically, Keller-Segel type chemotaxis models are discussed, their numerical solutions by sweep and Lax-Friedrichs methods are obtained and interpreted biologically.

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Warshel, Arieh. "Molecular Dynamics Simulations of Biological Reactions." Accounts of Chemical Research 35, no. 6 (2002): 385–95. http://dx.doi.org/10.1021/ar010033z.

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Huber, Gary A., and J. Andrew McCammon. "Brownian Dynamics Simulations of Biological Molecules." Trends in Chemistry 1, no. 8 (2019): 727–38. http://dx.doi.org/10.1016/j.trechm.2019.07.008.

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HYEON, Changbong. "Coarse-grained Simulations of Biological Motors." Physics and High Technology 20, no. 5 (2011): 27. http://dx.doi.org/10.3938/phit.20.022.

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Tieleman, D. Peter, W. F. Drew Bennet, and Justin MacCallum. "Molecular dynamics simulations of biological membranes." Chemistry and Physics of Lipids 149 (September 2007): S4. http://dx.doi.org/10.1016/j.chemphyslip.2007.06.008.

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Gerami, Marzieh, Mohammad Eshghi, Modjtaba Emadi-Baygi, Fatemeh Elahian, and Mehdi Hosseinzadeh. "A biological multiplexer, designs, and simulations." Journal of Supercomputing 77, no. 1 (2020): 366–87. http://dx.doi.org/10.1007/s11227-019-03138-4.

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Dissertations / Theses on the topic "Biological Simulations"

1

Waheed, Qaiser. "Molecular Dynamic Simulations of Biological Membranes." Doctoral thesis, KTH, Teoretisk biologisk fysik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-102268.

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Biological membranes mainly constituent lipid molecules along with some proteins and steroles. The properties of the pure lipid bilayers as well as in the presence of other constituents (in case of two or three component systems) are very important to be studied carefully to model these systems and compare them with the realistic systems. Molecular dynamic simulations provide a good opportunity to model such systems and to study them at microscopic level where experiments fail to do. In this thesis we study the structural and dynamic properties of the pure phospholipid bilayers and the phase b

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Baker, Joseph Lee. "Steered Molecular Dynamics Simulations of Biological Molecules." Diss., The University of Arizona, 2011. http://hdl.handle.net/10150/205416.

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Molecular dynamics (MD) simulation, which employs an empirical potential energy function to describe the interactions between the atoms in a system, is used to investigate atomistic motions of proteins. However, the timescale of many biological processes exceeds the reach of standard MD due to computational limitations. To circumvent these limitations, steered molecular dynamics (SMD), which applies external forces to the simulated system, can be used.Dynamical properties of the gonococcal type IV pilus (GC-T4P) from the bacteria Neisseria gonorrhoeae are first considered. T4 pili are long, fi

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Prévot, Martine. "Biomolecular simulations: structure, thermodynamics and dynamics of biological systems." Doctoral thesis, Universite Libre de Bruxelles, 2002. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/211440.

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Barder, Simen Eidsmo. "Molecular Dynamics Simulations of DNA Translocation through a biological Nanopore." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for konstruksjonsteknikk, 2012. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-19428.

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Experimental and simulation studies of nucleic acid transport through nanosized channels, both biological and synthetic, has become a rapidly growing research area over the last decade. While the utilization of the alpha-hemolysin channel as a sequencing device is soon to be realized, other biological nanochannels may hold advantages that are yet unknown. Motivated by this, the first reported molecular dynamics simulations of DNA translocation through a connexon 26 channel were accomplished, for single-strandeed DNA with a length of 24 nucleotides and with a sequence containing only adenine, c

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Parton, Daniel L. "Pushing the boundaries : molecular dynamics simulations of complex biological membranes." Thesis, University of Oxford, 2011. http://ora.ox.ac.uk/objects/uuid:7ab91b51-a5ae-46b4-b6dc-3f0dd3f0b477.

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A range of simulations have been conducted to investigate the behaviour of a diverse set of complex biological membrane systems. The processes of interest have required simulations over extended time and length scales, but without sacrifice of molecular detail. For this reason, the primary technique used has been coarse-grained molecular dynamics (CG MD) simulations, in which small groups of atoms are combined into lower-resolution CG particles. The increased computational efficiency of this technique has allowed simulations with time scales of microseconds, and length scales of hundreds of nm

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Leekumjorn, Sukit. "Molecular Dynamics Simulations for the Study of Biophysical Processes on Biological Membranes." Diss., Virginia Tech, 2008. http://hdl.handle.net/10919/29180.

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Phospholipid bilayers constitute the primary structural element of biological membranes, and as such, they play a central role in biochemical and biophysical processes at the cellular level, including cell protection, intercellular interactions, trans-membrane transport, cell morphology, and protein function, to name a few. The properties of phospholipid bilayers are thus of great interest from both experimental and theoretical standpoints. Although experiments have provided much of the macroscopic functions and properties of biological membranes, insight into specific mechanisms at the mole

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Guo, Donghang. "Large-Scale Simulations for Complex Adaptive Systems with Application to Biological Domains." Diss., Virginia Tech, 2007. http://hdl.handle.net/10919/26403.

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Modeling or simulating Complex Adaptive Systems (CASs) is both important and challenging. As the name suggests, CASs are systems consisting of large numbers of interacting adaptive compartments. They are studied across a wide range of disciplines and have unique properties. They model such systems as multicellular organisms, ecosystems, social networks, and many more. They are complex, in the sense that they are dynamical, nonlinear, and heterogeneous systems that cannot be simply scaled up/down. However, they are self-organized, in the sense that they can evolve into specific structures/patte

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FOUAD, AHMED MOHAMED. "Density-Dependent Diffusion Models with Biological Applications." Diss., Temple University Libraries, 2015. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/336411.

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Physics<br>Ph.D.<br>Diffusion is defined as the movement of a substance down a concentration gradient. The physics of diffusion is well described by Fick’s law. A density-dependent diffusion process is a one in which the diffusion coefficient is a function of the localized density of the diffusing substance. In my thesis I analyze the density-dependent diffusion behavior of two independent processes of biological interest. The first is tumor growth and invasion. The second is single-file diffusion, which in turn has a considerable biological significance, since it has been recently used to mod

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Pastuszak, Jakub. "Biological evolution and the physics of growing microbial colonies." Thesis, University of Edinburgh, 2016. http://hdl.handle.net/1842/22834.

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In this thesis I investigate the role of spatial structure, cell-cell interactions and horizontal gene transfer on the genetic composition of growing microbial colonies. In the first part I study how the roughness of the growing layer of the colony depends on the shape of colony-forming cells. To study its impact I develop an off-lattice Eden-like model in which cells are represented as spherocylinders with a variable aspect ratio. I show that the roughness of the expansion front is not significantly affected by the shape of cells and that the dynamic scaling of growing front belongs to the KP

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Mercker, Moritz [Verfasser], and Willi [Akademischer Betreuer] Jäger. "Models, Numerics and Simulations of Deforming Biological Surfaces / Moritz Mercker ; Betreuer: Willi Jäger." Heidelberg : Universitätsbibliothek Heidelberg, 2012. http://d-nb.info/1179785878/34.

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Books on the topic "Biological Simulations"

1

International, Conference on Computer Simulations in Biomedicine (3rd 1995 Milan Italy). Computer simulations in biomedicine. Computational Mechanics Publications, 1995.

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H, Power, Brebbia C. A, and Kenny J, eds. Simulations in biomedicine IV. Computational Mechanics Publications, 1997.

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Rui-Qin, Zhang, Treutlein Herbert R, and SpringerLink (Online service), eds. Quantum Simulations of Materials and Biological Systems. Springer Netherlands, 2012.

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Li, Shaofan, and Dong Qian, eds. Multiscale Simulations and Mechanics of Biological Materials. John Wiley & Sons Ltd, 2013. http://dx.doi.org/10.1002/9781118402955.

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Zeng, Jun, Rui-Qin Zhang, and Herbert R. Treutlein, eds. Quantum Simulations of Materials and Biological Systems. Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-4948-1.

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Goel, Narendra S. Computer simulations of self-organization in biological systems. Croom Helm, 1988., 1988.

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Goel, Narendra S. Computer simulations of self-organization in biological systems. Croom Helm, 1988.

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8

Stanley, Jeannette. Introduction to neural networks: Computer simulations of biological intelligence. California Scientific Software, 1988.

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M, Arnež Z., ed. Simulations in biomedicine V. WIT Press, 2003.

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R, Wellin Paul, ed. Computer simulations with Mathematica: Explorations in complex physical and biological systems. Springer-Verlag TELOS, 1995.

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Book chapters on the topic "Biological Simulations"

1

Jakobsson, Eric, Shankar Subramaniam, and H. Larry Scott. "Strategic Issues in Molecular Dynamics Simulations of Membranes." In Biological Membranes. Birkhäuser Boston, 1996. http://dx.doi.org/10.1007/978-1-4684-8580-6_4.

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Pietropaolo, Adriana, and Concetta Cozza. "Molecular Simulations of Biological Nanoswitches." In Encyclopedia of Biophysics. Springer Berlin Heidelberg, 2020. http://dx.doi.org/10.1007/978-3-642-35943-9_10092-1.

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3

Smit, B., M. Kranenburg, M. M. Sperotto, and M. Venturoli. "Mesoscopic Simulations of Biological Membranes." In Computer Simulations in Condensed Matter Systems: From Materials to Chemical Biology Volume 2. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/3-540-35284-8_11.

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Han, Xiaoying, and Peter E. Kloeden. "Comparative Simulations of Biological Systems." In Random Ordinary Differential Equations and Their Numerical Solution. Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-6265-0_15.

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Stevens, Angela. "Simulations of the Gliding Behavior and Aggregation of Myxobacteria." In Biological Motion. Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/978-3-642-51664-1_36.

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Callegari, Agnese, and Giovanni Volpe. "Numerical Simulations of Active Brownian Particles." In Soft and Biological Matter. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-23370-9_7.

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Post, C. B., and V. M. Dadarlat. "Molecular-dynamics simulations of biological macromolecules." In International Tables for Crystallography. International Union of Crystallography, 2006. http://dx.doi.org/10.1107/97809553602060000706.

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Post, C. B., and V. M. Dadarlat. "Molecular-dynamics simulations of biological macromolecules." In International Tables for Crystallography. International Union of Crystallography, 2012. http://dx.doi.org/10.1107/97809553602060000878.

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Lintermann, Andreas. "Computational Meshing for CFD Simulations." In Biological and Medical Physics, Biomedical Engineering. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-6716-2_6.

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Kamberaj, Hiqmet. "Thermodynamics of Biological Phenomena." In Molecular Dynamics Simulations in Statistical Physics: Theory and Applications. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-35702-3_4.

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Conference papers on the topic "Biological Simulations"

1

Marchyk, Nataliya A., Gennady K. Zhavnerko, and Vladimir E. Agabekov. "Polymeric analogs of biological membranes." In Nano-Design, Technology, Computer Simulations, edited by Alexander I. Melker and Vladislav V. Nelayev. SPIE, 2008. http://dx.doi.org/10.1117/12.836483.

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Chushak, Y., B. Foy, and J. Frazier. "Stochastic Simulations of Cellular Biological Processes." In 2007 DoD High Performance Computing Modernization Program Users Group Conference. IEEE, 2007. http://dx.doi.org/10.1109/hpcmp-ugc.2007.70.

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Biham, Ofer, Nathalie Q. Balaban, Adiel Loinger, Azi Lipshtat, and Hagai B. Perets. "Deterministic and stochastic simulations of simple genetic circuits." In Stochastic Models in Biological Sciences. Institute of Mathematics Polish Academy of Sciences, 2008. http://dx.doi.org/10.4064/bc80-0-4.

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Hampton, Scott, Pratul K. Agarwal, Sadaf R. Alam, and Paul S. Crozier. "Towards microsecond biological molecular dynamics simulations on hybrid processors." In Simulation (HPCS). IEEE, 2010. http://dx.doi.org/10.1109/hpcs.2010.5547149.

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Bonati, L., E. Fraschini, M. Lasagni, U. Cosentino, G. Moro, and D. Pitea. "Electrostatic descriptors in relation to biological activity of some chlorinated dibenzo-p-dioxins." In Advances in biomolecular simulations. AIP, 1991. http://dx.doi.org/10.1063/1.41317.

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Pozdneev, A., V. Weber, T. Laino, C. Bekas, and A. Curioni. "Enhanced MPSM3 for Applications to Quantum Biological Simulations." In SC16: International Conference for High Performance Computing, Networking, Storage and Analysis. IEEE, 2016. http://dx.doi.org/10.1109/sc.2016.8.

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Keane, John F., Christopher Bradley, and Carl Ebeling. "A compiled accelerator for biological cell signaling simulations." In Proceeding of the 2004 ACM/SIGDA 12th international symposium. ACM Press, 2004. http://dx.doi.org/10.1145/968280.968313.

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Ashlock, Wendy, and Daniel Ashlock. "Designing artificial organisms for use in biological simulations." In 2011 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology - Part of 17273 - 2011 Ssci. IEEE, 2011. http://dx.doi.org/10.1109/cibcb.2011.5948463.

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Phan, John H., Richard A. Moffitt, Todd H. Stokes, and May D. Wang. "Evolving Biological Behavior in Gene-Based Cellular Simulations." In 2007 IEEE 7th International Symposium on BioInformatics and BioEngineering. IEEE, 2007. http://dx.doi.org/10.1109/bibe.2007.4375609.

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Hesam, Ahmad, Lukas Breitwieser, Fons Rademakers, and Zaid Al-Ars. "GPU Acceleration of 3D Agent-Based Biological Simulations." In 2021 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW). IEEE, 2021. http://dx.doi.org/10.1109/ipdpsw52791.2021.00040.

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Reports on the topic "Biological Simulations"

1

Nayfack, Nicholas, and Robert W. MacDougall. Chemical Biological Defense (CBD) Simulations. Defense Technical Information Center, 1996. http://dx.doi.org/10.21236/ada396828.

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Singh, Rajesh, Marshall Richmond, Pedro Romero-Gomez, Cynthia Rakowski, and John Serkowski. Validation of Computational Fluid Dynamics Simulations for Biological Performance Assessment in Hydropower units. Office of Scientific and Technical Information (OSTI), 2021. http://dx.doi.org/10.2172/1798166.

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Lau, E., C. Venclovas, E. Schwegler, et al. A Strategic Initiative in Applied Biological Simulations 01-SI-012 Final Report for FY01 - FY03. Office of Scientific and Technical Information (OSTI), 2004. http://dx.doi.org/10.2172/15009789.

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Acosta, Felipe, Guillermo Riveros, Reena Patel, and Wayne Hodo. Numerical simulation of biological structures : paddlefish rostrum. Geotechnical and Structures Laboratory (U.S.), 2019. http://dx.doi.org/10.21079/11681/32749.

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BOOKER, C. P., and W. G. LACEY. VIRTUAL SIMULATION TESTBED FOR BIOLOGICAL DEFENSE: A COMPOSITION EVNIRONMENT FOR SIMULATION DEVELOPMENT. Office of Scientific and Technical Information (OSTI), 1999. http://dx.doi.org/10.2172/787261.

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Chai, Fei, and Emmanuel Boss. Physical-Biological-Optics Model Development and Simulation for the Monterey Bay, California. Defense Technical Information Center, 2008. http://dx.doi.org/10.21236/ada516870.

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Chai, Fei, and Emmanuel Boss. Physical-Biological-Optics Model Development and Simulation for the Pacific Ocean and Monterey Bay, California. Defense Technical Information Center, 2011. http://dx.doi.org/10.21236/ada540700.

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Chai, Fei, and Emmanuel Boss. Physical-Biological-Optics Model Development and Simulation for the Pacific Ocean and Monterey Bay, California. Defense Technical Information Center, 2010. http://dx.doi.org/10.21236/ada541221.

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Chai, Fei, and Emmanuel Boss. Physical-Biological-Optics Model Development and Simulation for the Pacific Ocean and Monterey Bay, California. Defense Technical Information Center, 2011. http://dx.doi.org/10.21236/ada557142.

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Chai, Fei, and Emmanuel Boss. Physical-Biological-Optics Model Development and Simulation for the Pacific Ocean and Monterey Bay, California. Defense Technical Information Center, 2012. http://dx.doi.org/10.21236/ada572747.

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