Relevant bibliographies by topics / Biological systems modeling

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Biological systems modeling'

Author: Grafiati
Published: 4 June 2021
Last updated: 17 February 2022

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Journal articles on the topic "Biological systems modeling"

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Ågren, Göran I. "Modeling biological systems." Forest Ecology and Management 96, no. 1-2 (1997): 185–86. http://dx.doi.org/10.1016/s0378-1127(97)00103-5.

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Darbari, Manuj, and Vipin Saxena. "Modeling biological systems." ACM SIGSOFT Software Engineering Notes 30, no. 5 (2005): 1–4. http://dx.doi.org/10.1145/1095430.1095441.

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Liu, Zhi-Ping, and Luonan Chen. "Multiscale modeling biological systems." IET Systems Biology 10, no. 1 (2016): 1. http://dx.doi.org/10.1049/iet-syb.2016.0002.

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Bagley, R. J., J. D. Farmer, S. A. Kauffman, N. H. Packard, A. S. Perelson, and I. M. Stadnyk. "Modeling adaptive biological systems." Biosystems 23, no. 2-3 (1989): 113–37. http://dx.doi.org/10.1016/0303-2647(89)90016-6.

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Wasik, Szymon. "Modeling Biological Systems Using Crowdsourcing." Foundations of Computing and Decision Sciences 43, no. 3 (2018): 219–43. http://dx.doi.org/10.1515/fcds-2018-0012.

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Abstract Crowdsourcing is a very effective technique for outsourcing work to a vast network usually comprising anonymous people. In this study, we review the application of crowdsourcing to modeling systems originating from systems biology. We consider a variety of verified approaches, including well-known projects such as EyeWire, FoldIt, and DREAM Challenges, as well as novel projects conducted at the European Center for Bioinformatics and Genomics. The latter projects utilized crowdsourced serious games to design models of dynamic biological systems, and it was demonstrated that these model
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Kiselev, Ilya, and Fedor Kolpakov. "Modular Modeling of Biological Systems." Virtual Biology 1, no. 1 (2013): 30. http://dx.doi.org/10.12704/vb/e11.

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Motta, S., and F. Pappalardo. "Mathematical modeling of biological systems." Briefings in Bioinformatics 14, no. 4 (2012): 411–22. http://dx.doi.org/10.1093/bib/bbs061.

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Sulpizi, Marialore, Roland Faller, and Sergio Pantano. "Multiscale modeling on biological systems." Biochemical and Biophysical Research Communications 498, no. 2 (2018): 263. http://dx.doi.org/10.1016/j.bbrc.2018.02.179.

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Raugei, Simone, Francesco Luigi Gervasio, and Paolo Carloni. "DFT modeling of biological systems." physica status solidi (b) 243, no. 11 (2006): 2500–2515. http://dx.doi.org/10.1002/pssb.200642096.

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Lubbock, Alexander L. R., and Carlos F. Lopez. "Programmatic modeling for biological systems." Current Opinion in Systems Biology 27 (September 2021): 100343. http://dx.doi.org/10.1016/j.coisb.2021.05.004.

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Dissertations / Theses on the topic "Biological systems modeling"

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Thiele, Sven. "Modeling biological systems with Answer Set Programming." Phd thesis, Universität Potsdam, 2011. http://opus.kobv.de/ubp/volltexte/2012/5938/.

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Biology has made great progress in identifying and measuring the building blocks of life. The availability of high-throughput methods in molecular biology has dramatically accelerated the growth of biological knowledge for various organisms. The advancements in genomic, proteomic and metabolomic technologies allow for constructing complex models of biological systems. An increasing number of biological repositories is available on the web, incorporating thousands of biochemical reactions and genetic regulations. Systems Biology is a recent research trend in life science, which fosters a sy
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Iyoho, Anthony E. "Modeling and analysis of nonlinear biological systems." Diss., Columbia, Mo. : University of Missouri-Columbia, 2007. http://hdl.handle.net/10355/6012.

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Thesis (Ph. D.)--University of Missouri-Columbia, 2007.<br>The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on December 28, 2007) Includes bibliographical references.
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Gao, Yue. "Modeling of Drug Transport in Biological Systems." The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1316452154.

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Shi, Kevin Ph D. Massachusetts Institute of Technology. "Modeling and controlling uncertainty in multi-level biological systems." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/121701.

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This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biological Engineering, 2019<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (pages 153-172).<br>Mathematical modeling is essential to the understanding and design of biological systems. Modeling uncertainty, which variously represents lack of data, variability between individuals and between different measurements of a single ind
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Mackin, Charles Edward. "Graphene chemical and biological sensors : modeling, systems, and applications." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/118095.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.<br>Cataloged from PDF version of thesis. Page 199 blank.<br>Includes bibliographical references (pages 173-198).<br>Graphene exhibits a unique combination of properties making it particularly promising for sensing applications. This thesis builds new graphene chemical and biological sensing technologies from the ground up by developing device models, systems, and applications. On the modeling side, this thesis develops a DC model for graphene electrolyte-gated field-effect tr
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Pokrzywa, Revonda Maria. "Systems Biology in an Imperfect World: Modeling Biological Systems with Incomplete Information." Diss., Virginia Tech, 2009. http://hdl.handle.net/10919/39938.

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One of the primary goals of systems biology is to understand the complex underlying network of biochemical interactions which allow an organism to respond to environmental stimuli. Models of these biological interactions serve as a tool to both codify current understanding of these interactions as well as a starting point for scientific discovery. Due to the massive amount of information which is required for this modeling process, systems biology studies must often attempt to construct models which reflect the whole of the system while having access to only partial information. In some cases,
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Lao, Bert Juan. "Diversified approach to the mathematical and computational modeling of biological systems." Diss., Restricted to subscribing institutions, 2008. http://proquest.umi.com/pqdweb?did=1562159981&sid=1&Fmt=2&clientId=1564&RQT=309&VName=PQD.

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Shvonski, Alexander J. "Modeling Nonlocal and Nonlinear Response Phenomena of Plasmonic and Biological Systems." Thesis, Boston College, 2018. http://hdl.handle.net/2345/bc-ir:108209.

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Thesis advisor: Krzysztof Kempa<br>In this work, we first examine nonlocal behavior in plasmonic systems and develop or expand upon models that enable calculation of higher-order, nonlocal responses for systems with novel geometries. The effects of nonlocality, i.e., spatial dispersion, are prominent in nanostuctures with small feature sizes, and accurate calculations of the nonlocal response of nanostructures are increasingly important for the study of novel physics at the nanoscale. Next, we consider a specific biological system, double-stranded DNA, and investigate the nonlocal and nonlinea
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Ren, Xiaojing. "Modeling pattern formation of swimming E.coli." Click to view the E-thesis via HKUTO, 2010. http://sunzi.lib.hku.hk/hkuto/record/B43704001.

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Thiele, Sven [Verfasser], and Torsten [Akademischer Betreuer] Schaub. "Modeling biological systems with Answer Set Programming / Sven Thiele. Betreuer: Torsten Schaub." Potsdam : Universitätsbibliothek der Universität Potsdam, 2012. http://d-nb.info/1023164612/34.

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Books on the topic "Biological systems modeling"

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Haefner, James W. Modeling Biological Systems. Springer US, 1996. http://dx.doi.org/10.1007/978-1-4615-4119-6.

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Haefner, James W. Modeling Biological Systems. Springer US, 2005. http://dx.doi.org/10.1007/b106568.

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Matthias, Ruth, ed. Modeling dynamic biological systems. Springer, 1997.

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Hannon, Bruce, and Matthias Ruth. Modeling Dynamic Biological Systems. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-05615-9.

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Ruth, Matthias, and Bruce Hannon. Modeling Dynamic Biological Systems. Springer New York, 1997. http://dx.doi.org/10.1007/978-1-4612-0651-4.

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Fariñas del Cerro, Luis, and Katsumi Inoue, eds. Logical Modeling of Biological Systems. John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781119005223.

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Deutsch, Andreas, Lutz Brusch, Helen Byrne, Gerda de Vries, and Hanspeter Herzel, eds. Mathematical Modeling of Biological Systems. Birkhäuser Boston, 2007. http://dx.doi.org/10.1007/978-0-8176-4558-8.

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Dokholyan, Nikolay V., ed. Computational Modeling of Biological Systems. Springer US, 2012. http://dx.doi.org/10.1007/978-1-4614-2146-7.

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Almudevar, Anthony, David Oakes, and Jack Hall, eds. Statistical Modeling for Biological Systems. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-34675-1.

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Agha, Gul, Olivier Danvy, and José Meseguer, eds. Formal Modeling: Actors, Open Systems, Biological Systems. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24933-4.

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Book chapters on the topic "Biological systems modeling"

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Parke, William C. "Modeling Biological Systems." In Biophysics. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-44146-3_13.

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Haefner, James W. "Models of Systems." In Modeling Biological Systems. Springer US, 1996. http://dx.doi.org/10.1007/978-1-4615-4119-6_1.

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Haefner, James W. "Complex Adaptive Systems." In Modeling Biological Systems. Springer US, 1996. http://dx.doi.org/10.1007/978-1-4615-4119-6_20.

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Haefner, James W. "The Modeling Process." In Modeling Biological Systems. Springer US, 1996. http://dx.doi.org/10.1007/978-1-4615-4119-6_2.

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Haefner, James W. "Stochastic Models." In Modeling Biological Systems. Springer US, 1996. http://dx.doi.org/10.1007/978-1-4615-4119-6_10.

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Haefner, James W. "Photosynthesis and Plant Growth." In Modeling Biological Systems. Springer US, 1996. http://dx.doi.org/10.1007/978-1-4615-4119-6_11.

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Haefner, James W. "Hormonal Control in Mammals." In Modeling Biological Systems. Springer US, 1996. http://dx.doi.org/10.1007/978-1-4615-4119-6_12.

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Haefner, James W. "Populations and Individuals." In Modeling Biological Systems. Springer US, 1996. http://dx.doi.org/10.1007/978-1-4615-4119-6_13.

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Haefner, James W. "Chemostats." In Modeling Biological Systems. Springer US, 1996. http://dx.doi.org/10.1007/978-1-4615-4119-6_14.

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Haefner, James W. "Spatial Patterns and Processes." In Modeling Biological Systems. Springer US, 1996. http://dx.doi.org/10.1007/978-1-4615-4119-6_15.

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Conference papers on the topic "Biological systems modeling"

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Pishak, Vasyl P., Taras N. Boychuk, Miroslav T. Strinadko, and B. M. Timochko. "Modeling biological systems rhythms." In International Conference on Correlation Optics, edited by Oleg V. Angelsky. SPIE, 1999. http://dx.doi.org/10.1117/12.370457.

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Wang, Qinsi, and Edmund M. Clarke. "Formal modeling of biological systems." In 2016 IEEE International High Level Design Validation and Test Workshop (HLDVT). IEEE, 2016. http://dx.doi.org/10.1109/hldvt.2016.7748273.

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Helms, Michael, Swaroop Vattam, and Ashok Goel. "The Effect of Functional Modeling on Understanding Complex Biological Systems." In ASME 2010 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/detc2010-28939.

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Biologically inspired engineering design requires understanding of complex biological systems for use as analogues in engineering designs. In this study we seek to understand how functional representations, in particular Structure-Behavior-Function (SBF) models, enable understanding complex biological systems. Results from this study indicate that SBF representations may enable more accurate inferences about biological systems for complex and abstract questions than purely textual, or textual and diagrammatic, representations. They also suggest that no one representation is best for all types
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Harel, David. "Comprehensive and Realistic Modeling of Biological Systems." In 2006 Winter Simulation Conference. IEEE, 2006. http://dx.doi.org/10.1109/wsc.2006.322936.

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Shafaei, Sima, and Nasser Ghasem Aghaee. "Biological Network Simulation Using Holonic Multiagent Systems." In Tenth International Conference on Computer Modeling and Simulation (uksim 2008). IEEE, 2008. http://dx.doi.org/10.1109/uksim.2008.23.

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Ed, McGuinness,. "Increasing Biological Accuracy in Models of HIV Progression While Minimising Complexity." In Modeling and Control in Biomedical Systems, edited by Rees, Stephen, chair Andreassen, Steen and Andreassen, Steen. Elsevier, 2009. http://dx.doi.org/10.3182/20090812-3-dk-2006.00056.

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Turnip, Arjon, and T. A. Tamba. "Algorithmic modeling and analysis of nonlinear biological systems." In 2015 10th Asian Control Conference (ASCC). IEEE, 2015. http://dx.doi.org/10.1109/ascc.2015.7244876.

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Kermani, Mohamed Hachem, and Zizette Boufaida. "A State of Art on Biological Systems Modeling." In 2016 19th IEEE Intl Conference on Computational Science and Engineering (CSE), IEEE 14th Intl Conference on Embedded and Ubiquitous Computing (EUC), and 15th Intl Symposium on Distributed Computing and Applications for Business Engineering (DCABES). IEEE, 2016. http://dx.doi.org/10.1109/cse-euc-dcabes.2016.266.

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Kalantari, John. "Unsupervised In-Silico Modeling of Complex Biological Systems." In 2016 IEEE 1st International Workshops on Foundations and Applications of Self* Systems (FAS*W). IEEE, 2016. http://dx.doi.org/10.1109/fas-w.2016.69.

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"Session TA1 Multi-Scale Modeling of Biological Systems." In Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004. IEEE, 2004. http://dx.doi.org/10.1109/acssc.2004.1399232.

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Reports on the topic "Biological systems modeling"

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Zurada, Jacek M., Andy G. Lozowski, and Mykola Lysetskiy. Modeling of Spatial and Temporal Dynamics in Biological Olfactory Systems. Defense Technical Information Center, 2007. http://dx.doi.org/10.21236/ada472796.

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Seale, Maria, Natàlia Garcia-Reyero, R. Salter, and Alicia Ruvinsky. An epigenetic modeling approach for adaptive prognostics of engineered systems. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/41282.

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Prognostics and health management (PHM) frameworks are widely used in engineered systems, such as manufacturing equipment, aircraft, and vehicles, to improve reliability, maintainability, and safety. Prognostic information for impending failures and remaining useful life is essential to inform decision-making by enabling cost versus risk estimates of maintenance actions. These estimates are generally provided by physics-based or data-driven models developed on historical information. Although current models provide some predictive capabilities, the ability to represent individualized dynamic f
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Stenner, Robert D., Donald L. Hadley, Peter R. Armstrong, John W. Buck, and Bonnie L. Hoopes. Indoor Air Nuclear, Biological, and Chemical Health Modeling and Assessment System. Office of Scientific and Technical Information (OSTI), 2001. http://dx.doi.org/10.2172/782696.

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Stenner, Robert D., Donald L. Hadley, Peter R. Armstrong, John W. Buck, Bonnie L. Hoopes, and Michael C. Janus. Indoor Air Nuclear, Biological, and Chemical Health Modeling and Assessment System. Office of Scientific and Technical Information (OSTI), 2001. http://dx.doi.org/10.2172/965735.

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Rittmann, B. E., A. J. Valocchi, and P. Baveye. Fundamental quantitative analysis of microbial activity in aquifer bioreclamation; and Modeling the transport of biologically and chemically reactive solutes in a two-dimensional, heterogeneous intermediate scale system. Semi-annual progress report, August 1991--March 1992. Office of Scientific and Technical Information (OSTI), 1992. http://dx.doi.org/10.2172/10187295.

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Computational Biology: Development in the Field of Medicine. Science Repository, 2021. http://dx.doi.org/10.31487/sr.blog.31.

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Computational biology involves the development and application of analytical-data and theoretical methods, computational simulation techniques, and mathematical modeling to the study of biological, behavioral, ecological, and social systems.
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