Relevant bibliographies by topics / Biological modelling

Contents

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

Academic literature on the topic 'Biological modelling'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Biological modelling"

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Roenneberg, Till, Elaine Jane Chua, Ric Bernardo, and Eduardo Mendoza. "Modelling Biological Rhythms." Current Biology 18, no. 17 (2008): R826—R835. http://dx.doi.org/10.1016/j.cub.2008.07.017.

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MADDEN, T. D., M. J. HOPE, and P. R. CULLIS. "Modelling the biological membrane." Biochemical Society Transactions 15, no. 1 (1987): 75–77. http://dx.doi.org/10.1042/bst0150075.

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Vanhooren, Henk, Jurgen Meirlaen, Youri Amerlinck, Filip Claeys, Hans Vangheluwe, and Peter A. Vanrolleghem. "WEST: modelling biological wastewater treatment." Journal of Hydroinformatics 5, no. 1 (2003): 27–50. http://dx.doi.org/10.2166/hydro.2003.0003.

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Modelling is considered to be an inherent part of the design and operation of a wastewater treatment system. The models used in practice range from conceptual models and physical design models (laboratory-scale or pilot-scale reactors) to empirical or mechanistic mathematical models. These mathematical models can be used during the design, operation and optimisation of a wastewater treatment system. To do so, a good software tool is indispensable. WEST is a general modelling and simulation environment and can, together with a model base, be used for this task. The model base presented here is
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Keane, John. "Tools for modelling biological processes." Nature 421, no. 6923 (2003): 573. http://dx.doi.org/10.1038/421573b.

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Mandel, J. J., W. Dubitzky, and N. M. Palfreyman. "Modelling codependence in biological systems." IET Systems Biology 1, no. 1 (2007): 18–32. http://dx.doi.org/10.1049/iet-syb:20060002.

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Cooling, M. T., E. J. Crampin, and P. Hunter. "Modelling biological modularity with CellML." IET Systems Biology 2, no. 2 (2008): 73–79. http://dx.doi.org/10.1049/iet-syb:20070020.

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Finkelstein, M. S. "Reliability modelling for biological ageing." Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability 222, no. 1 (2008): 1–6. http://dx.doi.org/10.1243/1748006xjrr65.

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Some stochastic approaches to modelling biological ageing are studied. The assumption is made that a random resource is acquired by an organism at birth. Failure (death) occurs when the accumulated wear exceeds this initial resource, modelled by discrete or continuous random variables. Deterioration in repairable objects is also considered. Two models are discussed. The first one is an imperfect repair model. It is shown that under certain assumptions the accumulated damage in this model is bounded. The second model is based on the shot noise process and takes into account the ‘healing effect’
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Purmal', A. P., and L. A. Nikolaev. "The Modelling of Biological Catalysts." Russian Chemical Reviews 54, no. 5 (1985): 466–75. http://dx.doi.org/10.1070/rc1985v054n05abeh003077.

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Osis, J., and L. Beghi. "Topological Modelling of Biological Systems." IFAC Proceedings Volumes 30, no. 2 (1997): 337–42. http://dx.doi.org/10.1016/s1474-6670(17)44593-9.

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Stein, Gillian Z. "Modelling counts in biological populations." Mathematical and Computer Modelling 12, no. 9 (1989): 1183. http://dx.doi.org/10.1016/0895-7177(89)90259-8.

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Dissertations / Theses on the topic "Biological modelling"

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Lemon, A. P. "Modelling the biological membrane." Thesis, University of Bath, 1995. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.760688.

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Lumley, James Andrew. "Molecular modelling of biological activity." Thesis, University of Reading, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.393752.

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Luo, Yang. "Stochastic modelling in biological systems." Thesis, University of Cambridge, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.610145.

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Billing, Alison Emslie. "Modelling techniques for biological systems." Master's thesis, University of Cape Town, 1987. http://hdl.handle.net/11427/21917.

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The objective of this investigation has been to develop and evaluate techniques which are appropriate to the modelling and simulation of biological reaction system behaviour. The model used as the basis for analysis of modelling and simulation techniques is a reduced version of the biological model proposed by the IAWPRC Task Group for mathematical modell ing in wastewater treatment design. This limited model has the advantage of being easily manageable in terms of analysis and presentation of the simulation techniQues whilst at the same time incorporating a range of features encountered with
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Cotton-Barratt, Rebecca. "Modelling biological form in evolution." Thesis, University of Warwick, 2013. http://wrap.warwick.ac.uk/70973/.

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How are processes working at the individual level, the species level and the macro-ecological level connected? This thesis explores the theoretical and structural constraints on biological evolution. It does this by developing an evolutionary program to model biological form. This development was necessary as the existing models of evolution are poorly suited to modelling morphological constraint. The model of biological form developed in this thesis uses graphs to abstractly represent organisms and the relationships of their internal structure. We show that by increasing the number of degrees
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Djordjilovic, Vera. "Graphical modelling of biological pathways." Doctoral thesis, Università degli studi di Padova, 2015. http://hdl.handle.net/11577/3424702.

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Biological pathways underlie the basic functions of a living cell. They are complex diagrams featuring genes, proteins and other small molecules, showing how they work together to achieve a particular biological effect. From a technical point of view, they are networks represented through a graph where genes and their connections are, respectively, nodes and edges of a graph. The main research objective of this thesis is to develop a framework for simulating effects of gene silencing. To this end, we propose a three step approach. First, we refine the structure of a pathway via our C
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Hodgkinson, Arran. "Mathematical Methods for Modelling Biological Heterogeneity." Thesis, Montpellier, 2019. http://www.theses.fr/2019MONTS119.

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Les processus biologiques sont des phénomènes complexes, multi-échelles, présentant une hétérogénéité importante à travers l’espace, la structure et la fonction. De plus, ils impliquent des événements fortement corrélés et présentent des boucles de rétroaction à travers les échelles. Dans cette thèse, nous utilisons des représentations spatio-structuro-temporelles en grande dimension pour étudier l'hétérogénéité biologique à travers l'espace, la fonction biologique et le temps, et appliquons cette méthode à divers problèmes importants en biologie et en clinique.Nous commençons par introduire u
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Sharma, A. "Modelling biological systems: a fractal approach." Thesis(Ph.D.), CSIR-National Chemical Laboratory, Pune, 1991. http://dspace.ncl.res.in:8080/xmlui/handle/20.500.12252/3009.

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Fear, Elise Carolyn. "Modelling biological cells exposed to electric fields." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ32685.pdf.

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Liu, Dianbo. "Modelling biological networks : topology, dynamics and generation." Thesis, University of Dundee, 2017. https://discovery.dundee.ac.uk/en/studentTheses/8ab98533-d17f-4ea5-adb7-62b23d1e42bc.

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Books on the topic "Biological modelling"

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Mosekilde, Erik, and Ole G. Mouritsen, eds. Modelling the Dynamics of Biological Systems. Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/978-3-642-79290-8.

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Mastebroek, Henk A. K., and Johan E. Vos, eds. Plausible Neural Networks for Biological Modelling. Springer Netherlands, 2001. http://dx.doi.org/10.1007/978-94-010-0674-3.

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Sukumaran, Muralidharan. Modelling the biological activity of s.coelicolor. UMIST, 1995.

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Mastebroek, Henk A. K. Plausible Neural Networks for Biological Modelling. Springer Netherlands, 2001.

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R, Carson Ewart, ed. Mathematical modelling of dynamic biological systems. 2nd ed. Research Studies Press, 1985.

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K, Mastebroek Henk A., and Vos Johan E, eds. Plausible neural networks for biological modelling. Kluwer Academic Publishers, 2001.

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Wilkinson, Darren James. Stochastic modelling for systems biology. 2nd ed. Taylor & Francis, 2012.

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R, Mondaini, and Pardalos P. M. 1954-, eds. Mathematical modelling of biosystems. Springer, 2008.

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Baláž, Štefan. Modelling kinetics of biological activity in xenobiotics. Veda, 1990.

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Eric, Renshaw, ed. Modelling biological populations in space and time. Cambridge University Press, 1993.

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Book chapters on the topic "Biological modelling"

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Tjelmeland, Sigurd, and Bjarte Bogstad. "Biological Modelling." In Contributions to Economics. Physica-Verlag HD, 1998. http://dx.doi.org/10.1007/978-3-642-99793-8_3.

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Maurer, Richard I., and Christopher A. Reynolds. "Modelling biological systems." In Chemical Modelling. Royal Society of Chemistry, 2007. http://dx.doi.org/10.1039/9781847553317-00199.

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Deakin, Michael A. B. "Modelling Biological Systems." In Dynamics of Complex Interconnected Biological Systems. Birkhäuser Boston, 1990. http://dx.doi.org/10.1007/978-1-4684-6784-0_1.

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Cotton-Barratt, Rebecca, and Markus Kirkilionis. "Modelling Biological Form." In Proceedings of the European Conference on Complex Systems 2012. Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-00395-5_64.

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Kaandorp, Jaap A. "Methods for Modelling Biological Objects." In Fractal Modelling. Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/978-3-642-57922-6_2.

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Kraus, Michael, and Bernhard Wolf. "Summary and Outlook." In Structured Biological Modelling. CRC Press, 2024. http://dx.doi.org/10.1201/9781003574279-9.

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Kraus, Michael, and Bernhard Wolf. "SBM Applied to Intracellular Ca2+ Oscillations." In Structured Biological Modelling. CRC Press, 2024. http://dx.doi.org/10.1201/9781003574279-6.

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Kraus, Michael, and Bernhard Wolf. "Emergence of Self-Organization in Tumor Biology." In Structured Biological Modelling. CRC Press, 2024. http://dx.doi.org/10.1201/9781003574279-8.

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Kraus, Michael, and Bernhard Wolf. "The SBM Cycle." In Structured Biological Modelling. CRC Press, 2024. http://dx.doi.org/10.1201/9781003574279-5.

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Kraus, Michael, and Bernhard Wolf. "Minimal Model of the Cellular Signal Transduction Network." In Structured Biological Modelling. CRC Press, 2024. http://dx.doi.org/10.1201/9781003574279-7.

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Conference papers on the topic "Biological modelling"

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Rock, Alan, Xiaoshu Xu, and Jerald E. Jones. "Typical Neural Network Applications in Signal Processing and Process Modelling." In CORROSION 1992. NACE International, 1992. https://doi.org/10.5006/c1992-92265.

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Abstract Artificial neural systems (ANS), also known as neural networks, are an attempt to develop computer systems that emulate the neural reasoning behavior of biological neural systems (e.g. the human brain). As such, they are loosely based on biological neural networks. The ANS consists of a series of nodes (neurons) and weighted connections (axons) that, when presented with a specific input pattern, can associate specific output patterns. It is essentially a highly complex, non-linear, mathematical relationship or transform. These constructs have two significant properties that have prove
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STOOP, RUEDI, and STEFANO LECCHINI. "BIOLOGICAL NEURAL NETWORKS: MODELING AND MEASUREMENTS." In Modelling Biomedical Signals. WORLD SCIENTIFIC, 2002. http://dx.doi.org/10.1142/9789812778055_0009.

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Abdullah, Shaikh. "Dispersion modelling for biological threat." In 2015 12th International Bhurban Conference on Applied Sciences and Technology (IBCAST). IEEE, 2015. http://dx.doi.org/10.1109/ibcast.2015.7058488.

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Tregubov, Vladimir, and Gerasim Krivovichev. "Mathematical modelling of biological mobility." In 2014 International Conference on Computer Technologies in Physical and Engineering Applications (ICCTPEA). IEEE, 2014. http://dx.doi.org/10.1109/icctpea.2014.6893353.

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Tregubov, Vladimir. "Mathematical modelling of biological liquids." In 2014 International Conference on Computer Technologies in Physical and Engineering Applications (ICCTPEA). IEEE, 2014. http://dx.doi.org/10.1109/icctpea.2014.6893354.

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Schnase, J. L., and J. J. Leggett. "Computational hypertext in biological modelling." In the second annual ACM conference. ACM Press, 1989. http://dx.doi.org/10.1145/74224.74240.

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Shiny, S., K. V. Shihabudheen, and Anish Gopinath. "Modelling of Biological Lower Extremity." In 2019 2nd International Conference on Intelligent Computing, Instrumentation and Control Technologies (ICICICT). IEEE, 2019. http://dx.doi.org/10.1109/icicict46008.2019.8993402.

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Fernandez, D. R., J. M. G. Chamizo, F. M. Perez, A. S. Paya, F. M. Perez, and A. S. Paya. "Robust Modelling of Biological Neuroregulators." In 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference. IEEE, 2005. http://dx.doi.org/10.1109/iembs.2005.1617100.

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Soetaert, Karline, Dick van Oevelen, Theodore E. Simos, George Psihoyios, Ch Tsitouras, and Zacharias Anastassi. "Modelling Marine Biological and Biogeochemical Data." In NUMERICAL ANALYSIS AND APPLIED MATHEMATICS ICNAAM 2011: International Conference on Numerical Analysis and Applied Mathematics. AIP, 2011. http://dx.doi.org/10.1063/1.3636664.

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Paltanea, Marius, Sabin Tabirca, Ernesc Scheiber, and Mark Tangney. "Logarithmic Growth in Biological Processes." In 2010 12th International Conference on Computer Modelling and Simulation. IEEE, 2010. http://dx.doi.org/10.1109/uksim.2010.29.

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Reports on the topic "Biological modelling"

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Комарова, Олена Володимирівна, and Альберт Армаїсович Азарян. Computer Simulation of Biological Processes at the High School. CEUR Workshop Proceedings (CEUR-WS.org), 2018. http://dx.doi.org/10.31812/123456789/2695.

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Abstract. Research goals: the necessity of study in high school of the law of Hardy – Weinberg as one of the fundamental genetic laws was justified. The peculiarities of using the method of model experiment in the study of the genetic and evolutionary processes in populations with the use of computer technology. Object of research: computer simulation of population genetic structure. Subject of research: computer simulation of genetic and evolutionary processes in ideal and real populations. Research methods: pedagogical experiment (survey), analysis of scientific publications on the use of th
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Комарова, Олена Володимирівна, and Альберт Арамаїсович Азарян. Computer Simulation of Biological Processes at the High School. CEUR-WS.org, 2018. http://dx.doi.org/10.31812/123456789/2656.

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Research goals: the necessity of study in high school of the law of Hardy – Weinberg as one of the fundamental genetic laws was justified. The peculiarities of using the method of model experiment in the study of the genetic and evolutionary processes in populations with the use of computer technology. Object of research: computer simulation of population genetic structure. Subject of research: computer simulation of genetic and evolutionary processes in ideal and real populations. Research methods: pedagogical experiment (survey), analysis of scientific publications on the use of the high sch
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Schartau, Markus, Tronje Peer Kemena, Vanessa Lampe, Jan Taucher, and Miriam Seifert. New/refined parameterizations for modelling ocean alkalinization effects on biogeochemistry and plankton dynamics. OceanNets, 2024. http://dx.doi.org/10.3289/oceannets_d5.8.

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In this report the potential effects of pulsed ocean alkalinity enhancement (OAE) on plankton growth dynamics, efficacy and carbon dioxide removal (CDR) are simulated at an oligotrophic site nearby the Canary Islands (Spain). Parameterizations of how phytoplankton and bacterial growth respond to variations in carbonate chemistry are introduced and applied. The model resolves vertical profiles within a 420 km2 area of OAE, and within a 2.05×105 km2 surrounding region. Both areas are connected and lateral dispersion causes a horizontal exchange of chemical and biological tracers. The analysis co
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Savosko, V., I. Komarova, Yu Lykholat, E. Yevtushenko, and T. Lykholat. Predictive model of heavy metals inputs to soil at Kryvyi Rih District and its use in the training for specialists in the field of Biology. IOP Publishing, 2021. http://dx.doi.org/10.31812/123456789/4511.

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The importance of our research is due to the need to introduce into modern biological education methods of predictive modeling which are based on relevant factual material. Such an actual material may be the entry of natural and anthropic heavy metals into the soil at industrial areas. The object of this work: (i) to work out a predictive model of the total heavy metals inputs to soil at the Kryvyi Rih ore-mining & metallurgical District and (ii) to identify ways to use this model in biological education. Our study areas are located in the Kryvyi Rih District (Dnipropetrovsk region, Centra
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Савосько, Василь Миколайович, Ірина Олександрівна Комарова, Юрій Васильович Лихолат, Едуард Олексійович Євтушенко,, and Тетяна Юріївна Лихолат. Predictive Model of Heavy Metals Inputs to Soil at Kryvyi Rih District and its Use in the Training for Specialists in the Field of Biology. IOP Publishing, 2021. http://dx.doi.org/10.31812/123456789/4266.

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The importance of our research is due to the need to introduce into modern biological education methods of predictive modeling which are based on relevant factual material. Such an actual material may be the entry of natural and anthropic heavy metals into the soil at industrial areas. The object of this work: (i) to work out a predictive model of the total heavy metals inputs to soil at the Kryvyi Rih ore-mining & metallurgical District and (ii) to identify ways to use this model in biological education. Our study areas are located in the Kryvyi Rih District (Dnipropetrovsk region, Centra
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Burkimsher, Marion. Modelling biological birth order and comparison with census parity data in Switzerland: a report to complement the Swiss data in the Human Fertility Collection (HFC). Max Planck Institute for Demographic Research, 2011. http://dx.doi.org/10.4054/mpidr-tr-2011-005.

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Sundelöf, Andreas, Massimilliano Cardinale, Hege Sande, Emmelie Hammenstig-Åström, and Henrik Pärn. Benchmark of European Lobster (Homarus gammarus) in Swedish areas of Skagerrak, Kattegat and Öresund : stock annex. Department of Aquatic Resources, Swedish University of Agricultural Science, 2025. https://doi.org/10.54612/a.4l1lrggjfs.

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This report summarizes the process of conducting a benchmark for the assessment of European lobster in the Swedish coastal areas of the Skagerrak, Kattegat and Öresund. Catch data, survey indices, commercial catch per unit of effort and life history data, on which the assessment is based on, are described in summary in the report and in detailed form in the attached appendices. Furthermore, the report summarizes the model structure and the sensitivity analyses done to generate an ensemble model that can be used to estimate the stock status of the lobster stock and provide advice. The current a
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Taucher, Jan, and Markus Schartau. Report on parameterizing seasonal response patterns in primary- and net community production to ocean alkalinization. OceanNETs, 2021. http://dx.doi.org/10.3289/oceannets_d5.2.

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We applied a 1-D plankton ecosystem-biogeochemical model to assess the impacts of ocean alkalinity enhancement (OAE) on seasonal changes in biogeochemistry and plankton dynamics. Depending on deployment scenarios, OAE should theoretically have variable effects on pH and seawater pCO2, which might in turn affect (a) plankton growth conditions and (b) the efficiency of carbon dioxide removal (CDR) via OAE. Thus, a major focus of our work is how different magnitudes and temporal frequencies of OAE might affect seasonal response patterns of net primary productivity (NPP), ecosystem functioning and
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Taucher, Jan, and Markus Schartau. Report on parameterizing seasonal response patterns in primary- and net community production to ocean alkalinization. OceanNETs, 2021. http://dx.doi.org/10.3289/oceannets_d5.3.

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We applied a 1-D plankton ecosystem-biogeochemical model to assess the impacts of ocean alkalinity enhancement (OAE) on seasonal changes in biogeochemistry and plankton dynamics. Depending on deployment scenarios, OAE should theoretically have variable effects on pH and seawater pCO2, which might in turn affect (a) plankton growth conditions and (b) the efficiency of carbon dioxide removal (CDR) via OAE. Thus, a major focus of our work is how different magnitudes and temporal frequencies of OAE might affect seasonal response patterns of net primary productivity (NPP), ecosystem functioning and
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