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Sample records for biologically based models

  1. Instance-Based Generative Biological Shape Modeling.

    Science.gov (United States)

    Peng, Tao; Wang, Wei; Rohde, Gustavo K; Murphy, Robert F

    2009-01-01

    Biological shape modeling is an essential task that is required for systems biology efforts to simulate complex cell behaviors. Statistical learning methods have been used to build generative shape models based on reconstructive shape parameters extracted from microscope image collections. However, such parametric modeling approaches are usually limited to simple shapes and easily-modeled parameter distributions. Moreover, to maximize the reconstruction accuracy, significant effort is required to design models for specific datasets or patterns. We have therefore developed an instance-based approach to model biological shapes within a shape space built upon diffeomorphic measurement. We also designed a recursive interpolation algorithm to probabilistically synthesize new shape instances using the shape space model and the original instances. The method is quite generalizable and therefore can be applied to most nuclear, cell and protein object shapes, in both 2D and 3D.

  2. Agent-based modelling in synthetic biology.

    Science.gov (United States)

    Gorochowski, Thomas E

    2016-11-30

    Biological systems exhibit complex behaviours that emerge at many different levels of organization. These span the regulation of gene expression within single cells to the use of quorum sensing to co-ordinate the action of entire bacterial colonies. Synthetic biology aims to make the engineering of biology easier, offering an opportunity to control natural systems and develop new synthetic systems with useful prescribed behaviours. However, in many cases, it is not understood how individual cells should be programmed to ensure the emergence of a required collective behaviour. Agent-based modelling aims to tackle this problem, offering a framework in which to simulate such systems and explore cellular design rules. In this article, I review the use of agent-based models in synthetic biology, outline the available computational tools, and provide details on recently engineered biological systems that are amenable to this approach. I further highlight the challenges facing this methodology and some of the potential future directions. © 2016 The Author(s).

  3. Biologically based multistage modeling of radiation effects

    Energy Technology Data Exchange (ETDEWEB)

    William Hazelton; Suresh Moolgavkar; E. Georg Luebeck

    2005-08-30

    This past year we have made substantial progress in modeling the contribution of homeostatic regulation to low-dose radiation effects and carcinogenesis. We have worked to refine and apply our multistage carcinogenesis models to explicitly incorporate cell cycle states, simple and complex damage, checkpoint delay, slow and fast repair, differentiation, and apoptosis to study the effects of low-dose ionizing radiation in mouse intestinal crypts, as well as in other tissues. We have one paper accepted for publication in ''Advances in Space Research'', and another manuscript in preparation describing this work. I also wrote a chapter describing our combined cell-cycle and multistage carcinogenesis model that will be published in a book on stochastic carcinogenesis models edited by Wei-Yuan Tan. In addition, we organized and held a workshop on ''Biologically Based Modeling of Human Health Effects of Low dose Ionizing Radiation'', July 28-29, 2005 at Fred Hutchinson Cancer Research Center in Seattle, Washington. We had over 20 participants, including Mary Helen Barcellos-Hoff as keynote speaker, talks by most of the low-dose modelers in the DOE low-dose program, experimentalists including Les Redpath (and Mary Helen), Noelle Metting from DOE, and Tony Brooks. It appears that homeostatic regulation may be central to understanding low-dose radiation phenomena. The primary effects of ionizing radiation (IR) are cell killing, delayed cell cycling, and induction of mutations. However, homeostatic regulation causes cells that are killed or damaged by IR to eventually be replaced. Cells with an initiating mutation may have a replacement advantage, leading to clonal expansion of these initiated cells. Thus we have focused particularly on modeling effects that disturb homeostatic regulation as early steps in the carcinogenic process. There are two primary considerations that support our focus on homeostatic regulation. First, a number of

  4. Network-Based Models in Molecular Biology

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    Beyer, Andreas

    Biological systems are characterized by a large number of diverse interactions. Interaction maps have been used to abstract those interactions at all biological scales ranging from food webs at the ecosystem level down to protein interaction networks at the molecular scale.

  5. A Color-Opponency Based Biological Model for Color Constancy

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    Yongjie Li

    2011-05-01

    Full Text Available Color constancy is the ability of the human visual system to adaptively correct color-biased scenes under different illuminants. Most of the existing color constancy models are nonphysiologically plausible. Among the limited biological models, the great majority is Retinex and its variations, and only two or three models directly simulate the feature of color-opponency, but only of the very earliest stages of visual pathway, i.e., the single-opponent mechanisms involved at the levels of retinal ganglion cells and lateral geniculate nucleus (LGN neurons. Considering the extensive physiological evidences supporting that both the single-opponent cells in retina and LGN and the double-opponent neurons in primary visual cortex (V1 are the building blocks for color constancy, in this study we construct a color-opponency based color constancy model by simulating the opponent fashions of both the single-opponent and double-opponent cells in a forward manner. As for the spatial structure of the receptive fields (RF, both the classical RF (CRF center and the nonclassical RF (nCRF surround are taken into account for all the cells. The proposed model was tested on several typical image databases commonly used for performance evaluation of color constancy methods, and exciting results were achieved.

  6. Biology Based Lung Cancer Model for Chronic Low Radon Exposures

    International Nuclear Information System (INIS)

    Truta-Popa, Lucia-Adina; Hofmann, Werner; Fakir, Hatim; Cosma, Constantin

    2008-01-01

    Low dose effects of alpha particles at the tissue level are characterized by the interaction of single alpha particles, affecting only a small fraction of the cells within that tissue. Alpha particle intersections of bronchial target cells during a given exposure period were simulated by an initiation-promotion model, formulated in terms of cellular hits within the cycle time of the cell (dose-rate) and then integrated over the whole exposure period (dose). For a given average number of cellular hits during the lifetime of bronchial cells, the actual number of single and multiple hits was selected from a Poisson distribution. While oncogenic transformation is interpreted as the primary initiation step, stimulated mitosis by killing adjacent cells is assumed to be the primary radiological promotion event. Analytical initiation and promotion functions were derived from experimental in vitro data on oncogenic transformation and cellular survival.To investigate the shape of the lung cancer risk function at chronic, low level exposures in more detail, additional biological factors describing the tissue response and operating specifically at low doses were incorporated into the initiation-promotion model. These mechanisms modifying the initial response at the cellular level were: adaptive response, genomic instability, induction of apoptosis by surrounding cells, and detrimental as well as protective bystander mechanisms. To quantify the effects of these mechanisms as functions of dose, analytical functions were derived from the experimental evidence presently available. Predictions of lung cancer risk, including these mechanisms, exhibit a distinct sublinear dose-response relationship at low exposures, particularly for very low exposure rates

  7. Evaluation and modeling of HIV based on communication theory in biological systems.

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    Dong, Miaowu; Li, Wenrong; Xu, Xi

    2016-12-01

    Some forms of communication are used in biological systems such as HIV transmission in human beings. In this paper, we plan to get a unique insight into biological communication systems generally through the analogy between HIV infection and electrical communication system. The model established in this paper can be used to test and simulate various communication systems since it provides researchers with an opportunity. We interpret biological communication systems by using telecommunications exemplification from a layered communication protocol developed before and use the model to indicate HIV spreading. We also implement a simulation of HIV infection based on the layered communication protocol to predict the development of this disease and the results prove the validity of the model. Copyright © 2016 Elsevier B.V. All rights reserved.

  8. Biologically-based mechanistic models of radiation-related carcinogenesis applied to epidemiological data.

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    Rühm, Werner; Eidemüller, Markus; Kaiser, Jan Christian

    2017-10-01

    Biologically-based mechanistic models that are used in combining current understanding of human carcinogenesis with epidemiological studies were reviewed. Assessment was made of how well they fit the data, whether they account for non-linear radiobiological low-dose effects, and whether they suggest any implications for the dose response at low doses and dose rates. However, the present paper does not make an attempt to provide a complete review of the existing literature on biologically-based models and their application to epidemiological data. In most studies the two-stage clonal expansion (TSCE) model of carcinogenesis was used. The model provided robust estimates of identifiable parameters and radiation risk. While relatively simple, it is flexible, so that more stages can easily be added, and tests made of various types of radiation action. In general, the model performed similarly or better than descriptive excess absolute and excess relative risk models, in terms of quality of fit and number of parameters. Only very rarely the shape of dose-response predicted by the models was investigated. For some tumors, when more detailed biological information was known, additional pathways were included in the model. The future development of these models will benefit from growing knowledge on carcinogenesis processes, and in particular from use of biobank tissue samples and advances in omics technologies. Their use appears a promising approach to investigate the radiation risk at low doses and low dose rates. However, the uncertainties involved are still considerable, and the models provide only a simplified description of the underlying complexity of carcinogenesis. Current assumptions in radiation protection including the linear-non-threshold (LNT) model are not in contradiction to what is presently known on the process of cancer development.

  9. Simulation on scattering features of biological tissue based on generated refractive-index model

    International Nuclear Information System (INIS)

    Wang Baoyong; Ding Zhihua

    2011-01-01

    Important information on morphology of biological tissue can be deduced from elastic scattering spectra, and their analyses are based on the known refractive-index model of tissue. In this paper, a new numerical refractive-index model is put forward, and its scattering properties are intensively studied. Spectral decomposition [1] is a widely used method to generate random medium in geology, but it is never used in biology. Biological tissue is different from geology in the sense of random medium. Autocorrelation function describe almost all of features in geology, but biological tissue is not as random as geology, its structure is regular in the sense of fractal geometry [2] , and fractal dimension can be used to describe its regularity under random. Firstly scattering theories of this fractal media are reviewed. Secondly the detailed generation process of refractive-index is presented. Finally the scattering features are simulated in FDTD (Finite Difference Time Domain) Solutions software. From the simulation results, we find that autocorrelation length and fractal dimension controls scattering feature of biological tissue.

  10. Simulation on scattering features of biological tissue based on generated refractive-index model

    Energy Technology Data Exchange (ETDEWEB)

    Wang Baoyong; Ding Zhihua, E-mail: zh_ding@zju.edu.cn [State Key Lab of Modern Optical Instrumentation, Zhejiang University 38 Zheda Rd., Hangzhou 310027 (China)

    2011-01-01

    Important information on morphology of biological tissue can be deduced from elastic scattering spectra, and their analyses are based on the known refractive-index model of tissue. In this paper, a new numerical refractive-index model is put forward, and its scattering properties are intensively studied. Spectral decomposition{sup [1]} is a widely used method to generate random medium in geology, but it is never used in biology. Biological tissue is different from geology in the sense of random medium. Autocorrelation function describe almost all of features in geology, but biological tissue is not as random as geology, its structure is regular in the sense of fractal geometry{sup [2]}, and fractal dimension can be used to describe its regularity under random. Firstly scattering theories of this fractal media are reviewed. Secondly the detailed generation process of refractive-index is presented. Finally the scattering features are simulated in FDTD (Finite Difference Time Domain) Solutions software. From the simulation results, we find that autocorrelation length and fractal dimension controls scattering feature of biological tissue.

  11. A phenomenological biological dose model for proton therapy based on linear energy transfer spectra.

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    Rørvik, Eivind; Thörnqvist, Sara; Stokkevåg, Camilla H; Dahle, Tordis J; Fjaera, Lars Fredrik; Ytre-Hauge, Kristian S

    2017-06-01

    The relative biological effectiveness (RBE) of protons varies with the radiation quality, quantified by the linear energy transfer (LET). Most phenomenological models employ a linear dependency of the dose-averaged LET (LET d ) to calculate the biological dose. However, several experiments have indicated a possible non-linear trend. Our aim was to investigate if biological dose models including non-linear LET dependencies should be considered, by introducing a LET spectrum based dose model. The RBE-LET relationship was investigated by fitting of polynomials from 1st to 5th degree to a database of 85 data points from aerobic in vitro experiments. We included both unweighted and weighted regression, the latter taking into account experimental uncertainties. Statistical testing was performed to decide whether higher degree polynomials provided better fits to the data as compared to lower degrees. The newly developed models were compared to three published LET d based models for a simulated spread out Bragg peak (SOBP) scenario. The statistical analysis of the weighted regression analysis favored a non-linear RBE-LET relationship, with the quartic polynomial found to best represent the experimental data (P = 0.010). The results of the unweighted regression analysis were on the borderline of statistical significance for non-linear functions (P = 0.053), and with the current database a linear dependency could not be rejected. For the SOBP scenario, the weighted non-linear model estimated a similar mean RBE value (1.14) compared to the three established models (1.13-1.17). The unweighted model calculated a considerably higher RBE value (1.22). The analysis indicated that non-linear models could give a better representation of the RBE-LET relationship. However, this is not decisive, as inclusion of the experimental uncertainties in the regression analysis had a significant impact on the determination and ranking of the models. As differences between the models were

  12. Fractional Calculus-Based Modeling of Electromagnetic Field Propagation in Arbitrary Biological Tissue

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    Pietro Bia

    2016-01-01

    Full Text Available The interaction of electromagnetic fields and biological tissues has become a topic of increasing interest for new research activities in bioelectrics, a new interdisciplinary field combining knowledge of electromagnetic theory, modeling, and simulations, physics, material science, cell biology, and medicine. In particular, the feasibility of pulsed electromagnetic fields in RF and mm-wave frequency range has been investigated with the objective to discover new noninvasive techniques in healthcare. The aim of this contribution is to illustrate a novel Finite-Difference Time-Domain (FDTD scheme for simulating electromagnetic pulse propagation in arbitrary dispersive biological media. The proposed method is based on the fractional calculus theory and a general series expansion of the permittivity function. The spatial dispersion effects are taken into account, too. The resulting formulation is explicit, it has a second-order accuracy, and the need for additional storage variables is minimal. The comparison between simulation results and those evaluated by using an analytical method based on the Fourier transformation demonstrates the accuracy and effectiveness of the developed FDTD model. Five numerical examples showing the plane wave propagation in a variety of dispersive media are examined.

  13. BSim: an agent-based tool for modeling bacterial populations in systems and synthetic biology.

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    Thomas E Gorochowski

    Full Text Available Large-scale collective behaviors such as synchronization and coordination spontaneously arise in many bacterial populations. With systems biology attempting to understand these phenomena, and synthetic biology opening up the possibility of engineering them for our own benefit, there is growing interest in how bacterial populations are best modeled. Here we introduce BSim, a highly flexible agent-based computational tool for analyzing the relationships between single-cell dynamics and population level features. BSim includes reference implementations of many bacterial traits to enable the quick development of new models partially built from existing ones. Unlike existing modeling tools, BSim fully considers spatial aspects of a model allowing for the description of intricate micro-scale structures, enabling the modeling of bacterial behavior in more realistic three-dimensional, complex environments. The new opportunities that BSim opens are illustrated through several diverse examples covering: spatial multicellular computing, modeling complex environments, population dynamics of the lac operon, and the synchronization of genetic oscillators. BSim is open source software that is freely available from http://bsim-bccs.sf.net and distributed under the Open Source Initiative (OSI recognized MIT license. Developer documentation and a wide range of example simulations are also available from the website. BSim requires Java version 1.6 or higher.

  14. A logic-based dynamic modeling approach to explicate the evolution of the central dogma of molecular biology.

    Science.gov (United States)

    Jafari, Mohieddin; Ansari-Pour, Naser; Azimzadeh, Sadegh; Mirzaie, Mehdi

    It is nearly half a century past the age of the introduction of the Central Dogma (CD) of molecular biology. This biological axiom has been developed and currently appears to be all the more complex. In this study, we modified CD by adding further species to the CD information flow and mathematically expressed CD within a dynamic framework by using Boolean network based on its present-day and 1965 editions. We show that the enhancement of the Dogma not only now entails a higher level of complexity, but it also shows a higher level of robustness, thus far more consistent with the nature of biological systems. Using this mathematical modeling approach, we put forward a logic-based expression of our conceptual view of molecular biology. Finally, we show that such biological concepts can be converted into dynamic mathematical models using a logic-based approach and thus may be useful as a framework for improving static conceptual models in biology.

  15. A Comprehensive Web-based Platform For Domain-Specific Biological Models

    Czech Academy of Sciences Publication Activity Database

    Klement, M.; Šafránek, D.; Děd, J.; Pejznoch, A.; Nedbal, Ladislav; Steuer, Ralf; Červený, Jan; Müller, Stefan

    2013-01-01

    Roč. 299, 25 Dec (2013), s. 61-67 ISSN 1571-0661 R&D Projects: GA MŠk(CZ) EE2.3.20.0256 Institutional support: RVO:67179843 Keywords : biological models * model annotation * systems biology * simulation * database Subject RIV: EH - Ecology, Behaviour

  16. Fractional Calculus Based FDTD Modeling of Layered Biological Media Exposure to Wideband Electromagnetic Pulses

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    Luciano Mescia

    2017-11-01

    Full Text Available Electromagnetic fields are involved in several therapeutic and diagnostic applications such as hyperthermia and electroporation. For these applications, pulsed electric fields (PEFs and transient phenomena are playing a key role for understanding the biological response due to the exposure to non-ionizing wideband pulses. To this end, the PEF propagation in the six-layered planar structure modeling the human head has been studied. The electromagnetic field and the specific absorption rate (SAR have been calculated through an accurate finite-difference time-domain (FDTD dispersive modeling based on the fractional derivative operator. The temperature rise inside the tissues due to the electromagnetic field exposure has been evaluated using both the non-thermoregulated and thermoregulated Gagge’s two-node models. Moreover, additional parametric studies have been carried out with the aim to investigate the thermal response by changing the amplitude and duration of the electric pulses.

  17. Laboratory of Biological Modeling

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    Federal Laboratory Consortium — The Laboratory of Biological Modeling is defined by both its methodologies and its areas of application. We use mathematical modeling in many forms and apply it to a...

  18. From Levy to Brownian: a computational model based on biological fluctuation.

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    Surya G Nurzaman

    Full Text Available BACKGROUND: Theoretical studies predict that Lévy walks maximizes the chance of encountering randomly distributed targets with a low density, but Brownian walks is favorable inside a patch of targets with high density. Recently, experimental data reports that some animals indeed show a Lévy and Brownian walk movement patterns when forage for foods in areas with low and high density. This paper presents a simple, Gaussian-noise utilizing computational model that can realize such behavior. METHODOLOGY/PRINCIPAL FINDINGS: We extend Lévy walks model of one of the simplest creature, Escherichia coli, based on biological fluctuation framework. We build a simulation of a simple, generic animal to observe whether Lévy or Brownian walks will be performed properly depends on the target density, and investigate the emergent behavior in a commonly faced patchy environment where the density alternates. CONCLUSIONS/SIGNIFICANCE: Based on the model, animal behavior of choosing Lévy or Brownian walk movement patterns based on the target density is able to be generated, without changing the essence of the stochastic property in Escherichia coli physiological mechanism as explained by related researches. The emergent behavior and its benefits in a patchy environment are also discussed. The model provides a framework for further investigation on the role of internal noise in realizing adaptive and efficient foraging behavior.

  19. Comparative systems biology between human and animal models based on next-generation sequencing methods.

    Science.gov (United States)

    Zhao, Yu-Qi; Li, Gong-Hua; Huang, Jing-Fei

    2013-04-01

    Animal models provide myriad benefits to both experimental and clinical research. Unfortunately, in many situations, they fall short of expected results or provide contradictory results. In part, this can be the result of traditional molecular biological approaches that are relatively inefficient in elucidating underlying molecular mechanism. To improve the efficacy of animal models, a technological breakthrough is required. The growing availability and application of the high-throughput methods make systematic comparisons between human and animal models easier to perform. In the present study, we introduce the concept of the comparative systems biology, which we define as "comparisons of biological systems in different states or species used to achieve an integrated understanding of life forms with all their characteristic complexity of interactions at multiple levels". Furthermore, we discuss the applications of RNA-seq and ChIP-seq technologies to comparative systems biology between human and animal models and assess the potential applications for this approach in the future studies.

  20. The ASM-NSF Biology Scholars Program: An Evidence-Based Model for Faculty Development

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    Amy L. Chang

    2016-05-01

    Full Text Available The American Society for Microbiology (ASM established its ASM-NSF (National Science Foundation Biology Scholars Program (BSP to promote undergraduate education reform by 1 supporting biologists to implement evidence-based teaching practices, 2 engaging life science professional societies to facilitate biologists’ leadership in scholarly teaching within the discipline, and 3 participating in a teaching community that fosters disciplinary-level science, technology, engineering, and mathematics (STEM reform. Since 2005, the program has utilized year-long residency training to provide a continuum of learning and practice centered on principles from the scholarship of teaching and learning (SoTL to more than 270 participants (“scholars” from biology and multiple other disciplines. Additionally, the program has recruited 11 life science professional societies to support faculty development in SoTL and discipline-based education research (DBER. To identify the BSP’s long-term outcomes and impacts, ASM engaged an external evaluator to conduct a study of the program’s 2010­–2014 scholars (n = 127 and society partners. The study methods included online surveys, focus groups, participant observation, and analysis of various documents. Study participants indicate that the program achieved its proposed goals relative to scholarship, professional society impact, leadership, community, and faculty professional development. Although participants also identified barriers that hindered elements of their BSP participation, findings suggest that the program was essential to their development as faculty and provides evidence of the BSP as a model for other societies seeking to advance undergraduate science education reform. The BSP is the longest-standing faculty development program sponsored by a collective group of life science societies. This collaboration promotes success across a fragmented system of more than 80 societies representing the life

  1. The ASM-NSF Biology Scholars Program: An Evidence-Based Model for Faculty Development.

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    Chang, Amy L; Pribbenow, Christine M

    2016-05-01

    The American Society for Microbiology (ASM) established its ASM-NSF (National Science Foundation) Biology Scholars Program (BSP) to promote undergraduate education reform by 1) supporting biologists to implement evidence-based teaching practices, 2) engaging life science professional societies to facilitate biologists' leadership in scholarly teaching within the discipline, and 3) participating in a teaching community that fosters disciplinary-level science, technology, engineering, and mathematics (STEM) reform. Since 2005, the program has utilized year-long residency training to provide a continuum of learning and practice centered on principles from the scholarship of teaching and learning (SoTL) to more than 270 participants ("scholars") from biology and multiple other disciplines. Additionally, the program has recruited 11 life science professional societies to support faculty development in SoTL and discipline-based education research (DBER). To identify the BSP's long-term outcomes and impacts, ASM engaged an external evaluator to conduct a study of the program's 2010-2014 scholars (n = 127) and society partners. The study methods included online surveys, focus groups, participant observation, and analysis of various documents. Study participants indicate that the program achieved its proposed goals relative to scholarship, professional society impact, leadership, community, and faculty professional development. Although participants also identified barriers that hindered elements of their BSP participation, findings suggest that the program was essential to their development as faculty and provides evidence of the BSP as a model for other societies seeking to advance undergraduate science education reform. The BSP is the longest-standing faculty development program sponsored by a collective group of life science societies. This collaboration promotes success across a fragmented system of more than 80 societies representing the life sciences and helps

  2. Trait-based representation of biological nitrification: Model development, testing, and predicted community composition

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    Nick eBouskill

    2012-10-01

    Full Text Available Trait-based microbial models show clear promise as tools to represent the diversity and activity of microorganisms across ecosystem gradients. These models parameterize specific traits that determine the relative fitness of an ‘organism’ in a given environment, and represent the complexity of biological systems across temporal and spatial scales. In this study we introduce a microbial community trait-based modeling framework (MicroTrait focused on nitrification (MicroTrait-N that represents the ammonia-oxidizing bacteria (AOB and ammonia-oxidizing archaea (AOA and nitrite oxidizing bacteria (NOB using traits related to enzyme kinetics and physiological properties. We used this model to predict nitrifier diversity, ammonia (NH3 oxidation rates and nitrous oxide (N2O production across pH, temperature and substrate gradients. Predicted nitrifier diversity was predominantly determined by temperature and substrate availability, the latter was strongly influenced by pH. The model predicted that transient N2O production rates are maximized by a decoupling of the AOB and NOB communities, resulting in an accumulation and detoxification of nitrite to N2O by AOB. However, cumulative N2O production (over six month simulations is maximized in a system where the relationship between AOB and NOB is maintained. When the reactions uncouple, the AOB become unstable and biomass declines rapidly, resulting in decreased NH3 oxidation and N2O production. We evaluated this model against site level chemical datasets from the interior of Alaska and accurately simulated NH3 oxidation rates and the relative ratio of AOA:AOB biomass. The predicted community structure and activity indicate (a parameterization of a small number of traits may be sufficient to broadly characterize nitrifying community structure and (b changing decadal trends in climate and edaphic conditions could impact nitrification rates in ways that are not captured by extant biogeochemical models.

  3. A Bayesian spatial model for neuroimaging data based on biologically informed basis functions.

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    Huertas, Ismael; Oldehinkel, Marianne; van Oort, Erik S B; Garcia-Solis, David; Mir, Pablo; Beckmann, Christian F; Marquand, Andre F

    2017-11-01

    The dominant approach to neuroimaging data analysis employs the voxel as the unit of computation. While convenient, voxels lack biological meaning and their size is arbitrarily determined by the resolution of the image. Here, we propose a multivariate spatial model in which neuroimaging data are characterised as a linearly weighted combination of multiscale basis functions which map onto underlying brain nuclei or networks or nuclei. In this model, the elementary building blocks are derived to reflect the functional anatomy of the brain during the resting state. This model is estimated using a Bayesian framework which accurately quantifies uncertainty and automatically finds the most accurate and parsimonious combination of basis functions describing the data. We demonstrate the utility of this framework by predicting quantitative SPECT images of striatal dopamine function and we compare a variety of basis sets including generic isotropic functions, anatomical representations of the striatum derived from structural MRI, and two different soft functional parcellations of the striatum derived from resting-state fMRI (rfMRI). We found that a combination of ∼50 multiscale functional basis functions accurately represented the striatal dopamine activity, and that functional basis functions derived from an advanced parcellation technique known as Instantaneous Connectivity Parcellation (ICP) provided the most parsimonious models of dopamine function. Importantly, functional basis functions derived from resting fMRI were more accurate than both structural and generic basis sets in representing dopamine function in the striatum for a fixed model order. We demonstrate the translational validity of our framework by constructing classification models for discriminating parkinsonian disorders and their subtypes. Here, we show that ICP approach is the only basis set that performs well across all comparisons and performs better overall than the classical voxel-based approach

  4. BClass: A Bayesian Approach Based on Mixture Models for Clustering and Classification of Heterogeneous Biological Data

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    Arturo Medrano-Soto

    2004-12-01

    Full Text Available Based on mixture models, we present a Bayesian method (called BClass to classify biological entities (e.g. genes when variables of quite heterogeneous nature are analyzed. Various statistical distributions are used to model the continuous/categorical data commonly produced by genetic experiments and large-scale genomic projects. We calculate the posterior probability of each entry to belong to each element (group in the mixture. In this way, an original set of heterogeneous variables is transformed into a set of purely homogeneous characteristics represented by the probabilities of each entry to belong to the groups. The number of groups in the analysis is controlled dynamically by rendering the groups as 'alive' and 'dormant' depending upon the number of entities classified within them. Using standard Metropolis-Hastings and Gibbs sampling algorithms, we constructed a sampler to approximate posterior moments and grouping probabilities. Since this method does not require the definition of similarity measures, it is especially suitable for data mining and knowledge discovery in biological databases. We applied BClass to classify genes in RegulonDB, a database specialized in information about the transcriptional regulation of gene expression in the bacterium Escherichia coli. The classification obtained is consistent with current knowledge and allowed prediction of missing values for a number of genes. BClass is object-oriented and fully programmed in Lisp-Stat. The output grouping probabilities are analyzed and interpreted using graphical (dynamically linked plots and query-based approaches. We discuss the advantages of using Lisp-Stat as a programming language as well as the problems we faced when the data volume increased exponentially due to the ever-growing number of genomic projects.

  5. The biological effectiveness of targeted radionuclide therapy based on a whole-body pharmacokinetic model

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    Grudzinski, Joseph J; Tomé, Wolfgang; Weichert, Jamey P; Jeraj, Robert

    2013-01-01

    Biologically effective dose (BED) may be more of a relevant quantity than absorbed dose for establishing tumour response relationships. By taking into account the dose rate and tissue-specific parameters such as repair and radiosensitivity, it is possible to compare the relative biological effects of different targeted radionuclide therapy (TRT) agents. The aim of this work was to develop an analytical tumour BED calculation for TRT that could predict a relative biological effect based on normal body and tumour pharmacokinetics. This work represents a step in the direction of establishing relative pharmacokinetic criteria of when the BED formalism is more applicable than absorbed dose for TRT. A previously established pharmacokinetic (PK) model for TRT was used and adapted into the BED formalism. An analytical equation for the protraction factor, which incorporates dose rate and repair rate, was derived. Dose rates within the normal body and tumour were related to the slopes of their time–activity curves which were determined by the ratios of their respective PK parameters. The relationships between the tumour influx-to-efflux ratio (k34:k43), central compartment efflux-to-influx ratio (k12:k21), central elimination (kel), and tumour repair rate (μ), and tumour BED were investigated. As the k34:k43 ratio increases and the k12:k21 ratio decreases, the difference between tumour BED and D increases. In contrast, as the k34:k43 ratios decrease and the k12:k21 ratios increase, the tumour BED approaches D. At large k34:k43 ratios, the difference between tumour BED and D increases to a maximum as kel increases. At small k34:k43 ratios, the tumour BED approaches D at very small kel. At small μ and small k34:k43 ratios, the tumour BED approaches D. For large k34:k43 ratios, large μ values cause tumour BED to approach D. This work represents a step in the direction of establishing relative PK criteria of when the BED formalism is more applicable than absorbed dose for

  6. Predicting biological parameters of estuarine benthic communities using models based on environmental data

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    José Souto Rosa-Filho

    2004-08-01

    Full Text Available This study aimed to predict the biological parameters (species composition, abundance, richness, diversity and evenness of benthic assemblages in southern Brazil estuaries using models based on environmental data (sediment characteristics, salinity, air and water temperature and depth. Samples were collected seasonally from five estuaries between the winter of 1996 and the summer of 1998. At each estuary, samples were taken in unpolluted areas with similar characteristics related to presence or absence of vegetation, depth and distance from the mouth. In order to obtain predictive models, two methods were used, the first one based on Multiple Discriminant Analysis (MDA, and the second based on Multiple Linear Regression (MLR. Models using MDA had better results than those based on linear regression. The best results using MLR were obtained for diversity and richness. It could be concluded that the use predictions models based on environmental data would be very useful in environmental monitoring studies in estuaries.Este trabalho objetivou predizer parâmetros da estrutura de associações macrobentônicas (composição específica, abundância, riqueza, diversidade e equitatividade em estuários do Sul do Brasil, utilizando modelos baseados em dados ambientais (características dos sedimentos, salinidade, temperaturas do ar e da água, e profundidade. As amostragens foram realizadas sazonalmente em cinco estuários entre o inverno de 1996 e o verão de 1998. Em cada estuário as amostras foram coletadas em áreas não poluídas, com características semelhantes quanto a presença ou ausência de vegetação, profundidade e distância da desenbocadura. Para a obtenção dos modelos de predição, foram utilizados dois métodos: o primeiro baseado em Análise Discriminante Múltipla (ADM e o segundo em Regressão Linear Múltipla (RLM. Os modelos baseados em ADM apresentaram resultados melhores do que os baseados em regressão linear. Os melhores

  7. Biological control of beet armyworm, Spodoptera exigua, with baculoviruses in greenhouses : development of a comprehensive process-based model

    NARCIS (Netherlands)

    Bianchi, F.J.J.A.; Vlak, J.M.; Rabbinge, R.; Werf, van der W.

    2002-01-01

    We describe the development of a comprehensive process-based model simulating the epizootiology and agronomic efficacy of baculoviruses used for biological control of beet armyworm, Spodoptera exigua, in greenhouse chrysanthemum. The model is built to help understand, evaluate, and predict the

  8. A biological-based model that links genomic instability, bystander effects, and adaptive response

    International Nuclear Information System (INIS)

    Scott, B.R.

    2004-01-01

    This paper links genomic instability, bystander effects, and adaptive response in mammalian cell communities via a novel biological-based, dose-response model called NEOTRANS 3 . The model is an extension of the NEOTRANS 2 model that addressed stochastic effects (genomic instability, mutations, and neoplastic transformation) associated with brief exposure to low radiation doses. With both models, ionizing radiation produces DNA damage in cells that can be associated with varying degrees of genomic instability. Cells with persistent problematic instability (PPI) are mutants that arise via misrepair of DNA damage. Progeny of PPI cells also have PPI and can undergo spontaneous neoplastic transformation. Unlike NEOTRANS 2 , with NEOTRANS 3 newly induced mutant PPI cells and their neoplastically transformed progeny can be suppressed via our previously introduced protective apoptosis-mediated (PAM) process, which can be activated by low linear energy transfer (LET) radiation. However, with NEOTRANS 3 (which like NEOTRANS 2 involves cross-talk between nongenomically compromised [e.g., nontransformed, nonmutants] and genomically compromised [e.g., mutants, transformants, etc.] cells), it is assumed that PAM is only activated over a relatively narrow, dose-rate-dependent interval (D PAM ,D off ); where D PAM is a small stochastic activation threshold, and D off is the stochastic dose above which PAM does not occur. PAM cooperates with activated normal DNA repair and with activated normal apoptosis in guarding against genomic instability. Normal repair involves both error-free repair and misrepair components. Normal apoptosis and the error-free component of normal repair protect mammals by preventing the occurrence of mutant cells. PAM selectively removes mutant cells arising via the misrepair component of normal repair, selectively removes existing neoplastically transformed cells, and probably selectively removes other genomically compromised cells when it is activated

  9. Strategies for efficient numerical implementation of hybrid multi-scale agent-based models to describe biological systems.

    Science.gov (United States)

    Cilfone, Nicholas A; Kirschner, Denise E; Linderman, Jennifer J

    2015-03-01

    Biologically related processes operate across multiple spatiotemporal scales. For computational modeling methodologies to mimic this biological complexity, individual scale models must be linked in ways that allow for dynamic exchange of information across scales. A powerful methodology is to combine a discrete modeling approach, agent-based models (ABMs), with continuum models to form hybrid models. Hybrid multi-scale ABMs have been used to simulate emergent responses of biological systems. Here, we review two aspects of hybrid multi-scale ABMs: linking individual scale models and efficiently solving the resulting model. We discuss the computational choices associated with aspects of linking individual scale models while simultaneously maintaining model tractability. We demonstrate implementations of existing numerical methods in the context of hybrid multi-scale ABMs. Using an example model describing Mycobacterium tuberculosis infection, we show relative computational speeds of various combinations of numerical methods. Efficient linking and solution of hybrid multi-scale ABMs is key to model portability, modularity, and their use in understanding biological phenomena at a systems level.

  10. A logic-based dynamic modeling approach to explicate the evolution of the central dogma of molecular biology.

    Directory of Open Access Journals (Sweden)

    Mohieddin Jafari

    Full Text Available It is nearly half a century past the age of the introduction of the Central Dogma (CD of molecular biology. This biological axiom has been developed and currently appears to be all the more complex. In this study, we modified CD by adding further species to the CD information flow and mathematically expressed CD within a dynamic framework by using Boolean network based on its present-day and 1965 editions. We show that the enhancement of the Dogma not only now entails a higher level of complexity, but it also shows a higher level of robustness, thus far more consistent with the nature of biological systems. Using this mathematical modeling approach, we put forward a logic-based expression of our conceptual view of molecular biology. Finally, we show that such biological concepts can be converted into dynamic mathematical models using a logic-based approach and thus may be useful as a framework for improving static conceptual models in biology.

  11. Dynamic neuronal ensembles: Issues in representing structure change in object-oriented, biologically-based brain models

    Energy Technology Data Exchange (ETDEWEB)

    Vahie, S.; Zeigler, B.P.; Cho, H. [Univ. of Arizona, Tucson, AZ (United States)

    1996-12-31

    This paper describes the structure of dynamic neuronal ensembles (DNEs). DNEs represent a new paradigm for learning, based on biological neural networks that use variable structures. We present a computational neural element that demonstrates biological neuron functionality such as neurotransmitter feedback absolute refractory period and multiple output potentials. More specifically, we will develop a network of neural elements that have the ability to dynamically strengthen, weaken, add and remove interconnections. We demonstrate that the DNE is capable of performing dynamic modifications to neuron connections and exhibiting biological neuron functionality. In addition to its applications for learning, DNEs provide an excellent environment for testing and analysis of biological neural systems. An example of habituation and hyper-sensitization in biological systems, using a neural circuit from a snail is presented and discussed. This paper provides an insight into the DNE paradigm using models developed and simulated in DEVS.

  12. Biologically based neural circuit modelling for the study of fear learning and extinction

    Science.gov (United States)

    Nair, Satish S.; Paré, Denis; Vicentic, Aleksandra

    2016-11-01

    The neuronal systems that promote protective defensive behaviours have been studied extensively using Pavlovian conditioning. In this paradigm, an initially neutral-conditioned stimulus is paired with an aversive unconditioned stimulus leading the subjects to display behavioural signs of fear. Decades of research into the neural bases of this simple behavioural paradigm uncovered that the amygdala, a complex structure comprised of several interconnected nuclei, is an essential part of the neural circuits required for the acquisition, consolidation and expression of fear memory. However, emerging evidence from the confluence of electrophysiological, tract tracing, imaging, molecular, optogenetic and chemogenetic methodologies, reveals that fear learning is mediated by multiple connections between several amygdala nuclei and their distributed targets, dynamical changes in plasticity in local circuit elements as well as neuromodulatory mechanisms that promote synaptic plasticity. To uncover these complex relations and analyse multi-modal data sets acquired from these studies, we argue that biologically realistic computational modelling, in conjunction with experiments, offers an opportunity to advance our understanding of the neural circuit mechanisms of fear learning and to address how their dysfunction may lead to maladaptive fear responses in mental disorders.

  13. Conceptual Model-based Systems Biology: mapping knowledge and discovering gaps in the mRNA transcription cycle.

    Directory of Open Access Journals (Sweden)

    Judith Somekh

    2012-12-01

    Full Text Available We propose a Conceptual Model-based Systems Biology framework for qualitative modeling, executing, and eliciting knowledge gaps in molecular biology systems. The framework is an adaptation of Object-Process Methodology (OPM, a graphical and textual executable modeling language. OPM enables concurrent representation of the system's structure-the objects that comprise the system, and behavior-how processes transform objects over time. Applying a top-down approach of recursively zooming into processes, we model a case in point-the mRNA transcription cycle. Starting with this high level cell function, we model increasingly detailed processes along with participating objects. Our modeling approach is capable of modeling molecular processes such as complex formation, localization and trafficking, molecular binding, enzymatic stimulation, and environmental intervention. At the lowest level, similar to the Gene Ontology, all biological processes boil down to three basic molecular functions: catalysis, binding/dissociation, and transporting. During modeling and execution of the mRNA transcription model, we discovered knowledge gaps, which we present and classify into various types. We also show how model execution enhances a coherent model construction. Identification and pinpointing knowledge gaps is an important feature of the framework, as it suggests where research should focus and whether conjectures about uncertain mechanisms fit into the already verified model.

  14. Agent-based re-engineering of ErbB signaling: a modeling pipeline for integrative systems biology.

    Science.gov (United States)

    Das, Arya A; Ajayakumar Darsana, T; Jacob, Elizabeth

    2017-03-01

    Experiments in systems biology are generally supported by a computational model which quantitatively estimates the parameters of the system by finding the best fit to the experiment. Mathematical models have proved to be successful in reverse engineering the system. The data generated is interpreted to understand the dynamics of the underlying phenomena. The question we have sought to answer is that - is it possible to use an agent-based approach to re-engineer a biological process, making use of the available knowledge from experimental and modelling efforts? Can the bottom-up approach benefit from the top-down exercise so as to create an integrated modelling formalism for systems biology? We propose a modelling pipeline that learns from the data given by reverse engineering, and uses it for re-engineering the system, to carry out in-silico experiments. A mathematical model that quantitatively predicts co-expression of EGFR-HER2 receptors in activation and trafficking has been taken for this study. The pipeline architecture takes cues from the population model that gives the rates of biochemical reactions, to formulate knowledge-based rules for the particle model. Agent-based simulations using these rules, support the existing facts on EGFR-HER2 dynamics. We conclude that, re-engineering models, built using the results of reverse engineering, opens up the possibility of harnessing the power pack of data which now lies scattered in literature. Virtual experiments could then become more realistic when empowered with the findings of empirical cell biology and modelling studies. Implemented on the Agent Modelling Framework developed in-house. C ++ code templates available in Supplementary material . liz.csir@gmail.com. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

  15. Proteomics-based systems biology modeling of bovine germinal vesicle stage oocyte and cumulus cell interaction.

    Directory of Open Access Journals (Sweden)

    Divyaswetha Peddinti

    Full Text Available BACKGROUND: Oocytes are the female gametes which establish the program of life after fertilization. Interactions between oocyte and the surrounding cumulus cells at germinal vesicle (GV stage are considered essential for proper maturation or 'programming' of oocytes, which is crucial for normal fertilization and embryonic development. However, despite its importance, little is known about the molecular events and pathways involved in this bidirectional communication. METHODOLOGY/PRINCIPAL FINDINGS: We used differential detergent fractionation multidimensional protein identification technology (DDF-Mud PIT on bovine GV oocyte and cumulus cells and identified 811 and 1247 proteins in GV oocyte and cumulus cells, respectively; 371 proteins were significantly differentially expressed between each cell type. Systems biology modeling, which included Gene Ontology (GO and canonical genetic pathway analysis, showed that cumulus cells have higher expression of proteins involved in cell communication, generation of precursor metabolites and energy, as well as transport than GV oocytes. Our data also suggests a hypothesis that oocytes may depend on the presence of cumulus cells to generate specific cellular signals to coordinate their growth and maturation. CONCLUSIONS/SIGNIFICANCE: Systems biology modeling of bovine oocytes and cumulus cells in the context of GO and protein interaction networks identified the signaling pathways associated with the proteins involved in cell-to-cell signaling biological process that may have implications in oocyte competence and maturation. This first comprehensive systems biology modeling of bovine oocytes and cumulus cell proteomes not only provides a foundation for signaling and cell physiology at the GV stage of oocyte development, but are also valuable for comparative studies of other stages of oocyte development at the molecular level.

  16. KiMoSys: a web-based repository of experimental data for KInetic MOdels of biological SYStems.

    Science.gov (United States)

    Costa, Rafael S; Veríssimo, André; Vinga, Susana

    2014-08-13

    The kinetic modeling of biological systems is mainly composed of three steps that proceed iteratively: model building, simulation and analysis. In the first step, it is usually required to set initial metabolite concentrations, and to assign kinetic rate laws, along with estimating parameter values using kinetic data through optimization when these are not known. Although the rapid development of high-throughput methods has generated much omics data, experimentalists present only a summary of obtained results for publication, the experimental data files are not usually submitted to any public repository, or simply not available at all. In order to automatize as much as possible the steps of building kinetic models, there is a growing requirement in the systems biology community for easily exchanging data in combination with models, which represents the main motivation of KiMoSys development. KiMoSys is a user-friendly platform that includes a public data repository of published experimental data, containing concentration data of metabolites and enzymes and flux data. It was designed to ensure data management, storage and sharing for a wider systems biology community. This community repository offers a web-based interface and upload facility to turn available data into publicly accessible, centralized and structured-format data files. Moreover, it compiles and integrates available kinetic models associated with the data.KiMoSys also integrates some tools to facilitate the kinetic model construction process of large-scale metabolic networks, especially when the systems biologists perform computational research. KiMoSys is a web-based system that integrates a public data and associated model(s) repository with computational tools, providing the systems biology community with a novel application facilitating data storage and sharing, thus supporting construction of ODE-based kinetic models and collaborative research projects.The web application implemented using Ruby

  17. Drawing-to-learn: a framework for using drawings to promote model-based reasoning in biology.

    Science.gov (United States)

    Quillin, Kim; Thomas, Stephen

    2015-03-02

    The drawing of visual representations is important for learners and scientists alike, such as the drawing of models to enable visual model-based reasoning. Yet few biology instructors recognize drawing as a teachable science process skill, as reflected by its absence in the Vision and Change report's Modeling and Simulation core competency. Further, the diffuse research on drawing can be difficult to access, synthesize, and apply to classroom practice. We have created a framework of drawing-to-learn that defines drawing, categorizes the reasons for using drawing in the biology classroom, and outlines a number of interventions that can help instructors create an environment conducive to student drawing in general and visual model-based reasoning in particular. The suggested interventions are organized to address elements of affect, visual literacy, and visual model-based reasoning, with specific examples cited for each. Further, a Blooming tool for drawing exercises is provided, as are suggestions to help instructors address possible barriers to implementing and assessing drawing-to-learn in the classroom. Overall, the goal of the framework is to increase the visibility of drawing as a skill in biology and to promote the research and implementation of best practices. © 2015 K. Quillin and S. Thomas. CBE—Life Sciences Education © 2015 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

  18. A biological network-based regularized artificial neural network model for robust phenotype prediction from gene expression data.

    Science.gov (United States)

    Kang, Tianyu; Ding, Wei; Zhang, Luoyan; Ziemek, Daniel; Zarringhalam, Kourosh

    2017-12-19

    Stratification of patient subpopulations that respond favorably to treatment or experience and adverse reaction is an essential step toward development of new personalized therapies and diagnostics. It is currently feasible to generate omic-scale biological measurements for all patients in a study, providing an opportunity for machine learning models to identify molecular markers for disease diagnosis and progression. However, the high variability of genetic background in human populations hampers the reproducibility of omic-scale markers. In this paper, we develop a biological network-based regularized artificial neural network model for prediction of phenotype from transcriptomic measurements in clinical trials. To improve model sparsity and the overall reproducibility of the model, we incorporate regularization for simultaneous shrinkage of gene sets based on active upstream regulatory mechanisms into the model. We benchmark our method against various regression, support vector machines and artificial neural network models and demonstrate the ability of our method in predicting the clinical outcomes using clinical trial data on acute rejection in kidney transplantation and response to Infliximab in ulcerative colitis. We show that integration of prior biological knowledge into the classification as developed in this paper, significantly improves the robustness and generalizability of predictions to independent datasets. We provide a Java code of our algorithm along with a parsed version of the STRING DB database. In summary, we present a method for prediction of clinical phenotypes using baseline genome-wide expression data that makes use of prior biological knowledge on gene-regulatory interactions in order to increase robustness and reproducibility of omic-scale markers. The integrated group-wise regularization methods increases the interpretability of biological signatures and gives stable performance estimates across independent test sets.

  19. Empirically based models of oceanographic and biological influences on Pacific Herring recruitment in Prince William Sound

    Science.gov (United States)

    Sewall, Fletcher; Norcross, Brenda; Mueter, Franz; Heintz, Ron

    2018-01-01

    Abundances of small pelagic fish can change dramatically over time and are difficult to forecast, partially due to variable numbers of fish that annually mature and recruit to the spawning population. Recruitment strength of age-3 Pacific Herring (Clupea pallasii) in Prince William Sound, Alaska, is estimated in an age-structured model framework as a function of spawning stock biomass via a Ricker stock-recruitment model, and forecasted using the 10-year median recruitment estimates. However, stock size has little influence on subsequent numbers of recruits. This study evaluated the usefulness of herring recruitment models that incorporate oceanographic and biological variables. Results indicated herring recruitment estimates were significantly improved by modifying the standard Ricker model to include an index of young-of-the-year (YOY) Walleye Pollock (Gadus chalcogrammus) abundance. The positive relationship between herring recruits-per-spawner and YOY pollock abundance has persisted through three decades, including the herring stock crash of the early 1990s. Including sea surface temperature, primary productivity, and additional predator or competitor abundances singly or in combination did not improve model performance. We suggest that synchrony of juvenile herring and pollock survival may be caused by increased abundance of their zooplankton prey, or high juvenile pollock abundance may promote prey switching and satiation of predators. Regardless of the mechanism, the relationship has practical application to herring recruitment forecasting, and serves as an example of incorporating ecosystem components into a stock assessment model.

  20. Remote Sensing Dynamic Monitoring of Biological Invasive Species Based on Adaptive PCNN and Improved C-V Model

    Directory of Open Access Journals (Sweden)

    PENG Gang

    2014-12-01

    Full Text Available Biological species invasion problem bring serious damage to the ecosystem, and have become one of the six major enviromental problems that affect the future economic development, also have become one of the hot topic in domestic and foreign scholars. Remote sensing technology has been successfully used in the investigation of coastal zone resources, dynamic monitoring of the resources and environment, and other fields. It will cite a new remote sensing image change detection algorithm based on adaptive pulse coupled neural network (PCNN and improved C-V model, for remote sensing dynamic monitoring of biological species invasion. The experimental results show that the algorithm is effective in the test results of biological species invasions.

  1. Exposure factors for marine eutrophication impacts assessment based on a mechanistic biological model

    DEFF Research Database (Denmark)

    Cosme, Nuno Miguel Dias; Koski, Marja; Hauschild, Michael Zwicky

    2015-01-01

    routes from primary (cell aggregates) and secondary producers (faecal pellets, carcasses, and active vertical transport). Carbon export production (PE) and ecosystems eXposure Factors (XF), which represents a nitrogen-to-oxygen 'conversion' potential, were estimated at a spatial resolution of 66 large......Emissions of nitrogen (N) from anthropogenic sources enrich marine waters and promote planktonic growth. This newly synthesised organic carbon is eventually exported to benthic waters where aerobic respiration by heterotrophic bacteria results in the consumption of dissolved oxygen (DO......). This pathway is typical of marine eutrophication. A model is proposed to mechanistically estimate the response of coastal marine ecosystems to N inputs. It addresses the biological processes of nutrient-limited primary production (PP), metazoan consumption, and bacterial degradation, in four distinct sinking...

  2. Quantitative global sensitivity analysis of a biologically based dose-response pregnancy model for the thyroid endocrine system.

    Science.gov (United States)

    Lumen, Annie; McNally, Kevin; George, Nysia; Fisher, Jeffrey W; Loizou, George D

    2015-01-01

    A deterministic biologically based dose-response model for the thyroidal system in a near-term pregnant woman and the fetus was recently developed to evaluate quantitatively thyroid hormone perturbations. The current work focuses on conducting a quantitative global sensitivity analysis on this complex model to identify and characterize the sources and contributions of uncertainties in the predicted model output. The workflow and methodologies suitable for computationally expensive models, such as the Morris screening method and Gaussian Emulation processes, were used for the implementation of the global sensitivity analysis. Sensitivity indices, such as main, total and interaction effects, were computed for a screened set of the total thyroidal system descriptive model input parameters. Furthermore, a narrower sub-set of the most influential parameters affecting the model output of maternal thyroid hormone levels were identified in addition to the characterization of their overall and pair-wise parameter interaction quotients. The characteristic trends of influence in model output for each of these individual model input parameters over their plausible ranges were elucidated using Gaussian Emulation processes. Through global sensitivity analysis we have gained a better understanding of the model behavior and performance beyond the domains of observation by the simultaneous variation in model inputs over their range of plausible uncertainties. The sensitivity analysis helped identify parameters that determine the driving mechanisms of the maternal and fetal iodide kinetics, thyroid function and their interactions, and contributed to an improved understanding of the system modeled. We have thus demonstrated the use and application of global sensitivity analysis for a biologically based dose-response model for sensitive life-stages such as pregnancy that provides richer information on the model and the thyroidal system modeled compared to local sensitivity analysis.

  3. Synthetic biology between challenges and risks: suggestions for a model of governance and a regulatory framework, based on fundamental rights.

    Science.gov (United States)

    Colussi, Ilaria Anna

    2013-01-01

    This paper deals with the emerging synthetic biology, its challenges and risks, and tries to design a model for the governance and regulation of the field. The model is called of "prudent vigilance" (inspired by the report about synthetic biology, drafted by the U.S. Presidential Commission on Bioethics, 2010), and it entails (a) an ongoing and periodically revised process of assessment and management of all the risks and concerns, and (b) the adoption of policies - taken through "hard law" and "soft law" sources - that are based on the principle of proportionality (among benefits and risks), on a reasonable balancing between different interests and rights at stake, and are oriented by a constitutional frame, which is represented by the protection of fundamental human rights emerging in the field of synthetic biology (right to life, right to health, dignity, freedom of scientific research, right to environment). After the theoretical explanation of the model, its operability is "checked", by considering its application with reference to only one specific risk brought up by synthetic biology - biosecurity risk, i.e. the risk of bioterrorism.

  4. A PROBLEM-BASED LEARNING MODEL IN BIOLOGY EDUCATION COURSES TO DEVELOP INQUIRY TEACHING COMPETENCY OF PRESERVICE TEACHERS

    Directory of Open Access Journals (Sweden)

    Diah Aryulina

    2016-02-01

    MODEL PEMBELAJARAN BERBASIS MASALAH PADA MATAKULIAH PENDIDIKAN BIOLOGI UNTUK MENGEMBANGKAN KOMPETENSI PEMBELAJARAN INKUIRI Abstrak: Tujuan tahap awal penelitian pengembangan ini adalah: 1 mengembangkan model pembelajaran berbasis masalah (PBM pada matakuliah pendidikan biologi, dan 2 memeroleh penilaian ahli terhadap ketepatan model PBM. Model PBM dikembangkan menggunakan pendekatan sistem desain instruksional berdasarkan analisis kebutuhan kompetensi guru biologi, serta kajian literatur mengenai ciri dan proses pembelajaran berbasis masalah. Evaluasi model PBM dilakukan oleh dua pakar pendidikan biologi. Selanjutnya data evaluasi dari pakar dianalisis secara deskriptif. Struktur model PBM yang dikembangkan pada matakuliah Strategi Pembelajaran Biologi, PPL I, dan PPL II terdiri atas tahap identifikasi masalah, perencanaan pemecahan masalah, pelaksanaan pemecahan masalah, penyajian hasil pemecahan masalah, dan refleksi pemecahan masalah. Kelima tahap tersebut dilaksanakan berulang dalam beberapa siklus selama semester. Hasil penilaian pakar menunjukkan bahwa model PBM sesuai dengan ciri pembelajaran berbasis masalah dan tepat digunakan untuk mengembangkan kompetensi pembelajaran inkuiri calon guru. Kata kunci: Model PBM, matakuliah pendidikan biologi, calon guru, kompetensi pembelajaran inkuiri

  5. Validation of systems biology models

    NARCIS (Netherlands)

    Hasdemir, D.

    2015-01-01

    The paradigm shift from qualitative to quantitative analysis of biological systems brought a substantial number of modeling approaches to the stage of molecular biology research. These include but certainly are not limited to nonlinear kinetic models, static network models and models obtained by the

  6. Issues in Biological Shape Modelling

    DEFF Research Database (Denmark)

    Hilger, Klaus Baggesen

    This talk reflects parts of the current research at informatics and Mathematical Modelling at the Technical University of Denmark within biological shape modelling. We illustrate a series of generalizations, modifications, and applications of the elements of constructing models of shape or appear......This talk reflects parts of the current research at informatics and Mathematical Modelling at the Technical University of Denmark within biological shape modelling. We illustrate a series of generalizations, modifications, and applications of the elements of constructing models of shape...

  7. Systems biology of bacterial nitrogen fixation: High-throughput technology and its integrative description with constraint-based modeling

    Directory of Open Access Journals (Sweden)

    Resendis-Antonio Osbaldo

    2011-07-01

    Full Text Available Abstract Background Bacterial nitrogen fixation is the biological process by which atmospheric nitrogen is uptaken by bacteroids located in plant root nodules and converted into ammonium through the enzymatic activity of nitrogenase. In practice, this biological process serves as a natural form of fertilization and its optimization has significant implications in sustainable agricultural programs. Currently, the advent of high-throughput technology supplies with valuable data that contribute to understanding the metabolic activity during bacterial nitrogen fixation. This undertaking is not trivial, and the development of computational methods useful in accomplishing an integrative, descriptive and predictive framework is a crucial issue to decoding the principles that regulated the metabolic activity of this biological process. Results In this work we present a systems biology description of the metabolic activity in bacterial nitrogen fixation. This was accomplished by an integrative analysis involving high-throughput data and constraint-based modeling to characterize the metabolic activity in Rhizobium etli bacteroids located at the root nodules of Phaseolus vulgaris (bean plant. Proteome and transcriptome technologies led us to identify 415 proteins and 689 up-regulated genes that orchestrate this biological process. Taking into account these data, we: 1 extended the metabolic reconstruction reported for R. etli; 2 simulated the metabolic activity during symbiotic nitrogen fixation; and 3 evaluated the in silico results in terms of bacteria phenotype. Notably, constraint-based modeling simulated nitrogen fixation activity in such a way that 76.83% of the enzymes and 69.48% of the genes were experimentally justified. Finally, to further assess the predictive scope of the computational model, gene deletion analysis was carried out on nine metabolic enzymes. Our model concluded that an altered metabolic activity on these enzymes induced

  8. A model invalidation-based approach for elucidating biological signalling pathways, applied to the chemotaxis pathway in R. sphaeroides.

    Science.gov (United States)

    Roberts, Mark A J; August, Elias; Hamadeh, Abdullah; Maini, Philip K; McSharry, Patrick E; Armitage, Judith P; Papachristodoulou, Antonis

    2009-10-31

    Developing methods for understanding the connectivity of signalling pathways is a major challenge in biological research. For this purpose, mathematical models are routinely developed based on experimental observations, which also allow the prediction of the system behaviour under different experimental conditions. Often, however, the same experimental data can be represented by several competing network models. In this paper, we developed a novel mathematical model/experiment design cycle to help determine the probable network connectivity by iteratively invalidating models corresponding to competing signalling pathways. To do this, we systematically design experiments in silico that discriminate best between models of the competing signalling pathways. The method determines the inputs and parameter perturbations that will differentiate best between model outputs, corresponding to what can be measured/observed experimentally. We applied our method to the unknown connectivities in the chemotaxis pathway of the bacterium Rhodobacter sphaeroides. We first developed several models of R. sphaeroides chemotaxis corresponding to different signalling networks, all of which are biologically plausible. Parameters in these models were fitted so that they all represented wild type data equally well. The models were then compared to current mutant data and some were invalidated. To discriminate between the remaining models we used ideas from control systems theory to determine efficiently in silico an input profile that would result in the biggest difference in model outputs. However, when we applied this input to the models, we found it to be insufficient for discrimination in silico. Thus, to achieve better discrimination, we determined the best change in initial conditions (total protein concentrations) as well as the best change in the input profile. The designed experiments were then performed on live cells and the resulting data used to invalidate all but one of the

  9. A model invalidation-based approach for elucidating biological signalling pathways, applied to the chemotaxis pathway in R. sphaeroides

    Directory of Open Access Journals (Sweden)

    Hamadeh Abdullah

    2009-10-01

    Full Text Available Abstract Background Developing methods for understanding the connectivity of signalling pathways is a major challenge in biological research. For this purpose, mathematical models are routinely developed based on experimental observations, which also allow the prediction of the system behaviour under different experimental conditions. Often, however, the same experimental data can be represented by several competing network models. Results In this paper, we developed a novel mathematical model/experiment design cycle to help determine the probable network connectivity by iteratively invalidating models corresponding to competing signalling pathways. To do this, we systematically design experiments in silico that discriminate best between models of the competing signalling pathways. The method determines the inputs and parameter perturbations that will differentiate best between model outputs, corresponding to what can be measured/observed experimentally. We applied our method to the unknown connectivities in the chemotaxis pathway of the bacterium Rhodobacter sphaeroides. We first developed several models of R. sphaeroides chemotaxis corresponding to different signalling networks, all of which are biologically plausible. Parameters in these models were fitted so that they all represented wild type data equally well. The models were then compared to current mutant data and some were invalidated. To discriminate between the remaining models we used ideas from control systems theory to determine efficiently in silico an input profile that would result in the biggest difference in model outputs. However, when we applied this input to the models, we found it to be insufficient for discrimination in silico. Thus, to achieve better discrimination, we determined the best change in initial conditions (total protein concentrations as well as the best change in the input profile. The designed experiments were then performed on live cells and the resulting

  10. A mathematical model for pressure-based organs behaving as biological pressure vessels.

    Science.gov (United States)

    Casha, Aaron R; Camilleri, Liberato; Gauci, Marilyn; Gatt, Ruben; Sladden, David; Chetcuti, Stanley; Grima, Joseph N

    2018-04-26

    We introduce a mathematical model that describes the allometry of physical characteristics of hollow organs behaving as pressure vessels based on the physics of ideal pressure vessels. The model was validated by studying parameters such as body and organ mass, systolic and diastolic pressures, internal and external dimensions, pressurization energy and organ energy output measurements of pressure-based organs in a wide range of mammals and birds. Seven rules were derived that govern amongst others, lack of size efficiency on scaling to larger organ sizes, matching organ size in the same species, equal relative efficiency in pressurization energy across species and direct size matching between organ mass and mass of contents. The lung, heart and bladder follow these predicted theoretical relationships with a similar relative efficiency across various mammalian and avian species; an exception is cardiac output in mammals with a mass exceeding 10kg. This may limit massive body size in mammals, breaking Cope's rule that populations evolve to increase in body size over time. Such a limit was not found in large flightless birds exceeding 100kg, leading to speculation about unlimited dinosaur size should dinosaurs carry avian-like cardiac characteristics. Copyright © 2018. Published by Elsevier Ltd.

  11. Model-based optimization of a sequencing batch reactor for biological nitrogen removal.

    Science.gov (United States)

    Souza, S M; Araújo, O Q F; Coelho, M A Z

    2008-05-01

    An optimal operating mode for a sequencing batch reactor was determined via a model-based optimization. Synthetic wastewater containing mainly organic matter (as glucose) and nitrogen (as ammonium chloride) was treated without any addition of an external carbon source to accomplish denitrification step. A simplified model was used to describe process dynamics, comprised of six ordinary differential equations and an empirical correlation for oxygen consumption rate. Batch cycle time was the chosen objective function to be minimized for a fixed volume of waste to be treated. Furthermore, as SBR operation is divided in two major phases - aerobic and anoxic, to achieve total pollutants removal within minimum time, these phases can be repeatedly alternated. To ensure availability of organic matter necessary for denitrification, these two phases were combined with feed steps. Different feed strategies were tested using one, two or three feed steps. A successive quadratic programming algorithm was used, and maximum values for final COD, nitrate and ammonium concentrations, as well as maximum feed pump flow rate were some the process constraints. One step feed strategy was indicated by the optimization leading to a batch cycle time of 5h.

  12. Biological methanation of hydrogen within biogas plants: A model-based feasibility study

    International Nuclear Information System (INIS)

    Bensmann, A.; Hanke-Rauschenbach, R.; Heyer, R.; Kohrs, F.; Benndorf, D.; Reichl, U.; Sundmacher, K.

    2014-01-01

    Highlights: • Simulation study about direct methanation of hydrogen within biogas plants. • In stationary operation two limitations, namely biological and transfer limit. • Biological limit at 4m H2 3 /m CO2 3 due to stoichiometry. • Dynamic behaviour shows three qualitatively different step responses. • A simple control scheme to meet the output quality was developed. - Abstract: One option to utilize excess electric energy is its conversion to hydrogen and the subsequent methanation. An alternative to the classical chemical Sabatier process is the biological methanation (methanogenesis) within biogas plants. In conventional biogas plants methane and carbon dioxide is produced. The latter can be directly converted to methane by feeding hydrogen into the reactor, since hydrogenotrophic bacteria are present. In the present contribution, a comprehensive simulation study with respect to stationary operating conditions and disturbances is presented. It reveals two qualitative different limitations, namely a biological limit (appr. at 4m H2 3 /m CO2 3 corresponds to 4.2m H2,STP 3 /m liq 3 /d) as well as a transfer limit. A parameter region for a safe operation was defined. The temporary operation with stationary unfeasible conditions was analysed and thereby three qualitatively different disturbances can be distinguished. In one of these the operation for several days is possible. On the basis of these results, a controller was proposed and tested that meets the demands on the conversion of hydrogen and also prevents the washout of the microbial community due to hydrogen overload

  13. Mathematical modeling of biological processes

    CERN Document Server

    Friedman, Avner

    2014-01-01

    This book on mathematical modeling of biological processes includes a wide selection of biological topics that demonstrate the power of mathematics and computational codes in setting up biological processes with a rigorous and predictive framework. Topics include: enzyme dynamics, spread of disease, harvesting bacteria, competition among live species, neuronal oscillations, transport of neurofilaments in axon, cancer and cancer therapy, and granulomas. Complete with a description of the biological background and biological question that requires the use of mathematics, this book is developed for graduate students and advanced undergraduate students with only basic knowledge of ordinary differential equations and partial differential equations; background in biology is not required. Students will gain knowledge on how to program with MATLAB without previous programming experience and how to use codes in order to test biological hypothesis.

  14. Physiologically based kinetic modelling based prediction of oral systemic bioavailability of flavonoids, their metabolites, and their biological effects

    NARCIS (Netherlands)

    Boonpawa, Rungnapa

    2017-01-01

    Flavonoids, abundantly present in fruits and vegetables, have been reported to exert various positive health effects based on in vitro bioassays. However, effects detected in in vitro models cannot be directly correlated to human health as most in vitro studies have been performed using flavonoid

  15. Physiologically based kinetic modelling based prediction of oral systemic bioavailability of flavonoids, their metabolites, and their biological effects

    NARCIS (Netherlands)

    Boonpawa, Rungnapa

    2017-01-01

    Flavonoids, abundantly present in fruits and vegetables, have been reported to exert various positive health effects based on in vitro bioassays. However, effects detected in in vitro models cannot be directly correlated to human health as most in vitro studies have

  16. "Model-Based Reasoning is Not a Simple Thing": Investigating Enactment of Modeling in Five High School Biology Classrooms

    Science.gov (United States)

    Gaytan, Candice Renee

    Modeling is an important scientific practice through which scientists generate, evaluate, and revise scientific knowledge, and it can be translated into science classrooms as a means for engaging students in authentic scientific practice. Much of the research investigating modeling in classrooms focuses on student learning, leaving a gap in understanding how teachers enact this important practice. This dissertation draws on data collected through a model-based curricular project to uncover instructional moves teachers made to enact modeling, to describe factors influencing enactment, and to discuss a framework for designing and enacting modeling lessons. I framed my analysis and interpretation of data within the varying perceptions of modeling found in the science studies and science education literature. Largely, modeling is described to varying degrees as a means to engage students in sense-making or as a means to deliver content to students. This frame revealed how the instructional moves teachers used to enact modeling may have influenced its portrayal as a reasoning practice. I found that teachers' responses to their students' ideas or questions may have important consequences for students' engagement in modeling, and thus, sense-making. To investigate factors influencing the portrayal of modeling, I analyzed teacher interviews and writings for what they perceived affected instruction. My findings illustrate alignments and misalignments between what teachers perceive modeling to be and what they do through instruction. In particular, teachers valued providing their students with time to collaborate and to share their ideas, but when time was perceived as a constraint, instruction shifted towards delivering content. Additionally, teachers' perceptions of students' capacity to engage in modeling is also related to if and how they provided opportunities for students to make sense of phenomena. The dissertation closes with a discussion of a framework for designing

  17. gPKPDSim: a SimBiology®-based GUI application for PKPD modeling in drug development.

    Science.gov (United States)

    Hosseini, Iraj; Gajjala, Anita; Bumbaca Yadav, Daniela; Sukumaran, Siddharth; Ramanujan, Saroja; Paxson, Ricardo; Gadkar, Kapil

    2018-01-04

    Modeling and simulation (M&S) is increasingly used in drug development to characterize pharmacokinetic-pharmacodynamic (PKPD) relationships and support various efforts such as target feasibility assessment, molecule selection, human PK projection, and preclinical and clinical dose and schedule determination. While model development typically require mathematical modeling expertise, model exploration and simulations could in many cases be performed by scientists in various disciplines to support the design, analysis and interpretation of experimental studies. To this end, we have developed a versatile graphical user interface (GUI) application to enable easy use of any model constructed in SimBiology ® to execute various common PKPD analyses. The MATLAB ® -based GUI application, called gPKPDSim, has a single screen interface and provides functionalities including simulation, data fitting (parameter estimation), population simulation (exploring the impact of parameter variability on the outputs of interest), and non-compartmental PK analysis. Further, gPKPDSim is a user-friendly tool with capabilities including interactive visualization, exporting of results and generation of presentation-ready figures. gPKPDSim was designed primarily for use in preclinical and translational drug development, although broader applications exist. gPKPDSim is a MATLAB ® -based open-source application and is publicly available to download from MATLAB ® Central™. We illustrate the use and features of gPKPDSim using multiple PKPD models to demonstrate the wide applications of this tool in pharmaceutical sciences. Overall, gPKPDSim provides an integrated, multi-purpose user-friendly GUI application to enable efficient use of PKPD models by scientists from various disciplines, regardless of their modeling expertise.

  18. A generic framework for individual-based modelling and physical-biological interaction

    DEFF Research Database (Denmark)

    Christensen, Asbjørn; Mariani, Patrizio; Payne, Mark R.

    2018-01-01

    , comparison of physical circulation models, model ensemble runs and recently posterior Eulerian simulations using the IBMlib framework. We present the code design ideas behind the longevity of the code, our implementation experiences, as well as code performance benchmarking. The framework may contribute...

  19. Mesoscopic models of biological membranes

    DEFF Research Database (Denmark)

    Venturoli, M.; Sperotto, Maria Maddalena; Kranenburg, M.

    2006-01-01

    Phospholipids are the main components of biological membranes and dissolved in water these molecules self-assemble into closed structures, of which bilayers are the most relevant from a biological point of view. Lipid bilayers are often used, both in experimental and by theoretical investigations...... to coarse grain a biological membrane. The conclusion of this comparison is that there can be many valid different strategies, but that the results obtained by the various mesoscopic models are surprisingly consistent. A second objective of this review is to illustrate how mesoscopic models can be used...

  20. Core–periphery models for graphs based on their δ-hyperbolicity: An example using biological networks

    Directory of Open Access Journals (Sweden)

    Hend Alrasheed

    2017-03-01

    Full Text Available Hyperbolicity is a global property of graphs that measures how close their structures are to trees in terms of their distances. It embeds multiple properties that facilitate solving several problems that found to be hard in the general graph form. In this paper, we investigate the hyperbolicity of graphs not only by considering Gromov’s notion of δ-hyperbolicity but also by analyzing its relationship to other graph’s parameters. This new perspective allows us to classify graphs with respect to their hyperbolicity and to show that many biological networks are hyperbolic. Then we introduce the eccentricity-based bending property which we exploit to identify the core vertices of a graph by proposing two models: the maximum-peak model and the minimum cover set model. In this extended version of the paper, we include some new theorems, as well as proofs of the theorems proposed in the conference paper. Also, we present the algorithms we used for each of the proposed core identification models, and we provide more analysis, explanations, and examples.

  1. And So It Grows: Using a Computer-Based Simulation of a Population Growth Model to Integrate Biology & Mathematics

    Science.gov (United States)

    Street, Garrett M.; Laubach, Timothy A.

    2013-01-01

    We provide a 5E structured-inquiry lesson so that students can learn more of the mathematics behind the logistic model of population biology. By using models and mathematics, students understand how population dynamics can be influenced by relatively simple changes in the environment.

  2. Compositional Modeling of Biological Systems

    OpenAIRE

    Zámborszky, Judit

    2010-01-01

    Molecular interactions are wired in a fascinating way resulting in complex behavior of bio-logical systems. Theoretical modeling provides us a useful framework for understanding the dynamics and the function of such networks. The complexity of the biological systems calls for conceptual tools that manage the combinatorial explosion of the set of possible interac-tions. A suitable conceptual tool to attack complexity is compositionality, already success-fully used in the process algebra field ...

  3. Multi-mutational model for cancer based on age-time patterns of radiation effects: 2. Biological aspects

    Energy Technology Data Exchange (ETDEWEB)

    Mendelsohn, M.L.; Pierce, P.A.

    1997-09-04

    Biological properties of relevance when modeling cancers induced in the atom bomb survivors include the wide distribution of the induced cancers across all organs, their biological indistinguishability from background cancers, their rates being proportional to background cancer rates, their rates steadily increasing over at least 50 years as the survivors age, and their radiation dose response being linear. We have successfully described this array of properties with a modified Armitage-Doll model using 5 to 6 somatic mutations, no intermediate growth, and the dose-related replacement of any one of these time-driven mutations by a radiation-induced mutation. Such a model is contrasted to prevailing models that use fewer mutations combined with intervening growth. While the rationale and effectiveness of our model is compelling for carcinogenesis in the atom bomb survivors, the lack of a promotional component may limit the generality of the model for other types of human carcinogenesis.

  4. Mesoscopic models of biological membranes

    DEFF Research Database (Denmark)

    Venturoli, M.; Sperotto, Maria Maddalena; Kranenburg, M.

    2006-01-01

    Phospholipids are the main components of biological membranes and dissolved in water these molecules self-assemble into closed structures, of which bilayers are the most relevant from a biological point of view. Lipid bilayers are often used, both in experimental and by theoretical investigations......, as model systems to understand the fundamental properties of biomembranes. The properties of lipid bilayers can be studied at different time and length scales. For some properties it is sufficient to envision a membrane as an elastic sheet, while for others it is important to take into account the details...... to coarse grain a biological membrane. The conclusion of this comparison is that there can be many valid different strategies, but that the results obtained by the various mesoscopic models are surprisingly consistent. A second objective of this review is to illustrate how mesoscopic models can be used...

  5. Biological transportation networks: Modeling and simulation

    KAUST Repository

    Albi, Giacomo

    2015-09-15

    We present a model for biological network formation originally introduced by Cai and Hu [Adaptation and optimization of biological transport networks, Phys. Rev. Lett. 111 (2013) 138701]. The modeling of fluid transportation (e.g., leaf venation and angiogenesis) and ion transportation networks (e.g., neural networks) is explained in detail and basic analytical features like the gradient flow structure of the fluid transportation network model and the impact of the model parameters on the geometry and topology of network formation are analyzed. We also present a numerical finite-element based discretization scheme and discuss sample cases of network formation simulations.

  6. Integrating interactive computational modeling in biology curricula.

    Directory of Open Access Journals (Sweden)

    Tomáš Helikar

    2015-03-01

    Full Text Available While the use of computer tools to simulate complex processes such as computer circuits is normal practice in fields like engineering, the majority of life sciences/biological sciences courses continue to rely on the traditional textbook and memorization approach. To address this issue, we explored the use of the Cell Collective platform as a novel, interactive, and evolving pedagogical tool to foster student engagement, creativity, and higher-level thinking. Cell Collective is a Web-based platform used to create and simulate dynamical models of various biological processes. Students can create models of cells, diseases, or pathways themselves or explore existing models. This technology was implemented in both undergraduate and graduate courses as a pilot study to determine the feasibility of such software at the university level. First, a new (In Silico Biology class was developed to enable students to learn biology by "building and breaking it" via computer models and their simulations. This class and technology also provide a non-intimidating way to incorporate mathematical and computational concepts into a class with students who have a limited mathematical background. Second, we used the technology to mediate the use of simulations and modeling modules as a learning tool for traditional biological concepts, such as T cell differentiation or cell cycle regulation, in existing biology courses. Results of this pilot application suggest that there is promise in the use of computational modeling and software tools such as Cell Collective to provide new teaching methods in biology and contribute to the implementation of the "Vision and Change" call to action in undergraduate biology education by providing a hands-on approach to biology.

  7. Integrating interactive computational modeling in biology curricula.

    Science.gov (United States)

    Helikar, Tomáš; Cutucache, Christine E; Dahlquist, Lauren M; Herek, Tyler A; Larson, Joshua J; Rogers, Jim A

    2015-03-01

    While the use of computer tools to simulate complex processes such as computer circuits is normal practice in fields like engineering, the majority of life sciences/biological sciences courses continue to rely on the traditional textbook and memorization approach. To address this issue, we explored the use of the Cell Collective platform as a novel, interactive, and evolving pedagogical tool to foster student engagement, creativity, and higher-level thinking. Cell Collective is a Web-based platform used to create and simulate dynamical models of various biological processes. Students can create models of cells, diseases, or pathways themselves or explore existing models. This technology was implemented in both undergraduate and graduate courses as a pilot study to determine the feasibility of such software at the university level. First, a new (In Silico Biology) class was developed to enable students to learn biology by "building and breaking it" via computer models and their simulations. This class and technology also provide a non-intimidating way to incorporate mathematical and computational concepts into a class with students who have a limited mathematical background. Second, we used the technology to mediate the use of simulations and modeling modules as a learning tool for traditional biological concepts, such as T cell differentiation or cell cycle regulation, in existing biology courses. Results of this pilot application suggest that there is promise in the use of computational modeling and software tools such as Cell Collective to provide new teaching methods in biology and contribute to the implementation of the "Vision and Change" call to action in undergraduate biology education by providing a hands-on approach to biology.

  8. Mathematical models in biological discovery

    CERN Document Server

    Walter, Charles

    1977-01-01

    When I was asked to help organize an American Association for the Advancement of Science symposium about how mathematical models have con­ tributed to biology, I agreed immediately. The subject is of immense importance and wide-spread interest. However, too often it is discussed in biologically sterile environments by "mutual admiration society" groups of "theoreticians", many of whom have never seen, and most of whom have never done, an original scientific experiment with the biolog­ ical materials they attempt to describe in abstract (and often prejudiced) terms. The opportunity to address the topic during an annual meeting of the AAAS was irresistable. In order to try to maintain the integrity ;,f the original intent of the symposium, it was entitled, "Contributions of Mathematical Models to Biological Discovery". This symposium was organized by Daniel Solomon and myself, held during the 141st annual meeting of the AAAS in New York during January, 1975, sponsored by sections G and N (Biological and Medic...

  9. The Biological Bases of Conformity

    Directory of Open Access Journals (Sweden)

    Thomas Joshau Henry Morgan

    2012-06-01

    Full Text Available Humans are characterized by an extreme dependence on culturally transmitted information and recent formal theory predicts that natural selection should favour adaptive learning strategies that facilitate effective use of social information in decision making. One strategy that has attracted particular attention is conformist transmission, defined as the disproportionately likely adoption of the most common variant. Conformity has historically been emphasized as significant in the social psychology literature, and recently there have also been reports of conformist behaviour in nonhuman animals. However, mathematical analyses differ in how important and widespread they expect conformity to be, and relevant experimental work is scarce, and generates findings that are both mutually contradictory and inconsistent with the predictions of the models. We review the relevant literature considering the causation, function, history and ontogeny of conformity and describe a computer-based experiment on human subjects that we carried out in order to resolve ambiguities. We found that only when many demonstrators were available and subjects were uncertain was subject behaviour conformist. A further analysis found that the underlying response to social information alone was generally conformist. Thus, our data are consistent with a conformist use of social information, but as subject’s behaviour is the result of both social and asocial influences, the resultant behaviour may not be conformist. We end by relating these findings to an embryonic cognitive neuroscience literature that has recently begun to explore the neural bases of social learning. Here conformist transmission may be a particularly useful case study, not only because there are well-defined and tractable opportunities to characterize the biological underpinnings of this form of social learning, but also because early findings imply that humans may possess specific cognitive adaptations for

  10. The Biological Bases of Conformity

    Science.gov (United States)

    Morgan, T. J. H.; Laland, K. N.

    2012-01-01

    Humans are characterized by an extreme dependence on culturally transmitted information and recent formal theory predicts that natural selection should favor adaptive learning strategies that facilitate effective copying and decision making. One strategy that has attracted particular attention is conformist transmission, defined as the disproportionately likely adoption of the most common variant. Conformity has historically been emphasized as significant in the social psychology literature, and recently there have also been reports of conformist behavior in non-human animals. However, mathematical analyses differ in how important and widespread they expect conformity to be, and relevant experimental work is scarce, and generates findings that are both mutually contradictory and inconsistent with the predictions of the models. We review the relevant literature considering the causation, function, history, and ontogeny of conformity, and describe a computer-based experiment on human subjects that we carried out in order to resolve ambiguities. We found that only when many demonstrators were available and subjects were uncertain was subject behavior conformist. A further analysis found that the underlying response to social information alone was generally conformist. Thus, our data are consistent with a conformist use of social information, but as subjects’ behavior is the result of both social and asocial influences, the resultant behavior may not be conformist. We end by relating these findings to an embryonic cognitive neuroscience literature that has recently begun to explore the neural bases of social learning. Here conformist transmission may be a particularly useful case study, not only because there are well-defined and tractable opportunities to characterize the biological underpinnings of this form of social learning, but also because early findings imply that humans may possess specific cognitive adaptations for effective social learning. PMID:22712006

  11. The biological bases of conformity.

    Science.gov (United States)

    Morgan, T J H; Laland, K N

    2012-01-01

    Humans are characterized by an extreme dependence on culturally transmitted information and recent formal theory predicts that natural selection should favor adaptive learning strategies that facilitate effective copying and decision making. One strategy that has attracted particular attention is conformist transmission, defined as the disproportionately likely adoption of the most common variant. Conformity has historically been emphasized as significant in the social psychology literature, and recently there have also been reports of conformist behavior in non-human animals. However, mathematical analyses differ in how important and widespread they expect conformity to be, and relevant experimental work is scarce, and generates findings that are both mutually contradictory and inconsistent with the predictions of the models. We review the relevant literature considering the causation, function, history, and ontogeny of conformity, and describe a computer-based experiment on human subjects that we carried out in order to resolve ambiguities. We found that only when many demonstrators were available and subjects were uncertain was subject behavior conformist. A further analysis found that the underlying response to social information alone was generally conformist. Thus, our data are consistent with a conformist use of social information, but as subjects' behavior is the result of both social and asocial influences, the resultant behavior may not be conformist. We end by relating these findings to an embryonic cognitive neuroscience literature that has recently begun to explore the neural bases of social learning. Here conformist transmission may be a particularly useful case study, not only because there are well-defined and tractable opportunities to characterize the biological underpinnings of this form of social learning, but also because early findings imply that humans may possess specific cognitive adaptations for effective social learning.

  12. Laser interaction with biological material mathematical modeling

    CERN Document Server

    Kulikov, Kirill

    2014-01-01

    This book covers the principles of laser interaction with biological cells and tissues of varying degrees of organization. The problems of biomedical diagnostics are considered. Scattering of laser irradiation of blood cells is modeled for biological structures (dermis, epidermis, vascular plexus). An analytic theory is provided which is based on solving the wave equation for the electromagnetic field. It allows the accurate analysis of interference effects arising from the partial superposition of scattered waves. Treated topics of mathematical modeling are: optical characterization of biological tissue with large-scale and small-scale inhomogeneities in the layers, heating blood vessel under laser irradiation incident on the outer surface of the skin and thermo-chemical denaturation of biological structures at the example of human skin.

  13. A biologically based model for the integration of sensory-motor contingencies in rules and plans: a prefrontal cortex based extension of the Distributed Adaptive Control architecture.

    Science.gov (United States)

    Duff, Armin; Fibla, Marti Sanchez; Verschure, Paul F M J

    2011-06-30

    Intelligence depends on the ability of the brain to acquire and apply rules and representations. At the neuronal level these properties have been shown to critically depend on the prefrontal cortex. Here we present, in the context of the Distributed Adaptive Control architecture (DAC), a biologically based model for flexible control and planning based on key physiological properties of the prefrontal cortex, i.e. reward modulated sustained activity and plasticity of lateral connectivity. We test the model in a series of pertinent tasks, including multiple T-mazes and the Tower of London that are standard experimental tasks to assess flexible control and planning. We show that the model is both able to acquire and express rules that capture the properties of the task and to quickly adapt to changes. Further, we demonstrate that this biomimetic self-contained cognitive architecture generalizes to planning. In addition, we analyze the extended DAC architecture, called DAC 6, as a model that can be applied for the creation of intelligent and psychologically believable synthetic agents. Copyright © 2010 Elsevier Inc. All rights reserved.

  14. A LabVIEW-based electrical bioimpedance spectroscopic data interpreter (LEBISDI) for biological tissue impedance analysis and equivalent circuit modelling

    KAUST Repository

    Bera, Tushar Kanti

    2016-12-05

    Under an alternating electrical signal, biological tissues produce a complex electrical bioimpedance that is a function of tissue composition and applied signal frequencies. By studying the bioimpedance spectra of biological tissues over a wide range of frequencies, we can noninvasively probe the physiological properties of these tissues to detect possible pathological conditions. Electrical impedance spectroscopy (EIS) can provide the spectra that are needed to calculate impedance parameters within a wide range of frequencies. Before impedance parameters can be calculated and tissue information extracted, impedance spectra should be processed and analyzed by a dedicated software program. National Instruments (NI) Inc. offers LabVIEW, a fast, portable, robust, user-friendly platform for designing dataanalyzing software. We developed a LabVIEW-based electrical bioimpedance spectroscopic data interpreter (LEBISDI) to analyze the electrical impedance spectra for tissue characterization in medical, biomedical and biological applications. Here, we test, calibrate and evaluate the performance of LEBISDI on the impedance data obtained from simulation studies as well as the practical EIS experimentations conducted on electronic circuit element combinations and the biological tissue samples. We analyze the Nyquist plots obtained from the EIS measurements and compare the equivalent circuit parameters calculated by LEBISDI with the corresponding original circuit parameters to assess the accuracy of the program developed. Calibration studies show that LEBISDI not only interpreted the simulated and circuitelement data accurately, but also successfully interpreted tissues impedance data and estimated the capacitive and resistive components produced by the compositions biological cells. Finally, LEBISDI efficiently calculated and analyzed variation in bioimpedance parameters of different tissue compositions, health and temperatures. LEBISDI can also be used for human tissue

  15. Notions of similarity for computational biology models

    KAUST Repository

    Waltemath, Dagmar

    2016-03-21

    Computational models used in biology are rapidly increasing in complexity, size, and numbers. To build such large models, researchers need to rely on software tools for model retrieval, model combination, and version control. These tools need to be able to quantify the differences and similarities between computational models. However, depending on the specific application, the notion of similarity may greatly vary. A general notion of model similarity, applicable to various types of models, is still missing. Here, we introduce a general notion of quantitative model similarities, survey the use of existing model comparison methods in model building and management, and discuss potential applications of model comparison. To frame model comparison as a general problem, we describe a theoretical approach to defining and computing similarities based on different model aspects. Potentially relevant aspects of a model comprise its references to biological entities, network structure, mathematical equations and parameters, and dynamic behaviour. Future similarity measures could combine these model aspects in flexible, problem-specific ways in order to mimic users\\' intuition about model similarity, and to support complex model searches in databases.

  16. Time lags in biological models

    CERN Document Server

    MacDonald, Norman

    1978-01-01

    In many biological models it is necessary to allow the rates of change of the variables to depend on the past history, rather than only the current values, of the variables. The models may require discrete lags, with the use of delay-differential equations, or distributed lags, with the use of integro-differential equations. In these lecture notes I discuss the reasons for including lags, especially distributed lags, in biological models. These reasons may be inherent in the system studied, or may be the result of simplifying assumptions made in the model used. I examine some of the techniques available for studying the solution of the equations. A large proportion of the material presented relates to a special method that can be applied to a particular class of distributed lags. This method uses an extended set of ordinary differential equations. I examine the local stability of equilibrium points, and the existence and frequency of periodic solutions. I discuss the qualitative effects of lags, and how these...

  17. Mass exchange in an experimental new-generation life support system model based on biological regeneration of environment

    Science.gov (United States)

    Tikhomirov, A. A.; Ushakova, S. A.; Manukovsky, N. S.; Lisovsky, G. M.; Kudenko, Yu. A.; Kovalev, V. S.; Gubanov, V. G.; Barkhatov, Yu. V.; Gribovskaya, I. V.; Zolotukhin, I. G.; Gros, J. B.; Lasseur, Ch.

    An experimental model of a biological life support system was used to evaluate qualitative and quantitative parameters of the internal mass exchange. The photosynthesizing unit included the higher plant component (wheat and radish), and the heterotrophic unit consisted of a soil-like substrate, California warms, mushrooms and microbial microflora. The gas mass exchange involved evolution of oxygen by the photosynthesizing component and its uptake by the heterotroph component along with the formation and maintaining of the SLS structure, growth of mushrooms and California worms, human respiration, and some other processes. Human presence in the system in the form of "virtual human" that at regular intervals took part in the respirative gas exchange during the experiment. Experimental data demonstrated good oxygen/carbon dioxide balance, and the closure of the cycles of these gases was almost complete. The water cycle was nearly 100% closed. The main components in the water mass exchange were transpiration water and the watering solution with mineral elements. Human consumption of the edible plant biomass (grains and roots) was simulated by processing these products by a unique physicochemical method of oxidizing them to inorganic mineral compounds, which were then returned into the system and fully assimilated by the plants. The oxidation was achieved by "wet combustion" of organic biomass, using hydrogen peroxide following a special procedure, which does not require high temperature and pressure. Hydrogen peroxide is produced from the water inside the system. The closure of the cycle was estimated for individual elements and compounds. Stoichiometric proportions are given for the main components included in the experimental model of the system. Approaches to the mathematical modeling of the cycling processes are discussed, using the data of the experimental model. Nitrogen, as a representative of biogmic elements, shows an almost 100% closure of the cycle inside

  18. [Assessment of accelerated aging among automobile drivers using model of the biological age based on physical work capacity].

    Science.gov (United States)

    Bashkireva, A S

    2012-01-01

    The studies of biological age, aging rate, physical work capacity in professional drivers were conducted. The examination revealed peculiarities of system organization of functions, which determine the physical work capacity levels. Dynamics of the aging process of professional driver's organism in relation with calendar age and driving experience were shown using the biological age on physical work capacity model. The results point at the premature decrease of the physical work capacity in professional drivers. The premature contraction of the range of cardio-vascular system adaptive reactions on submaximum physical load in the drivers as compared with control group was revealed. It was proved that premature age-related changes of physiologic indices in drivers are just "risk indicators", while long driving experience is a real risk factor, accelerating the ageing process. The "risk group" with manifestations of accelerating ageing was observed in 40-49-year old drivers with 15-19 years of professional experience. The expediency of using the following methods for the age rate estimation according to biologic age indices and necessity of prophylactic measures for premature and accelerated ageing prevention among working population was demonstrated.

  19. Stochastic resonance in biological nonlinear evolution models

    Science.gov (United States)

    Dunkel, Jörn; Hilbert, Stefan; Schimansky-Geier, Lutz; Hänggi, Peter

    2004-05-01

    We investigate stochastic resonance in the nonlinear, one-dimensional Fisher-Eigen model (FEM), which represents an archetypal model for biological evolution based on a global coupling scheme. In doing so we consider different periodically driven fitness functions which govern the evolution of a biological phenotype population. For the case of a simple harmonic fitness function we are able to derive the exact analytic solution for the asymptotic probability density. A distinct feature of this solution is a phase lag between the driving signal and the linear response of the system. Furthermore, for more complex systems a general perturbation theory (linear response approximation) is put forward. Using the latter approach, we investigate stochastic resonance in terms of the spectral amplification measure for a quadratic, a quartic single-peaked, and for a bistable fitness function. Our analytical results are also compared with those of detailed numerical simulations. Our findings vindicate that stochastic resonance does occur in these nonlinear, globally coupled biological systems.

  20. Statistical Model Checking for Biological Systems

    DEFF Research Database (Denmark)

    David, Alexandre; Larsen, Kim Guldstrand; Legay, Axel

    2014-01-01

    Statistical Model Checking (SMC) is a highly scalable simulation-based verification approach for testing and estimating the probability that a stochastic system satisfies a given linear temporal property. The technique has been applied to (discrete and continuous time) Markov chains, stochastic...... timed automata and most recently hybrid systems using the tool Uppaal SMC. In this paper we enable the application of SMC to complex biological systems, by combining Uppaal SMC with ANIMO, a plugin of the tool Cytoscape used by biologists, as well as with SimBiology®, a plugin of Matlab to simulate...

  1. Prospective Tests on Biological Models of Acupuncture

    Directory of Open Access Journals (Sweden)

    Charles Shang

    2009-01-01

    Full Text Available The biological effects of acupuncture include the regulation of a variety of neurohumoral factors and growth control factors. In science, models or hypotheses with confirmed predictions are considered more convincing than models solely based on retrospective explanations. Literature review showed that two biological models of acupuncture have been prospectively tested with independently confirmed predictions: The neurophysiology model on the long-term effects of acupuncture emphasizes the trophic and anti-inflammatory effects of acupuncture. Its prediction on the peripheral effect of endorphin in acupuncture has been confirmed. The growth control model encompasses the neurophysiology model and suggests that a macroscopic growth control system originates from a network of organizers in embryogenesis. The activity of the growth control system is important in the formation, maintenance and regulation of all the physiological systems. Several phenomena of acupuncture such as the distribution of auricular acupuncture points, the long-term effects of acupuncture and the effect of multimodal non-specific stimulation at acupuncture points are consistent with the growth control model. The following predictions of the growth control model have been independently confirmed by research results in both acupuncture and conventional biomedical sciences: (i Acupuncture has extensive growth control effects. (ii Singular point and separatrix exist in morphogenesis. (iii Organizers have high electric conductance, high current density and high density of gap junctions. (iv A high density of gap junctions is distributed as separatrices or boundaries at body surface after early embryogenesis. (v Many acupuncture points are located at transition points or boundaries between different body domains or muscles, coinciding with the connective tissue planes. (vi Some morphogens and organizers continue to function after embryogenesis. Current acupuncture research suggests a

  2. Track structure in biological models.

    Science.gov (United States)

    Curtis, S B

    1986-01-01

    High-energy heavy ions in the galactic cosmic radiation (HZE particles) may pose a special risk during long term manned space flights outside the sheltering confines of the earth's geomagnetic field. These particles are highly ionizing, and they and their nuclear secondaries can penetrate many centimeters of body tissue. The three dimensional patterns of ionizations they create as they lose energy are referred to as their track structure. Several models of biological action on mammalian cells attempt to treat track structure or related quantities in their formulation. The methods by which they do this are reviewed. The proximity function is introduced in connection with the theory of Dual Radiation Action (DRA). The ion-gamma kill (IGK) model introduces the radial energy-density distribution, which is a smooth function characterizing both the magnitude and extension of a charged particle track. The lethal, potentially lethal (LPL) model introduces lambda, the mean distance between relevant ion clusters or biochemical species along the track. Since very localized energy depositions (within approximately 10 nm) are emphasized, the proximity function as defined in the DRA model is not of utility in characterizing track structure in the LPL formulation.

  3. Polyvinylpyrrolidone and arsenic-induced changes in biological responses of model aquatic organisms exposed to iron-based nanoparticles

    Energy Technology Data Exchange (ETDEWEB)

    Llaneza, Verónica [University of Florida, Engineering School of Sustainable Infrastructure and Environment, Department of Environmental Engineering Sciences (United States); Rodea-Palomares, Ismael [Univ. Autonoma de Madrid, Dept. de Biologia, Facultad de Ciencias (Spain); Zhou, Zuo [University of Florida, Engineering School of Sustainable Infrastructure and Environment, Department of Environmental Engineering Sciences (United States); Rosal, Roberto [Univ. de Alcalá, Dept. de Ingeniería Química (Spain); Fernández-Pina, Francisca [Univ. Autonoma de Madrid, Dept. de Biologia, Facultad de Ciencias (Spain); Bonzongo, Jean-Claude J., E-mail: bonzongo@ufl.edu [University of Florida, Engineering School of Sustainable Infrastructure and Environment, Department of Environmental Engineering Sciences (United States)

    2016-08-15

    The efficiency of zero-valent iron particles used in the remediation of contaminated groundwater has, with the emergence of nanotechnology, stimulated interest on the use of nano-size particles to take advantage of high-specific surface area and reactivity characteristics of nanoparticles (NPs). Accordingly, engineered iron-NPs are among the most widely used nanomaterials for in situ remediation. However, while several ecotoxicity studies have been conducted to investigate the adverse impacts of these NPs on aquatic organisms, research on the implications of spent iron-based NPs is lacking. In this study, a comparative approach is used, in which the biological effects of three iron-based NPs (Fe{sub 3}O{sub 4} and γ-Fe{sub 2}O{sub 3} NPs with particle sizes ranging from 20 to 50 nm, and Fe{sup 0}-NPs with an average particle size of 40 nm) on Raphidocelis subcapitata (formely known as Pseudokirchneriella subcapitata) and Daphnia magna were investigated using both as-prepared and pollutant-doped Fe-based NPs. For the latter, arsenic (As) was used as example sorbed pollutant. The results show that improved degree of NP dispersion by use of polyvinylpyrrolidone overlapped with both increased arsenic adsorption capacity and toxicity to the tested organisms. For R. subcapitata, Fe-oxide NPs were more toxic than Fe{sup 0}-NPs, due primarily to differences in the degree of NPs aggregation and ability to produce reactive oxygen species. For the invertebrate D. magna, a similar trend of biological responses was observed, except that sorption of As to Fe{sup 0}-NPs significantly increased the toxic response when compared to R. subcapitata. Overall, these findings point to the need for research on downstream implications of NP-pollutant complexes generated during water treatment by injection of NPs into aquatic systems.

  4. Polyvinylpyrrolidone and arsenic-induced changes in biological responses of model aquatic organisms exposed to iron-based nanoparticles

    Science.gov (United States)

    Llaneza, Verónica; Rodea-Palomares, Ismael; Zhou, Zuo; Rosal, Roberto; Fernández-Pina, Francisca; Bonzongo, Jean-Claude J.

    2016-08-01

    The efficiency of zero-valent iron particles used in the remediation of contaminated groundwater has, with the emergence of nanotechnology, stimulated interest on the use of nano-size particles to take advantage of high-specific surface area and reactivity characteristics of nanoparticles (NPs). Accordingly, engineered iron-NPs are among the most widely used nanomaterials for in situ remediation. However, while several ecotoxicity studies have been conducted to investigate the adverse impacts of these NPs on aquatic organisms, research on the implications of spent iron-based NPs is lacking. In this study, a comparative approach is used, in which the biological effects of three iron-based NPs (Fe3O4 and γ-Fe2O3 NPs with particle sizes ranging from 20 to 50 nm, and Fe0-NPs with an average particle size of 40 nm) on Raphidocelis subcapitata (formely known as Pseudokirchneriella subcapitata) and Daphnia magna were investigated using both as-prepared and pollutant-doped Fe-based NPs. For the latter, arsenic (As) was used as example sorbed pollutant. The results show that improved degree of NP dispersion by use of polyvinylpyrrolidone overlapped with both increased arsenic adsorption capacity and toxicity to the tested organisms. For R. subcapitata, Fe-oxide NPs were more toxic than Fe0-NPs, due primarily to differences in the degree of NPs aggregation and ability to produce reactive oxygen species. For the invertebrate D. magna, a similar trend of biological responses was observed, except that sorption of As to Fe0-NPs significantly increased the toxic response when compared to R. subcapitata. Overall, these findings point to the need for research on downstream implications of NP-pollutant complexes generated during water treatment by injection of NPs into aquatic systems.

  5. Polyvinylpyrrolidone and arsenic-induced changes in biological responses of model aquatic organisms exposed to iron-based nanoparticles

    International Nuclear Information System (INIS)

    Llaneza, Verónica; Rodea-Palomares, Ismael; Zhou, Zuo; Rosal, Roberto; Fernández-Pina, Francisca; Bonzongo, Jean-Claude J.

    2016-01-01

    The efficiency of zero-valent iron particles used in the remediation of contaminated groundwater has, with the emergence of nanotechnology, stimulated interest on the use of nano-size particles to take advantage of high-specific surface area and reactivity characteristics of nanoparticles (NPs). Accordingly, engineered iron-NPs are among the most widely used nanomaterials for in situ remediation. However, while several ecotoxicity studies have been conducted to investigate the adverse impacts of these NPs on aquatic organisms, research on the implications of spent iron-based NPs is lacking. In this study, a comparative approach is used, in which the biological effects of three iron-based NPs (Fe 3 O 4 and γ-Fe 2 O 3 NPs with particle sizes ranging from 20 to 50 nm, and Fe 0 -NPs with an average particle size of 40 nm) on Raphidocelis subcapitata (formely known as Pseudokirchneriella subcapitata) and Daphnia magna were investigated using both as-prepared and pollutant-doped Fe-based NPs. For the latter, arsenic (As) was used as example sorbed pollutant. The results show that improved degree of NP dispersion by use of polyvinylpyrrolidone overlapped with both increased arsenic adsorption capacity and toxicity to the tested organisms. For R. subcapitata, Fe-oxide NPs were more toxic than Fe 0 -NPs, due primarily to differences in the degree of NPs aggregation and ability to produce reactive oxygen species. For the invertebrate D. magna, a similar trend of biological responses was observed, except that sorption of As to Fe 0 -NPs significantly increased the toxic response when compared to R. subcapitata. Overall, these findings point to the need for research on downstream implications of NP-pollutant complexes generated during water treatment by injection of NPs into aquatic systems.

  6. Use of mapping and statistical modelling for the prediction of bluetongue occurrence in Switzerland based on vector biology.

    Science.gov (United States)

    Racloz, Vanessa; Presi, Patrick; Vounatsou, Penelope; Schwermer, Heinzpeter; Casati, Simona; Vanzetti, Tullio; Griot, Christian; Stärk, Katarina D C

    2007-01-01

    Due to the spread of bluetongue (BT) in Europe in the last decade, a sentinel surveillance programme was initiated for Switzerland in 2003, consisting of serological sampling of sentinel cattle tested for BT virus antibodies, as well as entomological trapping of Culicoides midges from June until October. The aim of this study was to create a 'suitability map' of Switzerland, indicating areas of potential disease occurrence based on the biological parameters of Obsoletus Complex habitat. Data on Culicoides catches from insect traps together with various environmental parameters were recorded and analysed. A multiple regression analysis was performed to determine correlation between the environmental conditions and vector abundance. Meteorological data were collected from 50 geo-referenced weather stations across Switzerland and maps of temperature, precipitation and altitude were created. A range of values of temperature, precipitation and altitude influencing vector biology were obtained from the literature. The final combined map highlighted areas in Switzerland which are most suitable for vector presence, hence implying a higher probability of disease occurrence given the presence of susceptible animals. The results confirmed the need for an early warning system for the surveillance of BT disease and its vectors in Switzerland.

  7. Parameter estimation with a novel gradient-based optimization method for biological lattice-gas cellular automaton models.

    Science.gov (United States)

    Mente, Carsten; Prade, Ina; Brusch, Lutz; Breier, Georg; Deutsch, Andreas

    2011-07-01

    Lattice-gas cellular automata (LGCAs) can serve as stochastic mathematical models for collective behavior (e.g. pattern formation) emerging in populations of interacting cells. In this paper, a two-phase optimization algorithm for global parameter estimation in LGCA models is presented. In the first phase, local minima are identified through gradient-based optimization. Algorithmic differentiation is adopted to calculate the necessary gradient information. In the second phase, for global optimization of the parameter set, a multi-level single-linkage method is used. As an example, the parameter estimation algorithm is applied to a LGCA model for early in vitro angiogenic pattern formation.

  8. From biology to mathematical models and back: teaching modeling to biology students, and biology to math and engineering students.

    Science.gov (United States)

    Chiel, Hillel J; McManus, Jeffrey M; Shaw, Kendrick M

    2010-01-01

    We describe the development of a course to teach modeling and mathematical analysis skills to students of biology and to teach biology to students with strong backgrounds in mathematics, physics, or engineering. The two groups of students have different ways of learning material and often have strong negative feelings toward the area of knowledge that they find difficult. To give students a sense of mastery in each area, several complementary approaches are used in the course: 1) a "live" textbook that allows students to explore models and mathematical processes interactively; 2) benchmark problems providing key skills on which students make continuous progress; 3) assignment of students to teams of two throughout the semester; 4) regular one-on-one interactions with instructors throughout the semester; and 5) a term project in which students reconstruct, analyze, extend, and then write in detail about a recently published biological model. Based on student evaluations and comments, an attitude survey, and the quality of the students' term papers, the course has significantly increased the ability and willingness of biology students to use mathematical concepts and modeling tools to understand biological systems, and it has significantly enhanced engineering students' appreciation of biology.

  9. Quantifying bioalbedo: a new physically based model and discussion of empirical methods for characterising biological influence on ice and snow albedo

    Science.gov (United States)

    Cook, Joseph M.; Hodson, Andrew J.; Gardner, Alex S.; Flanner, Mark; Tedstone, Andrew J.; Williamson, Christopher; Irvine-Fynn, Tristram D. L.; Nilsson, Johan; Bryant, Robert; Tranter, Martyn

    2017-11-01

    The darkening effects of biological impurities on ice and snow have been recognised as a control on the surface energy balance of terrestrial snow, sea ice, glaciers and ice sheets. With a heightened interest in understanding the impacts of a changing climate on snow and ice processes, quantifying the impact of biological impurities on ice and snow albedo (bioalbedo) and its evolution through time is a rapidly growing field of research. However, rigorous quantification of bioalbedo has remained elusive because of difficulties in isolating the biological contribution to ice albedo from that of inorganic impurities and the variable optical properties of the ice itself. For this reason, isolation of the biological signature in reflectance data obtained from aerial/orbital platforms has not been achieved, even when ground-based biological measurements have been available. This paper provides the cell-specific optical properties that are required to model the spectral signatures and broadband darkening of ice. Applying radiative transfer theory, these properties provide the physical basis needed to link biological and glaciological ground measurements with remotely sensed reflectance data. Using these new capabilities we confirm that biological impurities can influence ice albedo, then we identify 10 challenges to the measurement of bioalbedo in the field with the aim of improving future experimental designs to better quantify bioalbedo feedbacks. These challenges are (1) ambiguity in terminology, (2) characterising snow or ice optical properties, (3) characterising solar irradiance, (4) determining optical properties of cells, (5) measuring biomass, (6) characterising vertical distribution of cells, (7) characterising abiotic impurities, (8) surface anisotropy, (9) measuring indirect albedo feedbacks, and (10) measurement and instrument configurations. This paper aims to provide a broad audience of glaciologists and biologists with an overview of radiative transfer and

  10. Quantifying bioalbedo: a new physically based model and discussion of empirical methods for characterising biological influence on ice and snow albedo

    Directory of Open Access Journals (Sweden)

    J. M. Cook

    2017-11-01

    Full Text Available The darkening effects of biological impurities on ice and snow have been recognised as a control on the surface energy balance of terrestrial snow, sea ice, glaciers and ice sheets. With a heightened interest in understanding the impacts of a changing climate on snow and ice processes, quantifying the impact of biological impurities on ice and snow albedo (bioalbedo and its evolution through time is a rapidly growing field of research. However, rigorous quantification of bioalbedo has remained elusive because of difficulties in isolating the biological contribution to ice albedo from that of inorganic impurities and the variable optical properties of the ice itself. For this reason, isolation of the biological signature in reflectance data obtained from aerial/orbital platforms has not been achieved, even when ground-based biological measurements have been available. This paper provides the cell-specific optical properties that are required to model the spectral signatures and broadband darkening of ice. Applying radiative transfer theory, these properties provide the physical basis needed to link biological and glaciological ground measurements with remotely sensed reflectance data. Using these new capabilities we confirm that biological impurities can influence ice albedo, then we identify 10 challenges to the measurement of bioalbedo in the field with the aim of improving future experimental designs to better quantify bioalbedo feedbacks. These challenges are (1 ambiguity in terminology, (2 characterising snow or ice optical properties, (3 characterising solar irradiance, (4 determining optical properties of cells, (5 measuring biomass, (6 characterising vertical distribution of cells, (7 characterising abiotic impurities, (8 surface anisotropy, (9 measuring indirect albedo feedbacks, and (10 measurement and instrument configurations. This paper aims to provide a broad audience of glaciologists and biologists with an overview of

  11. Generating Systems Biology Markup Language Models from the Synthetic Biology Open Language.

    Science.gov (United States)

    Roehner, Nicholas; Zhang, Zhen; Nguyen, Tramy; Myers, Chris J

    2015-08-21

    In the context of synthetic biology, model generation is the automated process of constructing biochemical models based on genetic designs. This paper discusses the use cases for model generation in genetic design automation (GDA) software tools and introduces the foundational concepts of standards and model annotation that make this process useful. Finally, this paper presents an implementation of model generation in the GDA software tool iBioSim and provides an example of generating a Systems Biology Markup Language (SBML) model from a design of a 4-input AND sensor written in the Synthetic Biology Open Language (SBOL).

  12. Reconstruction of biological networks based on life science data integration

    Directory of Open Access Journals (Sweden)

    Kormeier Benjamin

    2010-06-01

    Full Text Available For the implementation of the virtual cell, the fundamental question is how to model and simulate complex biological networks. Therefore, based on relevant molecular database and information systems, biological data integration is an essential step in constructing biological networks. In this paper, we will motivate the applications BioDWH - an integration toolkit for building life science data warehouses, CardioVINEdb - a information system for biological data in cardiovascular-disease and VANESA- a network editor for modeling and simulation of biological networks. Based on this integration process, the system supports the generation of biological network models. A case study of a cardiovascular-disease related gene-regulated biological network is also presented.

  13. Institute for Multiscale Modeling of Biological Interactions

    Energy Technology Data Exchange (ETDEWEB)

    Paulaitis, Michael E; Garcia-Moreno, Bertrand; Lenhoff, Abraham

    2009-12-26

    The Institute for Multiscale Modeling of Biological Interactions (IMMBI) has two primary goals: Foster interdisciplinary collaborations among faculty and their research laboratories that will lead to novel applications of multiscale simulation and modeling methods in the biological sciences and engineering; and Building on the unique biophysical/biology-based engineering foundations of the participating faculty, train scientists and engineers to apply computational methods that collectively span multiple time and length scales of biological organization. The success of IMMBI will be defined by the following: Size and quality of the applicant pool for pre-doctoral and post-doctoral fellows; Academic performance; Quality of the pre-doctoral and post-doctoral research; Impact of the research broadly and to the DOE (ASCR program) mission; Distinction of the next career step for pre-doctoral and post-doctoral fellows; and Faculty collaborations that result from IMMBI activities. Specific details about accomplishments during the three years of DOE support for IMMBI have been documented in Annual Progress Reports (April 2005, June 2006, and March 2007) and a Report for a National Academy of Sciences Review (October 2005) that were submitted to DOE on the dates indicated. An overview of these accomplishments is provided.

  14. Structural sensitivity of biological models revisited.

    Science.gov (United States)

    Cordoleani, Flora; Flora, Cordoleani; Nerini, David; David, Nerini; Gauduchon, Mathias; Mathias, Gauduchon; Morozov, Andrew; Andrew, Morozov; Poggiale, Jean-Christophe; Jean-Christophe, Poggiale

    2011-08-21

    Enhancing the predictive power of models in biology is a challenging issue. Among the major difficulties impeding model development and implementation are the sensitivity of outcomes to variations in model parameters, the problem of choosing of particular expressions for the parametrization of functional relations, and difficulties in validating models using laboratory data and/or field observations. In this paper, we revisit the phenomenon which is referred to as structural sensitivity of a model. Structural sensitivity arises as a result of the interplay between sensitivity of model outcomes to variations in parameters and sensitivity to the choice of model functions, and this can be somewhat of a bottleneck in improving the models predictive power. We provide a rigorous definition of structural sensitivity and we show how we can quantify the degree of sensitivity of a model based on the Hausdorff distance concept. We propose a simple semi-analytical test of structural sensitivity in an ODE modeling framework. Furthermore, we emphasize the importance of directly linking the variability of field/experimental data and model predictions, and we demonstrate a way of assessing the robustness of modeling predictions with respect to data sampling variability. As an insightful illustrative example, we test our sensitivity analysis methods on a chemostat predator-prey model, where we use laboratory data on the feeding of protozoa to parameterize the predator functional response. Copyright © 2011 Elsevier Ltd. All rights reserved.

  15. Genetically-Based Biologic Technologies. Biology and Human Welfare.

    Science.gov (United States)

    Mayer, William V.; McInerney, Joseph D.

    The purpose of this six-part booklet is to review the current status of genetically-based biologic technologies and to suggest how information about these technologies can be inserted into existing educational programs. Topic areas included in the six parts are: (1) genetically-based technologies in the curriculum; (2) genetic technologies…

  16. Comprehensive distributed-parameters modeling and experimental validation of microcantilever-based biosensors with an application to ultrasmall biological species detection

    International Nuclear Information System (INIS)

    Faegh, Samira; Jalili, Nader

    2013-01-01

    Nanotechnological advancements have made a great contribution in developing label-free and highly sensitive biosensors. The detection of ultrasmall adsorbed masses has been enabled by such sensors which transduce molecular interaction into detectable physical quantities. More specifically, microcantilever-based biosensors have caught widespread attention for offering a label-free, highly sensitive and inexpensive platform for biodetection. Although there are a lot of studies investigating microcantilever-based sensors and their biological applications, a comprehensive mathematical modeling and experimental validation of such devices providing a closed form mathematical framework is still lacking. In almost all of the studies, a simple lumped-parameters model has been proposed. However, in order to have a precise biomechanical sensor, a comprehensive model is required being capable of describing all phenomena and dynamics of the biosensor. Therefore, in this study, an extensive distributed-parameters modeling framework is proposed for the piezoelectric microcantilever-based biosensor using different methodologies for the purpose of detecting an ultrasmall adsorbed mass over the microcantilever surface. An optimum modeling methodology is concluded and verified with the experiment. This study includes three main parts. In the first part, the Euler–Bernoulli beam theory is used to model the nonuniform piezoelectric microcantilever. Simulation results are obtained and presented. The same system is then modeled as a nonuniform rectangular plate. The simulation results are presented describing model's capability in the detection of an ultrasmall mass. Finally the last part presents the experimental validation verifying the modeling results. It was shown that plate modeling predicts the real situation with a degree of precision of 99.57% whereas modeling the system as an Euler–Bernoulli beam provides a 94.45% degree of precision. The detection of ultrasmall

  17. Continuum Modeling of Biological Network Formation

    KAUST Repository

    Albi, Giacomo

    2017-04-10

    We present an overview of recent analytical and numerical results for the elliptic–parabolic system of partial differential equations proposed by Hu and Cai, which models the formation of biological transportation networks. The model describes the pressure field using a Darcy type equation and the dynamics of the conductance network under pressure force effects. Randomness in the material structure is represented by a linear diffusion term and conductance relaxation by an algebraic decay term. We first introduce micro- and mesoscopic models and show how they are connected to the macroscopic PDE system. Then, we provide an overview of analytical results for the PDE model, focusing mainly on the existence of weak and mild solutions and analysis of the steady states. The analytical part is complemented by extensive numerical simulations. We propose a discretization based on finite elements and study the qualitative properties of network structures for various parameter values.

  18. Central Puget Sound Ecopath/Ecosim model biological parameters - Developing food web models for ecosystem-based management applications in Puget Sound

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This project is developing food web models for ecosystem-based management applications in Puget Sound. It is primarily being done by NMFS FTEs and contractors, in...

  19. PENERAPAN BLENDED-PROBLEM BASED LEARNING DALAM PEMBELAJARAN BIOLOGI

    Directory of Open Access Journals (Sweden)

    Samuel Agus Triyanto

    2016-07-01

    Biologi abad 21 merupakan integrasi dan mengintegrasikan kembali sub disiplin ilmu biologi, serta integrasi biologi dengan disiplin ilmu lain untuk mengatasi permasalahan sosial. Penelitian ini bertujuan untuk mengetahui penerapan Blended-Problem Based Learning, aktivitas belajar, dan respon siswa dalam pembelajaran biologi. Penelitian ini merupakan penelitian survei dengan pendekatan deskriptif kualitatif. Data hasil penelitian menunjukkan bahwa aktivitas positif siswa dalam pembelajaran memuaskan, sedangkan respon siswa baik terhadap pembelajaran. Berdasarkan hasil penelitian, disimpulkan bahwa Blended-Problem Based Learning dapat diterapkan dan diterima sebagai model dalam pembelajaran.

  20. Cellular potts models multiscale extensions and biological applications

    CERN Document Server

    Scianna, Marco

    2013-01-01

    A flexible, cell-level, and lattice-based technique, the cellular Potts model accurately describes the phenomenological mechanisms involved in many biological processes. Cellular Potts Models: Multiscale Extensions and Biological Applications gives an interdisciplinary, accessible treatment of these models, from the original methodologies to the latest developments. The book first explains the biophysical bases, main merits, and limitations of the cellular Potts model. It then proposes several innovative extensions, focusing on ways to integrate and interface the basic cellular Potts model at the mesoscopic scale with approaches that accurately model microscopic dynamics. These extensions are designed to create a nested and hybrid environment, where the evolution of a biological system is realistically driven by the constant interplay and flux of information between the different levels of description. Through several biological examples, the authors demonstrate a qualitative and quantitative agreement with t...

  1. Piecewise deterministic processes in biological models

    CERN Document Server

    Rudnicki, Ryszard

    2017-01-01

    This book presents a concise introduction to piecewise deterministic Markov processes (PDMPs), with particular emphasis on their applications to biological models. Further, it presents examples of biological phenomena, such as gene activity and population growth, where different types of PDMPs appear: continuous time Markov chains, deterministic processes with jumps, processes with switching dynamics, and point processes. Subsequent chapters present the necessary tools from the theory of stochastic processes and semigroups of linear operators, as well as theoretical results concerning the long-time behaviour of stochastic semigroups induced by PDMPs and their applications to biological models. As such, the book offers a valuable resource for mathematicians and biologists alike. The first group will find new biological models that lead to interesting and often new mathematical questions, while the second can observe how to include seemingly disparate biological processes into a unified mathematical theory, and...

  2. Spherical Cancer Models in Tumor Biology

    Directory of Open Access Journals (Sweden)

    Louis-Bastien Weiswald

    2015-01-01

    Full Text Available Three-dimensional (3D in vitro models have been used in cancer research as an intermediate model between in vitro cancer cell line cultures and in vivo tumor. Spherical cancer models represent major 3D in vitro models that have been described over the past 4 decades. These models have gained popularity in cancer stem cell research using tumorospheres. Thus, it is crucial to define and clarify the different spherical cancer models thus far described. Here, we focus on in vitro multicellular spheres used in cancer research. All these spherelike structures are characterized by their well-rounded shape, the presence of cancer cells, and their capacity to be maintained as free-floating cultures. We propose a rational classification of the four most commonly used spherical cancer models in cancer research based on culture methods for obtaining them and on subsequent differences in sphere biology: the multicellular tumor spheroid model, first described in the early 70s and obtained by culture of cancer cell lines under nonadherent conditions; tumorospheres, a model of cancer stem cell expansion established in a serum-free medium supplemented with growth factors; tissue-derived tumor spheres and organotypic multicellular spheroids, obtained by tumor tissue mechanical dissociation and cutting. In addition, we describe their applications to and interest in cancer research; in particular, we describe their contribution to chemoresistance, radioresistance, tumorigenicity, and invasion and migration studies. Although these models share a common 3D conformation, each displays its own intrinsic properties. Therefore, the most relevant spherical cancer model must be carefully selected, as a function of the study aim and cancer type.

  3. Spherical cancer models in tumor biology.

    Science.gov (United States)

    Weiswald, Louis-Bastien; Bellet, Dominique; Dangles-Marie, Virginie

    2015-01-01

    Three-dimensional (3D) in vitro models have been used in cancer research as an intermediate model between in vitro cancer cell line cultures and in vivo tumor. Spherical cancer models represent major 3D in vitro models that have been described over the past 4 decades. These models have gained popularity in cancer stem cell research using tumorospheres. Thus, it is crucial to define and clarify the different spherical cancer models thus far described. Here, we focus on in vitro multicellular spheres used in cancer research. All these spherelike structures are characterized by their well-rounded shape, the presence of cancer cells, and their capacity to be maintained as free-floating cultures. We propose a rational classification of the four most commonly used spherical cancer models in cancer research based on culture methods for obtaining them and on subsequent differences in sphere biology: the multicellular tumor spheroid model, first described in the early 70s and obtained by culture of cancer cell lines under nonadherent conditions; tumorospheres, a model of cancer stem cell expansion established in a serum-free medium supplemented with growth factors; tissue-derived tumor spheres and organotypic multicellular spheroids, obtained by tumor tissue mechanical dissociation and cutting. In addition, we describe their applications to and interest in cancer research; in particular, we describe their contribution to chemoresistance, radioresistance, tumorigenicity, and invasion and migration studies. Although these models share a common 3D conformation, each displays its own intrinsic properties. Therefore, the most relevant spherical cancer model must be carefully selected, as a function of the study aim and cancer type. Copyright © 2014 Neoplasia Press, Inc. Published by Elsevier Inc. All rights reserved.

  4. Stochastic modelling of dynamical systems in biology

    NARCIS (Netherlands)

    Pellin, Danilo

    2017-01-01

    In this thesis two relevant biological problems will be addressed from a statistical modelling perspective. The first regards the study of hematopoiesis, a still not well understood biological process rarely observable in humans due to technical and ethical reasons. Hematopoiesis is responsible for

  5. Multiscale mechanical modeling of soft biological tissues

    Science.gov (United States)

    Stylianopoulos, Triantafyllos

    2008-10-01

    Soft biological tissues include both native and artificial tissues. In the human body, tissues like the articular cartilage, arterial wall, and heart valve leaflets are examples of structures composed of an underlying network of collagen fibers, cells, proteins and molecules. Artificial tissues are less complex than native tissues and mainly consist of a fiber polymer network with the intent of replacing lost or damaged tissue. Understanding of the mechanical function of these materials is essential for many clinical treatments (e.g. arterial clamping, angioplasty), diseases (e.g. arteriosclerosis) and tissue engineering applications (e.g. engineered blood vessels or heart valves). This thesis presents the derivation and application of a multiscale methodology to describe the macroscopic mechanical function of soft biological tissues incorporating directly their structural architecture. The model, which is based on volume averaging theory, accounts for structural parameters such as the network volume fraction and orientation, the realignment of the fibers in response to strain, the interactions among the fibers and the interactions between the fibers and the interstitial fluid in order to predict the overall tissue behavior. Therefore, instead of using a constitutive equation to relate strain to stress, the tissue microstructure is modeled within a representative volume element (RVE) and the macroscopic response at any point in the tissue is determined by solving a micromechanics problem in the RVE. The model was applied successfully to acellular collagen gels, native blood vessels, and electrospun polyurethane scaffolds and provided accurate predictions for permeability calculations in isotropic and oriented fiber networks. The agreement of model predictions with experimentally determined mechanical properties provided insights into the mechanics of tissues and tissue constructs, while discrepancies revealed limitations of the model framework.

  6. Modelling collagen diseases: STRUCTURAL BIOLOGY

    OpenAIRE

    Brodsky, Barbara; Baum, Jean

    2008-01-01

    Mutations in collagen lead to hereditary disorders such as brittle-bone disease. Peptide models for aberrant collagens are beginning to clarify how these amino-acid replacements lead to clinical problems.

  7. Setting Parameters for Biological Models With ANIMO

    NARCIS (Netherlands)

    Schivo, Stefano; Scholma, Jetse; Karperien, Hermanus Bernardus Johannes; Post, Janine Nicole; van de Pol, Jan Cornelis; Langerak, Romanus; André, Étienne; Frehse, Goran

    2014-01-01

    ANIMO (Analysis of Networks with Interactive MOdeling) is a software for modeling biological networks, such as e.g. signaling, metabolic or gene networks. An ANIMO model is essentially the sum of a network topology and a number of interaction parameters. The topology describes the interactions

  8. Medulloblastoma: toward biologically based management.

    Science.gov (United States)

    Samkari, Ayman; White, Jason C; Packer, Roger J

    2015-03-01

    Medulloblastoma is the most common malignant brain tumor in children and, as such, has been the focus of tremendous efforts to genomically characterize it. What was once thought to be a single disease has been divided into multiple, molecularly unique subgroups through gene expression profiling. Each subgroup is not only unique in its origin and pathogenesis but also in the prognosis and potential therapeutic options. Targeted therapy of malignancies has long been the goal of clinical oncology. The progress made in the classification of medulloblastoma should be used as a model for future studies. With the evolution of epigenetic and genomic sequencing, especially when used in tandem with high-throughput pharmacologic screening protocols, the potential for subgroup-specific targeting is closer than ever. This review focuses on the development of the molecular classification system and its potential use in developing prognostic models as well as for the advancement of targeted therapeutic interventions. Copyright © 2015 Elsevier Inc. All rights reserved.

  9. Nonlinear Rheology in a Model Biological Tissue.

    Science.gov (United States)

    Matoz-Fernandez, D A; Agoritsas, Elisabeth; Barrat, Jean-Louis; Bertin, Eric; Martens, Kirsten

    2017-04-14

    The rheological response of dense active matter is a topic of fundamental importance for many processes in nature such as the mechanics of biological tissues. One prominent way to probe mechanical properties of tissues is to study their response to externally applied forces. Using a particle-based model featuring random apoptosis and environment-dependent division rates, we evidence a crossover from linear flow to a shear-thinning regime with an increasing shear rate. To rationalize this nonlinear flow we derive a theoretical mean-field scenario that accounts for the interplay of mechanical and active noise in local stresses. These noises are, respectively, generated by the elastic response of the cell matrix to cell rearrangements and by the internal activity.

  10. From biological membranes to biomimetic model membranes

    Directory of Open Access Journals (Sweden)

    Eeman, M.

    2010-01-01

    Full Text Available Biological membranes play an essential role in the cellular protection as well as in the control and the transport of nutrients. Many mechanisms such as molecular recognition, enzymatic catalysis, cellular adhesion and membrane fusion take place into the biological membranes. In 1972, Singer et al. provided a membrane model, called fluid mosaic model, in which each leaflet of the bilayer is formed by a homogeneous environment of lipids in a fluid state including globular assembling of proteins and glycoproteins. Since its conception in 1972, many developments were brought to this model in terms of composition and molecular organization. The main development of the fluid mosaic model was made by Simons et al. (1997 and Brown et al. (1997 who suggested that membrane lipids are organized into lateral microdomains (or lipid rafts with a specific composition and a molecular dynamic that are different to the composition and the dynamic of the surrounding liquid crystalline phase. The discovery of a phase separation in the plane of the membrane has induced an explosion in the research efforts related to the biology of cell membranes but also in the development of new technologies for the study of these biological systems. Due to the high complexity of biological membranes and in order to investigate the biological processes that occur on the membrane surface or within the membrane lipid bilayer, a large number of studies are performed using biomimicking model membranes. This paper aims at revisiting the fundamental properties of biological membranes in terms of membrane composition, membrane dynamic and molecular organization, as well as at describing the most common biomimicking models that are frequently used for investigating biological processes such as membrane fusion, membrane trafficking, pore formation as well as membrane interactions at a molecular level.

  11. Structured population models in biology and epidemiology

    CERN Document Server

    Ruan, Shigui

    2008-01-01

    This book consists of six chapters written by leading researchers in mathematical biology. These chapters present recent and important developments in the study of structured population models in biology and epidemiology. Topics include population models structured by age, size, and spatial position; size-structured models for metapopulations, macroparasitc diseases, and prion proliferation; models for transmission of microparasites between host populations living on non-coincident spatial domains; spatiotemporal patterns of disease spread; method of aggregation of variables in population dynamics; and biofilm models. It is suitable as a textbook for a mathematical biology course or a summer school at the advanced undergraduate and graduate level. It can also serve as a reference book for researchers looking for either interesting and specific problems to work on or useful techniques and discussions of some particular problems.

  12. Unified data model for biological data

    International Nuclear Information System (INIS)

    Idrees, M.

    2014-01-01

    A data model empowers us to store, retrieve and manipulate data in a unified way. We consider the biological data consists of DNA (De-Oxyribonucleic Acid), RNA (Ribonucleic Acid) and protein structures. In our Bioinformatics Lab (Bioinformatics Lab, Alkhawarizmi Institute of Computer Science, University of Engineering and Technology, Lahore, Pakistan), we have already proposed two data models for DNA and protein structures individually. In this paper, we propose a unified data model by using the data models of TOS (Temporal Object Oriented System) after making some necessary modifications to this data model and our already proposed the two data models. This proposed unified data model can be used for the modeling and maintaining the biological data (i.e. DNA, RNA and protein structures), in a single unified way. (author)

  13. Bridging physics and biology teaching through modeling

    Science.gov (United States)

    Hoskinson, Anne-Marie; Couch, Brian A.; Zwickl, Benjamin M.; Hinko, Kathleen A.; Caballero, Marcos D.

    2014-05-01

    As the frontiers of biology become increasingly interdisciplinary, the physics education community has engaged in ongoing efforts to make physics classes more relevant to life science majors. These efforts are complicated by the many apparent differences between these fields, including the types of systems that each studies, the behavior of those systems, the kinds of measurements that each makes, and the role of mathematics in each field. Nonetheless, physics and biology are both sciences that rely on observations and measurements to construct models of the natural world. In this article, we propose that efforts to bridge the teaching of these two disciplines must emphasize shared scientific practices, particularly scientific modeling. We define modeling using language common to both disciplines and highlight how an understanding of the modeling process can help reconcile apparent differences between the teaching of physics and biology. We elaborate on how models can be used for explanatory, predictive, and functional purposes and present common models from each discipline demonstrating key modeling principles. By framing interdisciplinary teaching in the context of modeling, we aim to bridge physics and biology teaching and to equip students with modeling competencies applicable in any scientific discipline.

  14. Biological bases of human musicality.

    Science.gov (United States)

    Perrone-Capano, Carla; Volpicelli, Floriana; di Porzio, Umberto

    2017-04-01

    Music is a universal language, present in all human societies. It pervades the lives of most human beings and can recall memories and feelings of the past, can exert positive effects on our mood, can be strongly evocative and ignite intense emotions, and can establish or strengthen social bonds. In this review, we summarize the research and recent progress on the origins and neural substrates of human musicality as well as the changes in brain plasticity elicited by listening or performing music. Indeed, music improves performance in a number of cognitive tasks and may have beneficial effects on diseased brains. The emerging picture begins to unravel how and why particular brain circuits are affected by music. Numerous studies show that music affects emotions and mood, as it is strongly associated with the brain's reward system. We can therefore assume that an in-depth study of the relationship between music and the brain may help to shed light on how the mind works and how the emotions arise and may improve the methods of music-based rehabilitation for people with neurological disorders. However, many facets of the mind-music connection still remain to be explored and enlightened.

  15. Biological efficacy of two mineral trioxide aggregate (MTA)-based materials in a canine model of pulpotomy.

    Science.gov (United States)

    Lee, Myeongyeon; Kang, Chung-Min; Song, Je Seon; Shin, Yooseok; Kim, Seunghye; Kim, Seong-Oh; Choi, Hyung-Jun

    2017-01-31

    The aim of this study was to compare the biocompatibility of Endocem Zr ® and ProRoot MTA ® by histopathologic analysis in a canine model of pulpotomy. This study utilized 39 teeth of two beagle dogs. The exposed pulp tissues were treated by pulpotomy using ProRoot MTA (n=19) or Endocem Zr (n=20). After 8 weeks, the teeth were extracted and processed with hematoxylin-eosin staining for histologic evaluation. Most of the specimens in both groups developed a calcific barrier at the pulp amputation site and formed an odontoblast layer. However, some of the Endocem Zr specimens showed less calcific barrier formation with a greater inflammatory response and less odontoblast layer formation when compared with the ProRoot MTA specimens. ProRoot MTA and Endocem Zr specimens developed a calcific barrier; however, ProRoot MTA was more biocompatible than Endocem Zr.

  16. Biological Treatment of Solvent-Based Paint

    Science.gov (United States)

    2011-01-01

    COVERED (From - To) Mar 2005- Mar 2010 4. TITLE AND SUBTITLE Biological Treatment of Solvent-Based Paint 5a. CONTRACT NUMBER WP 200520 5b...GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Torres, Tom; Hoffard, Theresa 5d. PROJECT NUMBER WP 200520 Lagerquist, Jenny 5e. TASK...nonhazardous and can be landfarmed, composted , or captured in a filter press and landfilled. Most industrial biological treatment systems will also require

  17. Introduction to stochastic models in biology

    DEFF Research Database (Denmark)

    Ditlevsen, Susanne; Samson, Adeline

    2013-01-01

    This chapter is concerned with continuous time processes, which are often modeled as a system of ordinary differential equations (ODEs). These models assume that the observed dynamics are driven exclusively by internal, deterministic mechanisms. However, real biological systems will always be exp...

  18. Dose-volume and biological-model based comparison between helical tomotherapy and (inverse-planned) IMAT for prostate tumours

    International Nuclear Information System (INIS)

    Iori, Mauro; Cattaneo, Giovanni Mauro; Cagni, Elisabetta; Fiorino, Claudio; Borasi, Gianni; Riccardo, Calandrino; Iotti, Cinzia; Fazio, Ferruccio; Nahum, Alan E.

    2008-01-01

    Background and purpose: Helical tomotherapy (HT) and intensity-modulated arc therapy (IMAT) are two arc-based approaches to the delivery of intensity-modulated radiotherapy (IMRT). Through plan comparisons we have investigated the potential of IMAT, both with constant (conventional or IMAT-C) and variable (non-conventional or IMAT-NC, a theoretical exercise) dose-rate, to serve as an alternative to helical tomotherapy. Materials and methods: Six patients with prostate tumours treated by HT with a moderately hypo-fractionated protocol, involving a simultaneous integrated boost, were re-planned as IMAT treatments. A method for IMAT inverse-planning using a commercial module for static IMRT combined with a multi-leaf collimator (MLC) arc-sequencing was developed. IMAT plans were compared to HT plans in terms of dose statistics and radiobiological indices. Results: Concerning the planning target volume (PTV), the mean doses for all PTVs were similar for HT and IMAT-C plans with minimum dose, target coverage, equivalent uniform dose (EUD) and tumour control probability (TCP) values being generally higher for HT; maximum dose and degree of heterogeneity were instead higher for IMAT-C. In relation to organs at risk, mean doses and normal tissue complication probability (NTCP) values were similar between the two modalities, except for the penile bulb where IMAT was significantly better. Re-normalizing all plans to the same rectal toxicity (NTCP = 5%), the HT modality yielded higher TCP than IMAT-C but there was no significant difference between HT and IMAT-NC. The integral dose with HT was higher than that for IMAT. Conclusions: with regards to the plan analysis, the HT is superior to IMAT-C in terms of target coverage and dose homogeneity within the PTV. Introducing dose-rate variation during arc-rotation, not deliverable with current linac technology, the simulations result in comparable plan indices between (IMAT-NC) and HT

  19. Histological image classification using biologically interpretable shape-based features

    International Nuclear Information System (INIS)

    Kothari, Sonal; Phan, John H; Young, Andrew N; Wang, May D

    2013-01-01

    Automatic cancer diagnostic systems based on histological image classification are important for improving therapeutic decisions. Previous studies propose textural and morphological features for such systems. These features capture patterns in histological images that are useful for both cancer grading and subtyping. However, because many of these features lack a clear biological interpretation, pathologists may be reluctant to adopt these features for clinical diagnosis. We examine the utility of biologically interpretable shape-based features for classification of histological renal tumor images. Using Fourier shape descriptors, we extract shape-based features that capture the distribution of stain-enhanced cellular and tissue structures in each image and evaluate these features using a multi-class prediction model. We compare the predictive performance of the shape-based diagnostic model to that of traditional models, i.e., using textural, morphological and topological features. The shape-based model, with an average accuracy of 77%, outperforms or complements traditional models. We identify the most informative shapes for each renal tumor subtype from the top-selected features. Results suggest that these shapes are not only accurate diagnostic features, but also correlate with known biological characteristics of renal tumors. Shape-based analysis of histological renal tumor images accurately classifies disease subtypes and reveals biologically insightful discriminatory features. This method for shape-based analysis can be extended to other histological datasets to aid pathologists in diagnostic and therapeutic decisions

  20. Setting Parameters for Biological Models With ANIMO

    Directory of Open Access Journals (Sweden)

    Stefano Schivo

    2014-03-01

    Full Text Available ANIMO (Analysis of Networks with Interactive MOdeling is a software for modeling biological networks, such as e.g. signaling, metabolic or gene networks. An ANIMO model is essentially the sum of a network topology and a number of interaction parameters. The topology describes the interactions between biological entities in form of a graph, while the parameters determine the speed of occurrence of such interactions. When a mismatch is observed between the behavior of an ANIMO model and experimental data, we want to update the model so that it explains the new data. In general, the topology of a model can be expanded with new (known or hypothetical nodes, and enables it to match experimental data. However, the unrestrained addition of new parts to a model causes two problems: models can become too complex too fast, to the point of being intractable, and too many parts marked as "hypothetical" or "not known" make a model unrealistic. Even if changing the topology is normally the easier task, these problems push us to try a better parameter fit as a first step, and resort to modifying the model topology only as a last resource. In this paper we show the support added in ANIMO to ease the task of expanding the knowledge on biological networks, concentrating in particular on the parameter settings.

  1. Mathematical models in biology bringing mathematics to life

    CERN Document Server

    Ferraro, Maria; Guarracino, Mario

    2015-01-01

    This book presents an exciting collection of contributions based on the workshop “Bringing Maths to Life” held October 27-29, 2014 in Naples, Italy.  The state-of-the art research in biology and the statistical and analytical challenges facing huge masses of data collection are treated in this Work. Specific topics explored in depth surround the sessions and special invited sessions of the workshop and include genetic variability via differential expression, molecular dynamics and modeling, complex biological systems viewed from quantitative models, and microscopy images processing, to name several. In depth discussions of the mathematical analysis required to extract insights from complex bodies of biological datasets, to aid development in the field novel algorithms, methods and software tools for genetic variability, molecular dynamics, and complex biological systems are presented in this book. Researchers and graduate students in biology, life science, and mathematics/statistics will find the content...

  2. Biological Based Risk Assessment for Space Exploration

    Science.gov (United States)

    Cucinotta, Francis A.

    2011-01-01

    Exposures from galactic cosmic rays (GCR) - made up of high-energy protons and high-energy and charge (HZE) nuclei, and solar particle events (SPEs) - comprised largely of low- to medium-energy protons are the primary health concern for astronauts for long-term space missions. Experimental studies have shown that HZE nuclei produce both qualitative and quantitative differences in biological effects compared to terrestrial radiation, making risk assessments for cancer and degenerative risks, such as central nervous system effects and heart disease, highly uncertain. The goal for space radiation protection at NASA is to be able to reduce the uncertainties in risk assessments for Mars exploration to be small enough to ensure acceptable levels of risks are not exceeded and to adequately assess the efficacy of mitigation measures such as shielding or biological countermeasures. We review the recent BEIR VII and UNSCEAR-2006 models of cancer risks and their uncertainties. These models are shown to have an inherent 2-fold uncertainty as defined by ratio of the 95% percent confidence level to the mean projection, even before radiation quality is considered. In order to overcome the uncertainties in these models, new approaches to risk assessment are warranted. We consider new computational biology approaches to modeling cancer risks. A basic program of research that includes stochastic descriptions of the physics and chemistry of radiation tracks and biochemistry of metabolic pathways, to emerging biological understanding of cellular and tissue modifications leading to cancer is described.

  3. Systematic integration of experimental data and models in systems biology.

    Science.gov (United States)

    Li, Peter; Dada, Joseph O; Jameson, Daniel; Spasic, Irena; Swainston, Neil; Carroll, Kathleen; Dunn, Warwick; Khan, Farid; Malys, Naglis; Messiha, Hanan L; Simeonidis, Evangelos; Weichart, Dieter; Winder, Catherine; Wishart, Jill; Broomhead, David S; Goble, Carole A; Gaskell, Simon J; Kell, Douglas B; Westerhoff, Hans V; Mendes, Pedro; Paton, Norman W

    2010-11-29

    The behaviour of biological systems can be deduced from their mathematical models. However, multiple sources of data in diverse forms are required in the construction of a model in order to define its components and their biochemical reactions, and corresponding parameters. Automating the assembly and use of systems biology models is dependent upon data integration processes involving the interoperation of data and analytical resources. Taverna workflows have been developed for the automated assembly of quantitative parameterised metabolic networks in the Systems Biology Markup Language (SBML). A SBML model is built in a systematic fashion by the workflows which starts with the construction of a qualitative network using data from a MIRIAM-compliant genome-scale model of yeast metabolism. This is followed by parameterisation of the SBML model with experimental data from two repositories, the SABIO-RK enzyme kinetics database and a database of quantitative experimental results. The models are then calibrated and simulated in workflows that call out to COPASIWS, the web service interface to the COPASI software application for analysing biochemical networks. These systems biology workflows were evaluated for their ability to construct a parameterised model of yeast glycolysis. Distributed information about metabolic reactions that have been described to MIRIAM standards enables the automated assembly of quantitative systems biology models of metabolic networks based on user-defined criteria. Such data integration processes can be implemented as Taverna workflows to provide a rapid overview of the components and their relationships within a biochemical system.

  4. Prototype Biology-Based Radiation Risk Module Project

    Science.gov (United States)

    Terrier, Douglas; Clayton, Ronald G.; Patel, Zarana; Hu, Shaowen; Huff, Janice

    2015-01-01

    Biological effects of space radiation and risk mitigation are strategic knowledge gaps for the Evolvable Mars Campaign. The current epidemiology-based NASA Space Cancer Risk (NSCR) model contains large uncertainties (HAT #6.5a) due to lack of information on the radiobiology of galactic cosmic rays (GCR) and lack of human data. The use of experimental models that most accurately replicate the response of human tissues is critical for precision in risk projections. Our proposed study will compare DNA damage, histological, and cell kinetic parameters after irradiation in normal 2D human cells versus 3D tissue models, and it will use a multi-scale computational model (CHASTE) to investigate various biological processes that may contribute to carcinogenesis, including radiation-induced cellular signaling pathways. This cross-disciplinary work, with biological validation of an evolvable mathematical computational model, will help reduce uncertainties within NSCR and aid risk mitigation for radiation-induced carcinogenesis.

  5. Inferring Biological Mechanisms by Data-Based Mathematical Modelling: Compartment-Specific Gene Activation during Sporulation in Bacillus subtilis as a Test Case.

    Science.gov (United States)

    Iber, Dagmar

    2011-01-01

    Biological functionality arises from the complex interactions of simple components. Emerging behaviour is difficult to recognize with verbal models alone, and mathematical approaches are important. Even few interacting components can give rise to a wide range of different responses, that is, sustained, transient, oscillatory, switch-like responses, depending on the values of the model parameters. A quantitative comparison of model predictions and experiments is therefore important to distinguish between competing hypotheses and to judge whether a certain regulatory behaviour is at all possible and plausible given the observed type and strengths of interactions and the speed of reactions. Here I will review a detailed model for the transcription factor σ(F), a regulator of cell differentiation during sporulation in Bacillus subtilis. I will focus in particular on the type of conclusions that can be drawn from detailed, carefully validated models of biological signaling networks. For most systems, such detailed experimental information is currently not available, but accumulating biochemical data through technical advances are likely to enable the detailed modelling of an increasing number of pathways. A major challenge will be the linking of such detailed models and their integration into a multiscale framework to enable their analysis in a larger biological context.

  6. Inferring Biological Mechanisms by Data-Based Mathematical Modelling: Compartment-Specific Gene Activation during Sporulation in Bacillus subtilis as a Test Case

    Directory of Open Access Journals (Sweden)

    Dagmar Iber

    2011-01-01

    Full Text Available Biological functionality arises from the complex interactions of simple components. Emerging behaviour is difficult to recognize with verbal models alone, and mathematical approaches are important. Even few interacting components can give rise to a wide range of different responses, that is, sustained, transient, oscillatory, switch-like responses, depending on the values of the model parameters. A quantitative comparison of model predictions and experiments is therefore important to distinguish between competing hypotheses and to judge whether a certain regulatory behaviour is at all possible and plausible given the observed type and strengths of interactions and the speed of reactions. Here I will review a detailed model for the transcription factor , a regulator of cell differentiation during sporulation in Bacillus subtilis. I will focus in particular on the type of conclusions that can be drawn from detailed, carefully validated models of biological signaling networks. For most systems, such detailed experimental information is currently not available, but accumulating biochemical data through technical advances are likely to enable the detailed modelling of an increasing number of pathways. A major challenge will be the linking of such detailed models and their integration into a multiscale framework to enable their analysis in a larger biological context.

  7. Modelling biological pathway dynamics with Timed Automata

    NARCIS (Netherlands)

    Schivo, Stefano; Scholma, Jetse; Urquidi Camacho, R.A.; Wanders, B.; van der Vet, P.E.; Karperien, Hermanus Bernardus Johannes; Langerak, Romanus; van de Pol, Jan Cornelis; Post, Janine Nicole

    2012-01-01

    When analysing complex interaction networks occurring in biological cells, a biologist needs computational support in order to understand the effects of signalling molecules (e.g. growth factors, drugs). ANIMO (Analysis of Networks with Interactive MOdelling) is a tool that allows the user to create

  8. Biocellion: accelerating computer simulation of multicellular biological system models.

    Science.gov (United States)

    Kang, Seunghwa; Kahan, Simon; McDermott, Jason; Flann, Nicholas; Shmulevich, Ilya

    2014-11-01

    Biological system behaviors are often the outcome of complex interactions among a large number of cells and their biotic and abiotic environment. Computational biologists attempt to understand, predict and manipulate biological system behavior through mathematical modeling and computer simulation. Discrete agent-based modeling (in combination with high-resolution grids to model the extracellular environment) is a popular approach for building biological system models. However, the computational complexity of this approach forces computational biologists to resort to coarser resolution approaches to simulate large biological systems. High-performance parallel computers have the potential to address the computing challenge, but writing efficient software for parallel computers is difficult and time-consuming. We have developed Biocellion, a high-performance software framework, to solve this computing challenge using parallel computers. To support a wide range of multicellular biological system models, Biocellion asks users to provide their model specifics by filling the function body of pre-defined model routines. Using Biocellion, modelers without parallel computing expertise can efficiently exploit parallel computers with less effort than writing sequential programs from scratch. We simulate cell sorting, microbial patterning and a bacterial system in soil aggregate as case studies. Biocellion runs on x86 compatible systems with the 64 bit Linux operating system and is freely available for academic use. Visit http://biocellion.com for additional information. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  9. Modeling nonspecific interactions at biological interfaces

    Science.gov (United States)

    White, Andrew D.

    Difficulties in applied biomaterials often arise from the complexities of interactions in biological environments. These interactions can be broadly broken into two categories: those which are important to function (strong binding to a single target) and those which are detrimental to function (weak binding to many targets). These will be referred to as specific and nonspecific interactions, respectively. Nonspecific interactions have been central to failures of biomaterials, sensors, and surface coatings in harsh biological environments. There is little modeling work on studying nonspecific interactions. Modeling all possible nonspecific interactions within a biological system is difficult, yet there are ways to both indirectly model nonspecific interactions and directly model many interactions using machine-learning. This research utilizes bioinformatics, phenomenological modeling, molecular simulations, experiments, and stochastic modeling to study nonspecific interactions. These techniques are used to study the hydration molecules which resist nonspecific interactions, the formation of salt bridges, the chemistry of protein surfaces, nonspecific stabilization of proteins in molecular chaperones, and analysis of high-throughput screening experiments. The common aspect for these systems is that nonspecific interactions are more important than specific interactions. Studying these disparate systems has created a set of principles for resisting nonspecific interactions which have been experimentally demonstrated with the creation and testing of novel materials which resist nonspecific interactions.

  10. A symmetry model for genetic coding via a wallpaper group composed of the traditional four bases and an imaginary base E: towards category theory-like systematization of molecular/genetic biology.

    Science.gov (United States)

    Sawamura, Jitsuki; Morishita, Shigeru; Ishigooka, Jun

    2014-05-07

    Previously, we suggested prototypal models that describe some clinical states based on group postulates. Here, we demonstrate a group/category theory-like model for molecular/genetic biology as an alternative application of our previous model. Specifically, we focus on deoxyribonucleic acid (DNA) base sequences. We construct a wallpaper pattern based on a five-letter cruciform motif with letters C, A, T, G, and E. Whereas the first four letters represent the standard DNA bases, the fifth is introduced for ease in formulating group operations that reproduce insertions and deletions of DNA base sequences. A basic group Z5 = {r, u, d, l, n} of operations is defined for the wallpaper pattern, with which a sequence of points can be generated corresponding to changes of a base in a DNA sequence by following the orbit of a point of the pattern under operations in group Z5. Other manipulations of DNA sequence can be treated using a vector-like notation 'Dj' corresponding to a DNA sequence but based on the five-letter base set; also, 'Dj's are expressed graphically. Insertions and deletions of a series of letters 'E' are admitted to assist in describing DNA recombination. Likewise, a vector-like notation Rj can be constructed for sequences of ribonucleic acid (RNA). The wallpaper group B = {Z5×∞, ●} (an ∞-fold Cartesian product of Z5) acts on Dj (or Rj) yielding changes to Dj (or Rj) denoted by 'Dj◦B(j→k) = Dk' (or 'Rj◦B(j→k) = Rk'). Based on the operations of this group, two types of groups-a modulo 5 linear group and a rotational group over the Gaussian plane, acting on the five bases-are linked as parts of the wallpaper group for broader applications. As a result, changes, insertions/deletions and DNA (RNA) recombination (partial/total conversion) are described. As an exploratory study, a notation for the canonical "central dogma" via a category theory-like way is presented for future developments. Despite the large incompleteness of our

  11. Modeling and simulation of biological systems using SPICE language

    Science.gov (United States)

    Lallement, Christophe; Haiech, Jacques

    2017-01-01

    The article deals with BB-SPICE (SPICE for Biochemical and Biological Systems), an extension of the famous Simulation Program with Integrated Circuit Emphasis (SPICE). BB-SPICE environment is composed of three modules: a new textual and compact description formalism for biological systems, a converter that handles this description and generates the SPICE netlist of the equivalent electronic circuit and NGSPICE which is an open-source SPICE simulator. In addition, the environment provides back and forth interfaces with SBML (System Biology Markup Language), a very common description language used in systems biology. BB-SPICE has been developed in order to bridge the gap between the simulation of biological systems on the one hand and electronics circuits on the other hand. Thus, it is suitable for applications at the interface between both domains, such as development of design tools for synthetic biology and for the virtual prototyping of biosensors and lab-on-chip. Simulation results obtained with BB-SPICE and COPASI (an open-source software used for the simulation of biochemical systems) have been compared on a benchmark of models commonly used in systems biology. Results are in accordance from a quantitative viewpoint but BB-SPICE outclasses COPASI by 1 to 3 orders of magnitude regarding the computation time. Moreover, as our software is based on NGSPICE, it could take profit of incoming updates such as the GPU implementation, of the coupling with powerful analysis and verification tools or of the integration in design automation tools (synthetic biology). PMID:28787027

  12. Dynamic simulation and modeling of the motion modes produced during the 3D controlled manipulation of biological micro/nanoparticles based on the AFM.

    Science.gov (United States)

    Saraee, Mahdieh B; Korayem, Moharam H

    2015-08-07

    Determining the motion modes and the exact position of a particle displaced during the manipulation process is of special importance. This issue becomes even more important when the studied particles are biological micro/nanoparticles and the goals of manipulation are the transfer of these particles within body cells, repair of cancerous cells and the delivery of medication to damaged cells. However, due to the delicate nature of biological nanoparticles and their higher vulnerability, by obtaining the necessary force of manipulation for the considered motion mode, we can prevent the sample from interlocking with or sticking to the substrate because of applying a weak force or avoid damaging the sample due to the exertion of excessive force. In this paper, the dynamic behaviors and the motion modes of biological micro/nanoparticles such as DNA, yeast, platelet and bacteria due to the 3D manipulation effect have been investigated. Since the above nanoparticles generally have a cylindrical shape, the cylindrical contact models have been employed in an attempt to more precisely model the forces exerted on the nanoparticle during the manipulation process. Also, this investigation has performed a comprehensive modeling and simulation of all the possible motion modes in 3D manipulation by taking into account the eccentricity of the applied load on the biological nanoparticle. The obtained results indicate that unlike the macroscopic scale, the sliding of nanoparticle on substrate in nano-scale takes place sooner than the other motion modes and that the spinning about the vertical and transverse axes and the rolling of nanoparticle occur later than the other motion modes. The simulation results also indicate that the applied force necessary for the onset of nanoparticle movement and the resulting motion mode depend on the size and aspect ratio of the nanoparticle. Copyright © 2015 Elsevier Ltd. All rights reserved.

  13. Using views of Systems Biology Cloud: application for model building.

    Science.gov (United States)

    Ruebenacker, Oliver; Blinov, Michael

    2011-03-01

    A large and growing network ("cloud") of interlinked terms and records of items of Systems Biology knowledge is available from the web. These items include pathways, reactions, substances, literature references, organisms, and anatomy, all described in different data sets. Here, we discuss how the knowledge from the cloud can be molded into representations (views) useful for data visualization and modeling. We discuss methods to create and use various views relevant for visualization, modeling, and model annotations, while hiding irrelevant details without unacceptable loss or distortion. We show that views are compatible with understanding substances and processes as sets of microscopic compounds and events respectively, which allows the representation of specializations and generalizations as subsets and supersets respectively. We explain how these methods can be implemented based on the bridging ontology Systems Biological Pathway Exchange (SBPAX) in the Systems Biology Linker (SyBiL) we have developed.

  14. An integrated physical and biological model for anaerobic lagoons.

    Science.gov (United States)

    Wu, Binxin; Chen, Zhenbin

    2011-04-01

    A computational fluid dynamics (CFD) model that integrates physical and biological processes for anaerobic lagoons is presented. In the model development, turbulence is represented using a transition k-ω model, heat conduction and solar radiation are included in the thermal model, biological oxygen demand (BOD) reduction is characterized by first-order kinetics, and methane yield rate is expressed as a linear function of temperature. A test of the model applicability is conducted in a covered lagoon digester operated under tropical climate conditions. The commercial CFD software, ANSYS-Fluent, is employed to solve the integrated model. The simulation procedures include solving fluid flow and heat transfer, predicting local resident time based on the converged flow fields, and calculating the BOD reduction and methane production. The simulated results show that monthly methane production varies insignificantly, but the time to achieve a 99% BOD reduction in January is much longer than that in July. Copyright © 2011 Elsevier Ltd. All rights reserved.

  15. Biological Bases for Radiation Adaptive Responses in the Lung

    Energy Technology Data Exchange (ETDEWEB)

    Scott, Bobby R. [Lovelace Biomedical and Environmental Research Inst., Albuquerque, NM (United States); Lin, Yong [Lovelace Biomedical and Environmental Research Inst., Albuquerque, NM (United States); Wilder, Julie [Lovelace Biomedical and Environmental Research Inst., Albuquerque, NM (United States); Belinsky, Steven [Lovelace Biomedical and Environmental Research Inst., Albuquerque, NM (United States)

    2015-03-01

    Our main research objective was to determine the biological bases for low-dose, radiation-induced adaptive responses in the lung, and use the knowledge gained to produce an improved risk model for radiation-induced lung cancer that accounts for activated natural protection, genetic influences, and the role of epigenetic regulation (epiregulation). Currently, low-dose radiation risk assessment is based on the linear-no-threshold hypothesis, which now is known to be unsupported by a large volume of data.

  16. Evaluation of a commercial biologically based IMRT treatment planning system

    International Nuclear Information System (INIS)

    Semenenko, Vladimir A.; Reitz, Bodo; Day, Ellen; Qi, X. Sharon; Miften, Moyed; Li, X. Allen

    2008-01-01

    A new inverse treatment planning system (TPS) for external beam radiation therapy with high energy photons is commercially available that utilizes both dose-volume-based cost functions and a selection of cost functions which are based on biological models. The purpose of this work is to evaluate quality of intensity-modulated radiation therapy (IMRT) plans resulting from the use of biological cost functions in comparison to plans designed using a traditional TPS employing dose-volume-based optimization. Treatment planning was performed independently at two institutions. For six cancer patients, including head and neck (one case from each institution), prostate, brain, liver, and rectal cases, segmental multileaf collimator IMRT plans were designed using biological cost functions and compared with clinically used dose-based plans for the same patients. Dose-volume histograms and dosimetric indices, such as minimum, maximum, and mean dose, were extracted and compared between the two types of treatment plans. Comparisons of the generalized equivalent uniform dose (EUD), a previously proposed plan quality index (fEUD), target conformity and heterogeneity indices, and the number of segments and monitor units were also performed. The most prominent feature of the biologically based plans was better sparing of organs at risk (OARs). When all plans from both institutions were combined, the biologically based plans resulted in smaller EUD values for 26 out of 33 OARs by an average of 5.6 Gy (range 0.24 to 15 Gy). Owing to more efficient beam segmentation and leaf sequencing tools implemented in the biologically based TPS compared to the dose-based TPS, an estimated treatment delivery time was shorter in most (five out of six) cases with some plans showing up to 50% reduction. The biologically based plans were generally characterized by a smaller conformity index, but greater heterogeneity index compared to the dose-based plans. Overall, compared to plans based on dose

  17. Unit testing, model validation, and biological simulation.

    Science.gov (United States)

    Sarma, Gopal P; Jacobs, Travis W; Watts, Mark D; Ghayoomie, S Vahid; Larson, Stephen D; Gerkin, Richard C

    2016-01-01

    The growth of the software industry has gone hand in hand with the development of tools and cultural practices for ensuring the reliability of complex pieces of software. These tools and practices are now acknowledged to be essential to the management of modern software. As computational models and methods have become increasingly common in the biological sciences, it is important to examine how these practices can accelerate biological software development and improve research quality. In this article, we give a focused case study of our experience with the practices of unit testing and test-driven development in OpenWorm, an open-science project aimed at modeling Caenorhabditis elegans. We identify and discuss the challenges of incorporating test-driven development into a heterogeneous, data-driven project, as well as the role of model validation tests, a category of tests unique to software which expresses scientific models.

  18. Parameter estimation and model selection in computational biology.

    Directory of Open Access Journals (Sweden)

    Gabriele Lillacci

    2010-03-01

    Full Text Available A central challenge in computational modeling of biological systems is the determination of the model parameters. Typically, only a fraction of the parameters (such as kinetic rate constants are experimentally measured, while the rest are often fitted. The fitting process is usually based on experimental time course measurements of observables, which are used to assign parameter values that minimize some measure of the error between these measurements and the corresponding model prediction. The measurements, which can come from immunoblotting assays, fluorescent markers, etc., tend to be very noisy and taken at a limited number of time points. In this work we present a new approach to the problem of parameter selection of biological models. We show how one can use a dynamic recursive estimator, known as extended Kalman filter, to arrive at estimates of the model parameters. The proposed method follows. First, we use a variation of the Kalman filter that is particularly well suited to biological applications to obtain a first guess for the unknown parameters. Secondly, we employ an a posteriori identifiability test to check the reliability of the estimates. Finally, we solve an optimization problem to refine the first guess in case it should not be accurate enough. The final estimates are guaranteed to be statistically consistent with the measurements. Furthermore, we show how the same tools can be used to discriminate among alternate models of the same biological process. We demonstrate these ideas by applying our methods to two examples, namely a model of the heat shock response in E. coli, and a model of a synthetic gene regulation system. The methods presented are quite general and may be applied to a wide class of biological systems where noisy measurements are used for parameter estimation or model selection.

  19. Modeling of biological intelligence for SCM system optimization.

    Science.gov (United States)

    Chen, Shengyong; Zheng, Yujun; Cattani, Carlo; Wang, Wanliang

    2012-01-01

    This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms.

  20. Modeling of Biological Intelligence for SCM System Optimization

    Directory of Open Access Journals (Sweden)

    Shengyong Chen

    2012-01-01

    Full Text Available This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms.

  1. Modeling of Biological Intelligence for SCM System Optimization

    Science.gov (United States)

    Chen, Shengyong; Zheng, Yujun; Cattani, Carlo; Wang, Wanliang

    2012-01-01

    This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms. PMID:22162724

  2. Methods and models in mathematical biology deterministic and stochastic approaches

    CERN Document Server

    Müller, Johannes

    2015-01-01

    This book developed from classes in mathematical biology taught by the authors over several years at the Technische Universität München. The main themes are modeling principles, mathematical principles for the analysis of these models, and model-based analysis of data. The key topics of modern biomathematics are covered: ecology, epidemiology, biochemistry, regulatory networks, neuronal networks, and population genetics. A variety of mathematical methods are introduced, ranging from ordinary and partial differential equations to stochastic graph theory and  branching processes. A special emphasis is placed on the interplay between stochastic and deterministic models.

  3. Modeling and analysis of modular structure in diverse biological networks.

    Science.gov (United States)

    Al-Anzi, Bader; Gerges, Sherif; Olsman, Noah; Ormerod, Christopher; Piliouras, Georgios; Ormerod, John; Zinn, Kai

    2017-06-07

    Biological networks, like most engineered networks, are not the product of a singular design but rather are the result of a long process of refinement and optimization. Many large real-world networks are comprised of well-defined and meaningful smaller modules. While engineered networks are designed and refined by humans with particular goals in mind, biological networks are created by the selective pressures of evolution. In this paper, we seek to define aspects of network architecture that are shared among different types of evolved biological networks. First, we developed a new mathematical model, the Stochastic Block Model with Path Selection (SBM-PS) that simulates biological network formation based on the selection of edges that increase clustering. SBM-PS can produce modular networks whose properties resemble those of real networks. Second, we analyzed three real networks of very different types, and showed that all three can be fit well by the SBM-PS model. Third, we showed that modular elements within the three networks correspond to meaningful biological structures. The networks chosen for analysis were a proteomic network composed of all proteins required for mitochondrial function in budding yeast, a mesoscale anatomical network composed of axonal connections among regions of the mouse brain, and the connectome of individual neurons in the nematode C. elegans. We find that the three networks have common architectural features, and each can be divided into subnetworks with characteristic topologies that control specific phenotypic outputs. Copyright © 2017 Elsevier Ltd. All rights reserved.

  4. Biological-based and physical-based optimization for biological evaluation of prostate patient's plans

    Science.gov (United States)

    Sukhikh, E.; Sheino, I.; Vertinsky, A.

    2017-09-01

    Modern modalities of radiation treatment therapy allow irradiation of the tumor to high dose values and irradiation of organs at risk (OARs) to low dose values at the same time. In this paper we study optimal radiation treatment plans made in Monaco system. The first aim of this study was to evaluate dosimetric features of Monaco treatment planning system using biological versus dose-based cost functions for the OARs and irradiation targets (namely tumors) when the full potential of built-in biological cost functions is utilized. The second aim was to develop criteria for the evaluation of radiation dosimetry plans for patients based on the macroscopic radiobiological criteria - TCP/NTCP. In the framework of the study four dosimetric plans were created utilizing the full extent of biological and physical cost functions using dose calculation-based treatment planning for IMRT Step-and-Shoot delivery of stereotactic body radiation therapy (SBRT) in prostate case (5 fractions per 7 Gy).

  5. Documentation of TRU biological transport model (BIOTRAN)

    International Nuclear Information System (INIS)

    Gallegos, A.F.; Garcia, B.J.; Sutton, C.M.

    1980-01-01

    Inclusive of Appendices, this document describes the purpose, rationale, construction, and operation of a biological transport model (BIOTRAN). This model is used to predict the flow of transuranic elements (TRU) through specified plant and animal environments using biomass as a vector. The appendices are: (A) Flows of moisture, biomass, and TRU; (B) Intermediate variables affecting flows; (C) Mnemonic equivalents (code) for variables; (D) Variable library (code); (E) BIOTRAN code (Fortran); (F) Plants simulated; (G) BIOTRAN code documentation; (H) Operating instructions for BIOTRAN code. The main text is presented with a specific format which uses a minimum of space, yet is adequate for tracking most relationships from their first appearance to their formulation in the code. Because relationships are treated individually in this manner, and rely heavily on Appendix material for understanding, it is advised that the reader familiarize himself with these materials before proceeding with the main text

  6. Documentation of TRU biological transport model (BIOTRAN)

    Energy Technology Data Exchange (ETDEWEB)

    Gallegos, A.F.; Garcia, B.J.; Sutton, C.M.

    1980-01-01

    Inclusive of Appendices, this document describes the purpose, rationale, construction, and operation of a biological transport model (BIOTRAN). This model is used to predict the flow of transuranic elements (TRU) through specified plant and animal environments using biomass as a vector. The appendices are: (A) Flows of moisture, biomass, and TRU; (B) Intermediate variables affecting flows; (C) Mnemonic equivalents (code) for variables; (D) Variable library (code); (E) BIOTRAN code (Fortran); (F) Plants simulated; (G) BIOTRAN code documentation; (H) Operating instructions for BIOTRAN code. The main text is presented with a specific format which uses a minimum of space, yet is adequate for tracking most relationships from their first appearance to their formulation in the code. Because relationships are treated individually in this manner, and rely heavily on Appendix material for understanding, it is advised that the reader familiarize himself with these materials before proceeding with the main text.

  7. ACTIVE AND PARTICIPATORY METHODS IN BIOLOGY: MODELING

    Directory of Open Access Journals (Sweden)

    Brînduşa-Antonela SBÎRCEA

    2011-01-01

    Full Text Available By using active and participatory methods it is hoped that pupils will not only come to a deeper understanding of the issues involved, but also that their motivation will be heightened. Pupil involvement in their learning is essential. Moreover, by using a variety of teaching techniques, we can help students make sense of the world in different ways, increasing the likelihood that they will develop a conceptual understanding. The teacher must be a good facilitator, monitoring and supporting group dynamics. Modeling is an instructional strategy in which the teacher demonstrates a new concept or approach to learning and pupils learn by observing. In the teaching of biology the didactic materials are fundamental tools in the teaching-learning process. Reading about scientific concepts or having a teacher explain them is not enough. Research has shown that modeling can be used across disciplines and in all grade and ability level classrooms. Using this type of instruction, teachers encourage learning.

  8. Artificial neural network modelling of biological oxygen demand in rivers at the national level with input selection based on Monte Carlo simulations.

    Science.gov (United States)

    Šiljić, Aleksandra; Antanasijević, Davor; Perić-Grujić, Aleksandra; Ristić, Mirjana; Pocajt, Viktor

    2015-03-01

    Biological oxygen demand (BOD) is the most significant water quality parameter and indicates water pollution with respect to the present biodegradable organic matter content. European countries are therefore obliged to report annual BOD values to Eurostat; however, BOD data at the national level is only available for 28 of 35 listed European countries for the period prior to 2008, among which 46% of data is missing. This paper describes the development of an artificial neural network model for the forecasting of annual BOD values at the national level, using widely available sustainability and economical/industrial parameters as inputs. The initial general regression neural network (GRNN) model was trained, validated and tested utilizing 20 inputs. The number of inputs was reduced to 15 using the Monte Carlo simulation technique as the input selection method. The best results were achieved with the GRNN model utilizing 25% less inputs than the initial model and a comparison with a multiple linear regression model trained and tested using the same input variables using multiple statistical performance indicators confirmed the advantage of the GRNN model. Sensitivity analysis has shown that inputs with the greatest effect on the GRNN model were (in descending order) precipitation, rural population with access to improved water sources, treatment capacity of wastewater treatment plants (urban) and treatment of municipal waste, with the last two having an equal effect. Finally, it was concluded that the developed GRNN model can be useful as a tool to support the decision-making process on sustainable development at a regional, national and international level.

  9. Modeling drug- and chemical- induced hepatotoxicity with systems biology approaches

    Directory of Open Access Journals (Sweden)

    Sudin eBhattacharya

    2012-12-01

    Full Text Available We provide an overview of computational systems biology approaches as applied to the study of chemical- and drug-induced toxicity. The concept of ‘toxicity pathways’ is described in the context of the 2007 US National Academies of Science report, Toxicity testing in the 21st Century: A Vision and A Strategy. Pathway mapping and modeling based on network biology concepts are a key component of the vision laid out in this report for a more biologically-based analysis of dose-response behavior and the safety of chemicals and drugs. We focus on toxicity of the liver (hepatotoxicity – a complex phenotypic response with contributions from a number of different cell types and biological processes. We describe three case studies of complementary multi-scale computational modeling approaches to understand perturbation of toxicity pathways in the human liver as a result of exposure to environmental contaminants and specific drugs. One approach involves development of a spatial, multicellular virtual tissue model of the liver lobule that combines molecular circuits in individual hepatocytes with cell-cell interactions and blood-mediated transport of toxicants through hepatic sinusoids, to enable quantitative, mechanistic prediction of hepatic dose-response for activation of the AhR toxicity pathway. Simultaneously, methods are being developing to extract quantitative maps of intracellular signaling and transcriptional regulatory networks perturbed by environmental contaminants, using a combination of gene expression and genome-wide protein-DNA interaction data. A predictive physiological model (DILIsymTM to understand drug-induced liver injury (DILI, the most common adverse event leading to termination of clinical development programs and regulatory actions on drugs, is also described. The model initially focuses on reactive metabolite-induced DILI in response to administration of acetaminophen, and spans multiple biological scales.

  10. Models to study gravitational biology of Mammalian reproduction

    Science.gov (United States)

    Tou, Janet; Ronca, April; Grindeland, Richard; Wade, Charles

    2002-01-01

    Mammalian reproduction evolved within Earth's 1-g gravitational field. As we move closer to the reality of space habitation, there is growing scientific interest in how different gravitational states influence reproduction in mammals. Habitation of space and extended spaceflight missions require prolonged exposure to decreased gravity (hypogravity, i.e., weightlessness). Lift-off and re-entry of the spacecraft are associated with exposure to increased gravity (hypergravity). Existing data suggest that spaceflight is associated with a constellation of changes in reproductive physiology and function. However, limited spaceflight opportunities and confounding effects of various nongravitational factors associated with spaceflight (i.e., radiation, stress) have led to the development of ground-based models for studying the effects of altered gravity on biological systems. Human bed rest and rodent hindlimb unloading paradigms are used to study exposure to hypogravity. Centrifugation is used to study hypergravity. Here, we review the results of spaceflight and ground-based models of altered gravity on reproductive physiology. Studies utilizing ground-based models that simulate hyper- and hypogravity have produced reproductive results similar to those obtained from spaceflight and are contributing new information on biological responses across the gravity continuum, thereby confirming the appropriateness of these models for studying reproductive responses to altered gravity and the underlying mechanisms of these responses. Together, these unique tools are yielding new insights into the gravitational biology of reproduction in mammals.

  11. Programming biological models in Python using PySB.

    Science.gov (United States)

    Lopez, Carlos F; Muhlich, Jeremy L; Bachman, John A; Sorger, Peter K

    2013-01-01

    Mathematical equations are fundamental to modeling biological networks, but as networks get large and revisions frequent, it becomes difficult to manage equations directly or to combine previously developed models. Multiple simultaneous efforts to create graphical standards, rule-based languages, and integrated software workbenches aim to simplify biological modeling but none fully meets the need for transparent, extensible, and reusable models. In this paper we describe PySB, an approach in which models are not only created using programs, they are programs. PySB draws on programmatic modeling concepts from little b and ProMot, the rule-based languages BioNetGen and Kappa and the growing library of Python numerical tools. Central to PySB is a library of macros encoding familiar biochemical actions such as binding, catalysis, and polymerization, making it possible to use a high-level, action-oriented vocabulary to construct detailed models. As Python programs, PySB models leverage tools and practices from the open-source software community, substantially advancing our ability to distribute and manage the work of testing biochemical hypotheses. We illustrate these ideas using new and previously published models of apoptosis.

  12. Language Based Techniques for Systems Biology

    DEFF Research Database (Denmark)

    Pilegaard, Henrik

    Process calculus is the common denominator for a class of compact, idealised, domain-specific formalisms normally associated with the study of reactive concurrent systems within Computer Science. With the rise of the interactioncentred science of Systems Biology a number of bio-inspired process......), is context insensitive, while the other, a poly-variant analysis (2CFA), is context-sensitive. These analyses compute safe approximations to the set of spatial configurations that are reachable according to a given model. This is useful in the qualitative study of cellular self-organisation and, e.......g., the effects of receptor defects or drug delivery mechanisms. The property of sequential realisability. which is closely related to the function of biochemical pathways, is addressed by a variant of traditional Data Flow Analysis (DFA). This so-called ‘Pathway Analysis’ computes safe approximations to the set...

  13. Evaluation of radiobiological effects in 3 distinct biological models

    International Nuclear Information System (INIS)

    Lemos, J.; Costa, P.; Cunha, L.; Metello, L.F.; Carvalho, A.P.; Vasconcelos, V.; Genesio, P.; Ponte, F.; Costa, P.S.; Crespo, P.

    2015-01-01

    Full text of publication follows. The present work aims at sharing the process of development of advanced biological models to study radiobiological effects. Recognizing several known limitations and difficulties of the current monolayer cellular models, as well as the increasing difficulties to use advanced biological models, our group has been developing advanced biological alternative models, namely three-dimensional cell cultures and a less explored animal model (the Zebra fish - Danio rerio - which allows the access to inter-generational data, while characterized by a great genetic homology towards the humans). These 3 models (monolayer cellular model, three-dimensional cell cultures and zebra fish) were externally irradiated with 100 mGy, 500 mGy or 1 Gy. The consequences of that irradiation were studied using cellular and molecular tests. Our previous experimental studies with 100 mGy external gamma irradiation of HepG2 monolayer cells showed a slight increase in the proliferation rate 24 h, 48 h and 72 h post irradiation. These results also pointed into the presence of certain bystander effects 72 h post irradiation, constituting the starting point for the need of a more accurate analysis realized with this work. At this stage, we continue focused on the acute biological effects. Obtained results, namely MTT and clonogenic assays for evaluating cellular metabolic activity and proliferation in the in vitro models, as well as proteomics for the evaluation of in vivo effects will be presented, discussed and explained. Several hypotheses will be presented and defended based on the facts previously demonstrated. This work aims at sharing the actual state and the results already available from this medium-term project, building the proof of the added value on applying these advanced models, while demonstrating the strongest and weakest points from all of them (so allowing the comparison between them and to base the subsequent choice for research groups starting

  14. Complex Behavior in Simple Models of Biological Coevolution

    Science.gov (United States)

    Rikvold, Per Arne

    We explore the complex dynamical behavior of simple predator-prey models of biological coevolution that account for interspecific and intraspecific competition for resources, as well as adaptive foraging behavior. In long kinetic Monte Carlo simulations of these models we find quite robust 1/f-like noise in species diversity and population sizes, as well as power-law distributions for the lifetimes of individual species and the durations of quiet periods of relative evolutionary stasis. In one model, based on the Holling Type II functional response, adaptive foraging produces a metastable low-diversity phase and a stable high-diversity phase.

  15. Modeling and simulation of biological systems using SPICE language.

    Directory of Open Access Journals (Sweden)

    Morgan Madec

    Full Text Available The article deals with BB-SPICE (SPICE for Biochemical and Biological Systems, an extension of the famous Simulation Program with Integrated Circuit Emphasis (SPICE. BB-SPICE environment is composed of three modules: a new textual and compact description formalism for biological systems, a converter that handles this description and generates the SPICE netlist of the equivalent electronic circuit and NGSPICE which is an open-source SPICE simulator. In addition, the environment provides back and forth interfaces with SBML (System Biology Markup Language, a very common description language used in systems biology. BB-SPICE has been developed in order to bridge the gap between the simulation of biological systems on the one hand and electronics circuits on the other hand. Thus, it is suitable for applications at the interface between both domains, such as development of design tools for synthetic biology and for the virtual prototyping of biosensors and lab-on-chip. Simulation results obtained with BB-SPICE and COPASI (an open-source software used for the simulation of biochemical systems have been compared on a benchmark of models commonly used in systems biology. Results are in accordance from a quantitative viewpoint but BB-SPICE outclasses COPASI by 1 to 3 orders of magnitude regarding the computation time. Moreover, as our software is based on NGSPICE, it could take profit of incoming updates such as the GPU implementation, of the coupling with powerful analysis and verification tools or of the integration in design automation tools (synthetic biology.

  16. Clinical oncology based upon radiation biology

    International Nuclear Information System (INIS)

    Hirata, Hideki

    2016-01-01

    This paper discussed the biological effects of radiation as physical energy, especially those of X-ray as electromagnetic radiation, by associating the position of clinical oncology with classical radiation cell biology as well as recent molecular biology. First, it described the physical and biological effects of radiation, cell death due to radiation and recovery, radiation effects at tissue level, and location information and dosage information in the radiotherapy of cancer. It also described the territories unresolved through radiation biology, such as low-dose high-sensitivity, bystander effects, etc. (A.O.)

  17. Mathematical biology modules based on modern molecular biology and modern discrete mathematics.

    Science.gov (United States)

    Robeva, Raina; Davies, Robin; Hodge, Terrell; Enyedi, Alexander

    2010-01-01

    We describe an ongoing collaborative curriculum materials development project between Sweet Briar College and Western Michigan University, with support from the National Science Foundation. We present a collection of modules under development that can be used in existing mathematics and biology courses, and we address a critical national need to introduce students to mathematical methods beyond the interface of biology with calculus. Based on ongoing research, and designed to use the project-based-learning approach, the modules highlight applications of modern discrete mathematics and algebraic statistics to pressing problems in molecular biology. For the majority of projects, calculus is not a required prerequisite and, due to the modest amount of mathematical background needed for some of the modules, the materials can be used for an early introduction to mathematical modeling. At the same time, most modules are connected with topics in linear and abstract algebra, algebraic geometry, and probability, and they can be used as meaningful applied introductions into the relevant advanced-level mathematics courses. Open-source software is used to facilitate the relevant computations. As a detailed example, we outline a module that focuses on Boolean models of the lac operon network.

  18. Mathematical Biology Modules Based on Modern Molecular Biology and Modern Discrete Mathematics

    Science.gov (United States)

    Davies, Robin; Hodge, Terrell; Enyedi, Alexander

    2010-01-01

    We describe an ongoing collaborative curriculum materials development project between Sweet Briar College and Western Michigan University, with support from the National Science Foundation. We present a collection of modules under development that can be used in existing mathematics and biology courses, and we address a critical national need to introduce students to mathematical methods beyond the interface of biology with calculus. Based on ongoing research, and designed to use the project-based-learning approach, the modules highlight applications of modern discrete mathematics and algebraic statistics to pressing problems in molecular biology. For the majority of projects, calculus is not a required prerequisite and, due to the modest amount of mathematical background needed for some of the modules, the materials can be used for an early introduction to mathematical modeling. At the same time, most modules are connected with topics in linear and abstract algebra, algebraic geometry, and probability, and they can be used as meaningful applied introductions into the relevant advanced-level mathematics courses. Open-source software is used to facilitate the relevant computations. As a detailed example, we outline a module that focuses on Boolean models of the lac operon network. PMID:20810955

  19. Topological Data Analysis of Biological Aggregation Models

    Science.gov (United States)

    Topaz, Chad M.; Ziegelmeier, Lori; Halverson, Tom

    2015-01-01

    We apply tools from topological data analysis to two mathematical models inspired by biological aggregations such as bird flocks, fish schools, and insect swarms. Our data consists of numerical simulation output from the models of Vicsek and D'Orsogna. These models are dynamical systems describing the movement of agents who interact via alignment, attraction, and/or repulsion. Each simulation time frame is a point cloud in position-velocity space. We analyze the topological structure of these point clouds, interpreting the persistent homology by calculating the first few Betti numbers. These Betti numbers count connected components, topological circles, and trapped volumes present in the data. To interpret our results, we introduce a visualization that displays Betti numbers over simulation time and topological persistence scale. We compare our topological results to order parameters typically used to quantify the global behavior of aggregations, such as polarization and angular momentum. The topological calculations reveal events and structure not captured by the order parameters. PMID:25970184

  20. Accelerating Bayesian inference for evolutionary biology models.

    Science.gov (United States)

    Meyer, Xavier; Chopard, Bastien; Salamin, Nicolas

    2017-03-01

    Bayesian inference is widely used nowadays and relies largely on Markov chain Monte Carlo (MCMC) methods. Evolutionary biology has greatly benefited from the developments of MCMC methods, but the design of more complex and realistic models and the ever growing availability of novel data is pushing the limits of the current use of these methods. We present a parallel Metropolis-Hastings (M-H) framework built with a novel combination of enhancements aimed towards parameter-rich and complex models. We show on a parameter-rich macroevolutionary model increases of the sampling speed up to 35 times with 32 processors when compared to a sequential M-H process. More importantly, our framework achieves up to a twentyfold faster convergence to estimate the posterior probability of phylogenetic trees using 32 processors when compared to the well-known software MrBayes for Bayesian inference of phylogenetic trees. https://bitbucket.org/XavMeyer/hogan. nicolas.salamin@unil.ch. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

  1. Ising models of strongly coupled biological networks with multivariate interactions

    Science.gov (United States)

    Merchan, Lina; Nemenman, Ilya

    2013-03-01

    Biological networks consist of a large number of variables that can be coupled by complex multivariate interactions. However, several neuroscience and cell biology experiments have reported that observed statistics of network states can be approximated surprisingly well by maximum entropy models that constrain correlations only within pairs of variables. We would like to verify if this reduction in complexity results from intricacies of biological organization, or if it is a more general attribute of these networks. We generate random networks with p-spin (p > 2) interactions, with N spins and M interaction terms. The probability distribution of the network states is then calculated and approximated with a maximum entropy model based on constraining pairwise spin correlations. Depending on the M/N ratio and the strength of the interaction terms, we observe a transition where the pairwise approximation is very good to a region where it fails. This resembles the sat-unsat transition in constraint satisfaction problems. We argue that the pairwise model works when the number of highly probable states is small. We argue that many biological systems must operate in a strongly constrained regime, and hence we expect the pairwise approximation to be accurate for a wide class of problems. This research has been partially supported by the James S McDonnell Foundation grant No.220020321.

  2. Computational Modeling of Biological Systems From Molecules to Pathways

    CERN Document Server

    2012-01-01

    Computational modeling is emerging as a powerful new approach for studying and manipulating biological systems. Many diverse methods have been developed to model, visualize, and rationally alter these systems at various length scales, from atomic resolution to the level of cellular pathways. Processes taking place at larger time and length scales, such as molecular evolution, have also greatly benefited from new breeds of computational approaches. Computational Modeling of Biological Systems: From Molecules to Pathways provides an overview of established computational methods for the modeling of biologically and medically relevant systems. It is suitable for researchers and professionals working in the fields of biophysics, computational biology, systems biology, and molecular medicine.

  3. Brillouin Spectroscopy Data Base for Biological Threats

    National Research Council Canada - National Science Library

    Rubel, Glenn

    2003-01-01

    .... Brillouin scattering from DNA, ovalbumen, the Bacillus spores globigii and thuringiensis were measured to determine the feasibility of biological material discrimination using Brillouin scattering...

  4. Analysis of Parallel Algorithms on SMP Node and Cluster of Workstations Using Parallel Programming Models with New Tile-based Method for Large Biological Datasets

    Science.gov (United States)

    Shrimankar, D. D.; Sathe, S. R.

    2016-01-01

    Sequence alignment is an important tool for describing the relationships between DNA sequences. Many sequence alignment algorithms exist, differing in efficiency, in their models of the sequences, and in the relationship between sequences. The focus of this study is to obtain an optimal alignment between two sequences of biological data, particularly DNA sequences. The algorithm is discussed with particular emphasis on time, speedup, and efficiency optimizations. Parallel programming presents a number of critical challenges to application developers. Today’s supercomputer often consists of clusters of SMP nodes. Programming paradigms such as OpenMP and MPI are used to write parallel codes for such architectures. However, the OpenMP programs cannot be scaled for more than a single SMP node. However, programs written in MPI can have more than single SMP nodes. But such a programming paradigm has an overhead of internode communication. In this work, we explore the tradeoffs between using OpenMP and MPI. We demonstrate that the communication overhead incurs significantly even in OpenMP loop execution and increases with the number of cores participating. We also demonstrate a communication model to approximate the overhead from communication in OpenMP loops. Our results are astonishing and interesting to a large variety of input data files. We have developed our own load balancing and cache optimization technique for message passing model. Our experimental results show that our own developed techniques give optimum performance of our parallel algorithm for various sizes of input parameter, such as sequence size and tile size, on a wide variety of multicore architectures. PMID:27932868

  5. Analysis of Parallel Algorithms on SMP Node and Cluster of Workstations Using Parallel Programming Models with New Tile-based Method for Large Biological Datasets.

    Science.gov (United States)

    Shrimankar, D D; Sathe, S R

    2016-01-01

    Sequence alignment is an important tool for describing the relationships between DNA sequences. Many sequence alignment algorithms exist, differing in efficiency, in their models of the sequences, and in the relationship between sequences. The focus of this study is to obtain an optimal alignment between two sequences of biological data, particularly DNA sequences. The algorithm is discussed with particular emphasis on time, speedup, and efficiency optimizations. Parallel programming presents a number of critical challenges to application developers. Today's supercomputer often consists of clusters of SMP nodes. Programming paradigms such as OpenMP and MPI are used to write parallel codes for such architectures. However, the OpenMP programs cannot be scaled for more than a single SMP node. However, programs written in MPI can have more than single SMP nodes. But such a programming paradigm has an overhead of internode communication. In this work, we explore the tradeoffs between using OpenMP and MPI. We demonstrate that the communication overhead incurs significantly even in OpenMP loop execution and increases with the number of cores participating. We also demonstrate a communication model to approximate the overhead from communication in OpenMP loops. Our results are astonishing and interesting to a large variety of input data files. We have developed our own load balancing and cache optimization technique for message passing model. Our experimental results show that our own developed techniques give optimum performance of our parallel algorithm for various sizes of input parameter, such as sequence size and tile size, on a wide variety of multicore architectures.

  6. Biological darkening of ice: measurements and models

    Science.gov (United States)

    Cook, J.; Tedstone, A.; Hodson, A. J.; Williamson, C.; McCutcheon, J.; Tranter, M.

    2017-12-01

    Biological growth occurs in the ablation zones of glaciers and ice sheets, resulting in a reduction of the ice albedo. Given the critical role of albedo in determining the surface energy balance - and therefore melt rate - of a mass of ice, understanding and quantifying biological albedo reduction is fundamental to predicting future ice dynamics. This may be particularly important on ablating ice on the western Greenland Ice Sheet, where a `dark ice zone' of varying spatial extent may be partly or mostly explained by biological growth. However, our ability to quantify and predict the contribution of biological impurities to the overall energy balance of glacial systems is currently limited by a lack of understanding of the mechanisms of biological darkening, difficulties in determining the spatial extent of biological impurities and uncertainty in isolating biological from non-biological albedo reduction. Here, new spectral measurements are presented for ice containing varying amounts of biological impurities which were obtained on the ground using a field spectrometer and from the air using a purpose built UAV on the Greenland Ice Sheet in summer 2016 and 2017. Distinctive spectral signatures are identified and used to map the spatial extent of algal blooms on the ice surface. A new radiative transfer scheme (BioSNICAR) for predicting the albedo of snow or ice discolored by microbial life is also described, offering insight into the mechanisms of biological darkening. Together, these demonstrate the critical role played by pigmented algae in darkening ice surfaces and provide a framework for predicting biological albedo reduction in future climate scenarios.

  7. INTERVAL OBSERVER FOR A BIOLOGICAL REACTOR MODEL

    Directory of Open Access Journals (Sweden)

    T. A. Kharkovskaia

    2014-05-01

    Full Text Available The method of an interval observer design for nonlinear systems with parametric uncertainties is considered. The interval observer synthesis problem for systems with varying parameters consists in the following. If there is the uncertainty restraint for the state values of the system, limiting the initial conditions of the system and the set of admissible values for the vector of unknown parameters and inputs, the interval existence condition for the estimations of the system state variables, containing the actual state at a given time, needs to be held valid over the whole considered time segment as well. Conditions of the interval observers design for the considered class of systems are shown. They are: limitation of the input and state, the existence of a majorizing function defining the uncertainty vector for the system, Lipschitz continuity or finiteness of this function, the existence of an observer gain with the suitable Lyapunov matrix. The main condition for design of such a device is cooperativity of the interval estimation error dynamics. An individual observer gain matrix selection problem is considered. In order to ensure the property of cooperativity for interval estimation error dynamics, a static transformation of coordinates is proposed. The proposed algorithm is demonstrated by computer modeling of the biological reactor. Possible applications of these interval estimation systems are the spheres of robust control, where the presence of various types of uncertainties in the system dynamics is assumed, biotechnology and environmental systems and processes, mechatronics and robotics, etc.

  8. Toward university modeling instruction--biology: adapting curricular frameworks from physics to biology.

    Science.gov (United States)

    Manthey, Seth; Brewe, Eric

    2013-06-01

    University Modeling Instruction (UMI) is an approach to curriculum and pedagogy that focuses instruction on engaging students in building, validating, and deploying scientific models. Modeling Instruction has been successfully implemented in both high school and university physics courses. Studies within the physics education research (PER) community have identified UMI's positive impacts on learning gains, equity, attitudinal shifts, and self-efficacy. While the success of this pedagogical approach has been recognized within the physics community, the use of models and modeling practices is still being developed for biology. Drawing from the existing research on UMI in physics, we describe the theoretical foundations of UMI and how UMI can be adapted to include an emphasis on models and modeling for undergraduate introductory biology courses. In particular, we discuss our ongoing work to develop a framework for the first semester of a two-semester introductory biology course sequence by identifying the essential basic models for an introductory biology course sequence.

  9. Toward University Modeling Instruction—Biology: Adapting Curricular Frameworks from Physics to Biology

    Science.gov (United States)

    Manthey, Seth; Brewe, Eric

    2013-01-01

    University Modeling Instruction (UMI) is an approach to curriculum and pedagogy that focuses instruction on engaging students in building, validating, and deploying scientific models. Modeling Instruction has been successfully implemented in both high school and university physics courses. Studies within the physics education research (PER) community have identified UMI's positive impacts on learning gains, equity, attitudinal shifts, and self-efficacy. While the success of this pedagogical approach has been recognized within the physics community, the use of models and modeling practices is still being developed for biology. Drawing from the existing research on UMI in physics, we describe the theoretical foundations of UMI and how UMI can be adapted to include an emphasis on models and modeling for undergraduate introductory biology courses. In particular, we discuss our ongoing work to develop a framework for the first semester of a two-semester introductory biology course sequence by identifying the essential basic models for an introductory biology course sequence. PMID:23737628

  10. Oscillation and stability of delay models in biology

    CERN Document Server

    Agarwal, Ravi P; Saker, Samir H

    2014-01-01

    Environmental variation plays an important role in many biological and ecological dynamical systems. This monograph focuses on the study of oscillation and the stability of delay models occurring in biology. The book presents recent research results on the qualitative behavior of mathematical models under different physical and environmental conditions, covering dynamics including the distribution and consumption of food. Researchers in the fields of mathematical modeling, mathematical biology, and population dynamics will be particularly interested in this material.

  11. Computerised modelling for developmental biology : an exploration with case studies

    NARCIS (Netherlands)

    Bertens, Laura M.F.

    2012-01-01

    Many studies in developmental biology rely on the construction and analysis of models. This research presents a broad view of modelling approaches for developmental biology, with a focus on computational methods. An overview of modelling techniques is given, followed by several case studies. Using

  12. Morphogenesis and pattern formation in biological systems experiments and models

    CERN Document Server

    Noji, Sumihare; Ueno, Naoto; Maini, Philip

    2003-01-01

    A central goal of current biology is to decode the mechanisms that underlie the processes of morphogenesis and pattern formation. Concerned with the analysis of those phenomena, this book covers a broad range of research fields, including developmental biology, molecular biology, plant morphogenesis, ecology, epidemiology, medicine, paleontology, evolutionary biology, mathematical biology, and computational biology. In Morphogenesis and Pattern Formation in Biological Systems: Experiments and Models, experimental and theoretical aspects of biology are integrated for the construction and investigation of models of complex processes. This collection of articles on the latest advances by leading researchers not only brings together work from a wide spectrum of disciplines, but also provides a stepping-stone to the creation of new areas of discovery.

  13. Modelling biological and chemically induced precipitation of calcium phosphate in enhanced biological phosphorus removal systems.

    Science.gov (United States)

    Barat, R; Montoya, T; Seco, A; Ferrer, J

    2011-06-01

    The biologically induced precipitation processes can be important in wastewater treatment, in particular treating raw wastewater with high calcium concentration combined with Enhanced Biological Phosphorus Removal. Currently, there is little information and experience in modelling jointly biological and chemical processes. This paper presents a calcium phosphate precipitation model and its inclusion in the Activated Sludge Model No 2d (ASM2d). The proposed precipitation model considers that aqueous phase reactions quickly achieve the chemical equilibrium and that aqueous-solid change is kinetically governed. The model was calibrated using data from four experiments in a Sequencing Batch Reactor (SBR) operated for EBPR and finally validated with two experiments. The precipitation model proposed was able to reproduce the dynamics of amorphous calcium phosphate (ACP) formation and later crystallization to hydroxyapatite (HAP) under different scenarios. The model successfully characterised the EBPR performance of the SBR, including the biological, physical and chemical processes. Copyright © 2011 Elsevier Ltd. All rights reserved.

  14. Model-Based Discovery of Synthetic Agonists for the Zn2+-Sensing G-Protein-Coupled Receptor 39 (GPR39) Reveals Novel Biological Functions

    DEFF Research Database (Denmark)

    Frimurer, Thomas M.; Mende, Franziska; Graae, Anne-Sofie

    2017-01-01

    The G-protein coupled receptor 39 (GPR39) is a G protein-coupled receptor activated by Zn2. We used a homol. model-based approach to identify small-mol. pharmacol. tool compds. for the receptor. The method focused on a putative binding site in GPR39 for synthetic ligands and knowledge of ligand....... of the initial library were inactive when tested alone, but lead compds. were identified using Zn2 as an allosteric enhancer. Highly selective, highly potent Zn2-independent GPR39 agonists were found in subsequent mini-libraries. These agonists identified GPR39 as a novel regulator of gastric somatostatin...

  15. OFFl Models: Novel Schema for Dynamical Modeling of Biological Systems.

    Directory of Open Access Journals (Sweden)

    C Brandon Ogbunugafor

    Full Text Available Flow diagrams are a common tool used to help build and interpret models of dynamical systems, often in biological contexts such as consumer-resource models and similar compartmental models. Typically, their usage is intuitive and informal. Here, we present a formalized version of flow diagrams as a kind of weighted directed graph which follow a strict grammar, which translate into a system of ordinary differential equations (ODEs by a single unambiguous rule, and which have an equivalent representation as a relational database. (We abbreviate this schema of "ODEs and formalized flow diagrams" as OFFL. Drawing a diagram within this strict grammar encourages a mental discipline on the part of the modeler in which all dynamical processes of a system are thought of as interactions between dynamical species that draw parcels from one or more source species and deposit them into target species according to a set of transformation rules. From these rules, the net rate of change for each species can be derived. The modeling schema can therefore be understood as both an epistemic and practical heuristic for modeling, serving both as an organizational framework for the model building process and as a mechanism for deriving ODEs. All steps of the schema beyond the initial scientific (intuitive, creative abstraction of natural observations into model variables are algorithmic and easily carried out by a computer, thus enabling the future development of a dedicated software implementation. Such tools would empower the modeler to consider significantly more complex models than practical limitations might have otherwise proscribed, since the modeling framework itself manages that complexity on the modeler's behalf. In this report, we describe the chief motivations for OFFL, carefully outline its implementation, and utilize a range of classic examples from ecology and epidemiology to showcase its features.

  16. Bionic models for identification of biological systems

    Science.gov (United States)

    Gerget, O. M.

    2017-01-01

    This article proposes a clinical decision support system that processes biomedical data. For this purpose a bionic model has been designed based on neural networks, genetic algorithms and immune systems. The developed system has been tested on data from pregnant women. The paper focuses on the approach to enable selection of control actions that can minimize the risk of adverse outcome. The control actions (hyperparameters of a new type) are further used as an additional input signal. Its values are defined by a hyperparameter optimization method. A software developed with Python is briefly described.

  17. Modeling the Biological Diversity of Pig Carcasses

    DEFF Research Database (Denmark)

    Erbou, Søren Gylling Hemmingsen

    for extracting and modeling meaningful information from the vast amount of information available from non-invasive imaging data. The lean meat percentage (LMP) is a common standard for measuring the quality of pig carcasses. Measuring the LMP using CT and using this as a reference for calibration of online...... more spatially localized modes of variation that are easier interpretable and the latter enables the use of PDM’s without the need for full point correspondence of new data. There is great potential in applying CT as non-invasive modality in the meat industry, e.g. in population based studies...

  18. Model reduction in mathematical pharmacology : Integration, reduction and linking of PBPK and systems biology models.

    Science.gov (United States)

    Snowden, Thomas J; van der Graaf, Piet H; Tindall, Marcus J

    2018-03-26

    In this paper we present a framework for the reduction and linking of physiologically based pharmacokinetic (PBPK) models with models of systems biology to describe the effects of drug administration across multiple scales. To address the issue of model complexity, we propose the reduction of each type of model separately prior to being linked. We highlight the use of balanced truncation in reducing the linear components of PBPK models, whilst proper lumping is shown to be efficient in reducing typically nonlinear systems biology type models. The overall methodology is demonstrated via two example systems; a model of bacterial chemotactic signalling in Escherichia coli and a model of extracellular regulatory kinase activation mediated via the extracellular growth factor and nerve growth factor receptor pathways. Each system is tested under the simulated administration of three hypothetical compounds; a strong base, a weak base, and an acid, mirroring the parameterisation of pindolol, midazolam, and thiopental, respectively. Our method can produce up to an 80% decrease in simulation time, allowing substantial speed-up for computationally intensive applications including parameter fitting or agent based modelling. The approach provides a straightforward means to construct simplified Quantitative Systems Pharmacology models that still provide significant insight into the mechanisms of drug action. Such a framework can potentially bridge pre-clinical and clinical modelling - providing an intermediate level of model granularity between classical, empirical approaches and mechanistic systems describing the molecular scale.

  19. Basic science through engineering? Synthetic modeling and the idea of biology-inspired engineering.

    Science.gov (United States)

    Knuuttila, Tarja; Loettgers, Andrea

    2013-06-01

    Synthetic biology is often understood in terms of the pursuit for well-characterized biological parts to create synthetic wholes. Accordingly, it has typically been conceived of as an engineering dominated and application oriented field. We argue that the relationship of synthetic biology to engineering is far more nuanced than that and involves a sophisticated epistemic dimension, as shown by the recent practice of synthetic modeling. Synthetic models are engineered genetic networks that are implanted in a natural cell environment. Their construction is typically combined with experiments on model organisms as well as mathematical modeling and simulation. What is especially interesting about this combinational modeling practice is that, apart from greater integration between these different epistemic activities, it has also led to the questioning of some central assumptions and notions on which synthetic biology is based. As a result synthetic biology is in the process of becoming more "biology inspired." Copyright © 2013 Elsevier Ltd. All rights reserved.

  20. Application of Biologically-Based Lumping To Investigate the ...

    Science.gov (United States)

    People are often exposed to complex mixtures of environmental chemicals such as gasoline, tobacco smoke, water contaminants, or food additives. However, investigators have often considered complex mixtures as one lumped entity. Valuable information can be obtained from these experiments, though this simplification provides little insight into the impact of a mixture's chemical composition on toxicologically-relevant metabolic interactions that may occur among its constituents. We developed an approach that applies chemical lumping methods to complex mixtures, in this case gasoline, based on biologically relevant parameters used in physiologically-based pharmacokinetic (PBPK) modeling. Inhalation exposures were performed with rats to evaluate performance of our PBPK model. There were 109 chemicals identified and quantified in the vapor in the chamber. The time-course kinetic profiles of 10 target chemicals were also determined from blood samples collected during and following the in vivo experiments. A general PBPK model was used to compare the experimental data to the simulated values of blood concentration for the 10 target chemicals with various numbers of lumps, iteratively increasing from 0 to 99. Large reductions in simulation error were gained by incorporating enzymatic chemical interactions, in comparison to simulating the individual chemicals separately. The error was further reduced by lumping the 99 non-target chemicals. Application of this biologic

  1. Genome-scale biological models for industrial microbial systems.

    Science.gov (United States)

    Xu, Nan; Ye, Chao; Liu, Liming

    2018-04-01

    The primary aims and challenges associated with microbial fermentation include achieving faster cell growth, higher productivity, and more robust production processes. Genome-scale biological models, predicting the formation of an interaction among genetic materials, enzymes, and metabolites, constitute a systematic and comprehensive platform to analyze and optimize the microbial growth and production of biological products. Genome-scale biological models can help optimize microbial growth-associated traits by simulating biomass formation, predicting growth rates, and identifying the requirements for cell growth. With regard to microbial product biosynthesis, genome-scale biological models can be used to design product biosynthetic pathways, accelerate production efficiency, and reduce metabolic side effects, leading to improved production performance. The present review discusses the development of microbial genome-scale biological models since their emergence and emphasizes their pertinent application in improving industrial microbial fermentation of biological products.

  2. Mathematical modeling of the evolution of a simple biological system

    Digital Repository Service at National Institute of Oceanography (India)

    Gonsalves, M.J.B.D.; Neetu, S.; Krishnan, K.P.; Attri, K.; LokaBharathi, P.A.

    Paula, Goa 403 004, India. Phone: +91 0832 2450624, Fax: +91 0832 2450606, e-mail: mjudith@nio.org Introduction In India, classroom education in biology does not generally include an exercise in which the data can be used to develop models.... This has hampered exposure to quantitative tools in biology, much to the disadvantage of students. The purpose of this note is to report an exercise we carried out to expose traditional biologists educated in India to mathematical modelling of biological...

  3. Function-Based Algorithms for Biological Sequences

    Science.gov (United States)

    Mohanty, Pragyan Sheela P.

    2015-01-01

    Two problems at two different abstraction levels of computational biology are studied. At the molecular level, efficient pattern matching algorithms in DNA sequences are presented. For gene order data, an efficient data structure is presented capable of storing all gene re-orderings in a systematic manner. A common characteristic of presented…

  4. [Conceptual bases of biological safety. Part 1].

    Science.gov (United States)

    Onishchenko, G G; Smolenskiĭ, V Iu; Ezhlova, E B; Demina, Iu V; Toporkov, V P; Toprokov, A V; Liapin, M N; Kutyrev, V V

    2013-01-01

    Up to date there is a narrow and broad interpretation of the term biological safety (BS) the world over. In the narrow sense it is defined as availability of international regulations applied to diagnostic, manufacturing, or experimental works with pathogenic biological agents (PBA) in accordance with specified levels of biological hazard and BS. In a broader context it has no national, conceptual, terminological or defying basis. Therewith, establishment of this framework has become the core issue of the study. Investigations have revealed that BS should conceptually cover the whole sphere of sanitary-and-epidemiological welfare as well as related fields such as veterinary-sanitary, phytosanitary provision, ecological safety, environmental conditions (occupational, socio-economic and geopolitical infrastructures, ecological system), and be exercised to prevent and control emergency situations (ES) of biological character. It is demonstrated that this type of ES differs from ES in the sphere of public health care of international concern which is formalized in IHR (2005), in the way that it is characterized by high socio-economic and geopolitical significance of the negative influence on human vital activities, comparable with national and international security hazard. Elaborated is the conceptual, terminological and defying toolkit of the BS broad interpretation (27 terms).

  5. Biochemical Space: A Framework for Systemic Annotation of Biological Models

    Czech Academy of Sciences Publication Activity Database

    Klement, M.; Děd, T.; Šafránek, D.; Červený, Jan; Müller, Stefan; Steuer, Ralf

    2014-01-01

    Roč. 306, JUL (2014), s. 31-44 ISSN 1571-0661 R&D Projects: GA MŠk(CZ) EE2.3.20.0256 Institutional support: RVO:67179843 Keywords : biological models * model annotation * systems biology * cyanobacteria Subject RIV: EH - Ecology, Behaviour

  6. Digital Learning Material for Model Building in Molecular Biology

    Science.gov (United States)

    Aegerter-Wilmsen, Tinri; Janssen, Fred; Hartog, Rob; Bisseling, Ton

    2005-01-01

    Building models to describe processes forms an essential part of molecular biology research. However, in molecular biology curricula little attention is generally being paid to the development of this skill. In order to provide students the opportunity to improve their model building skills, we decided to develop a number of digital cases about…

  7. Review of "Stochastic Modelling for Systems Biology" by Darren Wilkinson

    Directory of Open Access Journals (Sweden)

    Bullinger Eric

    2006-12-01

    Full Text Available Abstract "Stochastic Modelling for Systems Biology" by Darren Wilkinson introduces the peculiarities of stochastic modelling in biology. This book is particularly suited to as a textbook or for self-study, and for readers with a theoretical background.

  8. Introduction to mathematical biology modeling, analysis, and simulations

    CERN Document Server

    Chou, Ching Shan

    2016-01-01

    This book is based on a one semester course that the authors have been teaching for several years, and includes two sets of case studies. The first includes chemostat models, predator-prey interaction, competition among species, the spread of infectious diseases, and oscillations arising from bifurcations. In developing these topics, readers will also be introduced to the basic theory of ordinary differential equations, and how to work with MATLAB without having any prior programming experience. The second set of case studies were adapted from recent and current research papers to the level of the students. Topics have been selected based on public health interest. This includes the risk of atherosclerosis associated with high cholesterol levels, cancer and immune interactions, cancer therapy, and tuberculosis. Readers will experience how mathematical models and their numerical simulations can provide explanations that guide biological and biomedical research. Considered to be the undergraduate companion to t...

  9. Preservice Biology Teachers' Conceptions about the Tentative Nature of Theories and Models in Biology

    Science.gov (United States)

    Reinisch, Bianca; Krüger, Dirk

    2018-01-01

    In research on the nature of science, there is a need to investigate the role and status of different scientific knowledge forms. Theories and models are two of the most important knowledge forms within biology and are the focus of this study. During interviews, preservice biology teachers (N = 10) were asked about their understanding of theories…

  10. Experimental, statistical, and biological models of radon carcinogenesis

    International Nuclear Information System (INIS)

    Cross, F.T.

    1991-09-01

    Risk models developed for underground miners have not been consistently validated in studies of populations exposed to indoor radon. Imprecision in risk estimates results principally from differences between exposures in mines as compared to domestic environments and from uncertainties about the interaction between cigarette-smoking and exposure to radon decay products. Uncertainties in extrapolating miner data to domestic exposures can be reduced by means of a broad-based health effects research program that addresses the interrelated issues of exposure, respiratory tract dose, carcinogenesis (molecular/cellular and animal studies, plus developing biological and statistical models), and the relationship of radon to smoking and other copollutant exposures. This article reviews experimental animal data on radon carcinogenesis observed primarily in rats at Pacific Northwest Laboratory. Recent experimental and mechanistic carcinogenesis models of exposures to radon, uranium ore dust, and cigarette smoke are presented with statistical analyses of animal data. 20 refs., 1 fig

  11. Experimental, statistical and biological models of radon carcinogenesis

    International Nuclear Information System (INIS)

    Cross, F.T.

    1992-01-01

    Risk models developed for underground miners have not been consistently validated in studies of populations exposed to indoor radon. Imprecision in risk estimates results principally from differences between exposures in mines as compared with domestic environments and from uncertainties about the interaction between cigarette smoking and exposure to radon decay products. Uncertainties in extrapolating miner data to domestic exposures can be reduced by means of a broad-based health effects research programme that addresses the interrelated issues of exposure, respiratory tract dose, carcinogenesis (molecular/cellular and animal studies, plus developing biological and statistical models) and the relationship of radon to smoking and other co-pollutant exposures. This article reviews experimental animal data on radon carcinogenesis observed primarily in rats at Pacific Northwest Laboratory. Recent experimental and mechanistic carcinogenesis models of exposures to radon, uranium ore dust, and cigarette smoke are presented with statistical analyses of animal data. (author)

  12. Synthesis, biological evaluation and molecular modeling of a novel series of 7-azaindole based tri-heterocyclic compounds as potent CDK2/Cyclin E inhibitors

    Czech Academy of Sciences Publication Activity Database

    Baltus, C.B.; Jorda, Radek; Marot, Ch.; Berka, K.; Bazgier, Václav; Kryštof, Vladimír; Prie, G.; Viaud-Massuard, M.C.

    2016-01-01

    Roč. 108, JAN 27 (2016), s. 701-719 ISSN 0223-5234 R&D Projects: GA MŠk(CZ) LO1204 Institutional support: RVO:61389030 Keywords : Cyclin-dependent kinase 2 * Kinase inhibitors * Anti-tumor agent Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 4.519, year: 2016

  13. Modeling the mechanisms of biological GTP hydrolysis

    DEFF Research Database (Denmark)

    Carvalho, Alexandra T.P.; Szeler, Klaudia; Vavitsas, Konstantinos

    2015-01-01

    in which GTP hydrolysis is activated and regulated is still a controversial topic and well-designed simulations can play an important role in resolving and rationalizing the experimental data. In this review, we discuss the contributions of computational biology to our understanding of GTP hydrolysis...

  14. Sensitivity analysis approaches applied to systems biology models.

    Science.gov (United States)

    Zi, Z

    2011-11-01

    With the rising application of systems biology, sensitivity analysis methods have been widely applied to study the biological systems, including metabolic networks, signalling pathways and genetic circuits. Sensitivity analysis can provide valuable insights about how robust the biological responses are with respect to the changes of biological parameters and which model inputs are the key factors that affect the model outputs. In addition, sensitivity analysis is valuable for guiding experimental analysis, model reduction and parameter estimation. Local and global sensitivity analysis approaches are the two types of sensitivity analysis that are commonly applied in systems biology. Local sensitivity analysis is a classic method that studies the impact of small perturbations on the model outputs. On the other hand, global sensitivity analysis approaches have been applied to understand how the model outputs are affected by large variations of the model input parameters. In this review, the author introduces the basic concepts of sensitivity analysis approaches applied to systems biology models. Moreover, the author discusses the advantages and disadvantages of different sensitivity analysis methods, how to choose a proper sensitivity analysis approach, the available sensitivity analysis tools for systems biology models and the caveats in the interpretation of sensitivity analysis results.

  15. Computer Models and Automata Theory in Biology and Medicine

    CERN Document Server

    Baianu, I C

    2004-01-01

    The applications of computers to biological and biomedical problem solving goes back to the very beginnings of computer science, automata theory [1], and mathematical biology [2]. With the advent of more versatile and powerful computers, biological and biomedical applications of computers have proliferated so rapidly that it would be virtually impossible to compile a comprehensive review of all developments in this field. Limitations of computer simulations in biology have also come under close scrutiny, and claims have been made that biological systems have limited information processing power [3]. Such general conjectures do not, however, deter biologists and biomedical researchers from developing new computer applications in biology and medicine. Microprocessors are being widely employed in biological laboratories both for automatic data acquisition/processing and modeling; one particular area, which is of great biomedical interest, involves fast digital image processing and is already established for rout...

  16. Mathematical Modeling of Complex Biological Systems

    OpenAIRE

    Fischer, Hans Peter

    2008-01-01

    To understand complex biological systems such as cells, tissues, or even the human body, it is not sufficient to identify and characterize the individual molecules in the system. It also is necessary to obtain a thorough understanding of the interaction between molecules and pathways. This is even truer for understanding complex diseases such as cancer, Alzheimer’s disease, or alcoholism. With recent technological advances enabling researchers to monitor complex cellular processes on the mole...

  17. Modelling and Inference Strategies for Biological Systems

    OpenAIRE

    Palmisano, Alida

    2010-01-01

    For many years, computers have played an important role in helping scientists to store, manipulate, and analyze data coming from many different disciplines. In recent years, however, new technological capabilities and new ways of thinking about the usefulness of computer science is extending the reach of computers from simple analysis of collected data to hypothesis generation. The aim of this work is to provide a contribution in the Computational Systems Biology field. The main purpose of...

  18. A guide to numerical modelling in systems biology

    CERN Document Server

    Deuflhard, Peter

    2015-01-01

    This book is intended for students of computational systems biology with only a limited background in mathematics. Typical books on systems biology merely mention algorithmic approaches, but without offering a deeper understanding. On the other hand, mathematical books are typically unreadable for computational biologists. The authors of the present book have worked hard to fill this gap. The result is not a book on systems biology, but on computational methods in systems biology. This book originated from courses taught by the authors at Freie Universität Berlin. The guiding idea of the courses was to convey those mathematical insights that are indispensable for systems biology, teaching the necessary mathematical prerequisites by means of many illustrative examples and without any theorems. The three chapters cover the mathematical modelling of biochemical and physiological processes, numerical simulation of the dynamics of biological networks, and identification of model parameters by means of comparisons...

  19. Learning (from) the errors of a systems biology model.

    Science.gov (United States)

    Engelhardt, Benjamin; Frőhlich, Holger; Kschischo, Maik

    2016-02-11

    Mathematical modelling is a labour intensive process involving several iterations of testing on real data and manual model modifications. In biology, the domain knowledge guiding model development is in many cases itself incomplete and uncertain. A major problem in this context is that biological systems are open. Missed or unknown external influences as well as erroneous interactions in the model could thus lead to severely misleading results. Here we introduce the dynamic elastic-net, a data driven mathematical method which automatically detects such model errors in ordinary differential equation (ODE) models. We demonstrate for real and simulated data, how the dynamic elastic-net approach can be used to automatically (i) reconstruct the error signal, (ii) identify the target variables of model error, and (iii) reconstruct the true system state even for incomplete or preliminary models. Our work provides a systematic computational method facilitating modelling of open biological systems under uncertain knowledge.

  20. Systemic Modeling of Biological Functions in Consideration of Physiome Project

    Science.gov (United States)

    Minamitani, Haruyuki

    Emerging of the physiome project provides various influences on the medical, biological and pharmaceutical development. In this paper, as an example of physiome research, neural network model analysis providing the conduction mechanisms of pain and tactile sensations was presented, and the functional relations between neural activities of the network cells and stimulus intensity applied on the peripheral receptive fields were described. The modeling presented here is based on the various assumptions made by the results of physiological and anatomical studies reported in the literature. The functional activities of spinothalamic and thalamocortical cells show a good agreement with the physiological and psychophysical functions of somatosensory system that are very instructive for covering the gap between physiologically and psychophysically aspects of pain and tactile sensation.

  1. Mass balances for a biological life support system simulation model

    Science.gov (United States)

    Volk, Tyler; Rummel, John D.

    1987-01-01

    Design decisions to aid the development of future space based biological life support systems (BLSS) can be made with simulation models. The biochemistry stoichiometry was developed for: (1) protein, carbohydrate, fat, fiber, and lignin production in the edible and inedible parts of plants; (2) food consumption and production of organic solids in urine, feces, and wash water by the humans; and (3) operation of the waste processor. Flux values for all components are derived for a steady state system with wheat as the sole food source. The large scale dynamics of a materially closed (BLSS) computer model is described in a companion paper. An extension of this methodology can explore multifood systems and more complex biochemical dynamics while maintaining whole system closure as a focus.

  2. Development of a kinetic model for biological sulphate reduction ...

    African Journals Online (AJOL)

    Further, in the BSR model the end-product sulphide has a gaseous equilibrium not in the UCTADM1 model, and hence the physical gas exchange for sulphide is included. The BSR biological, chemical and physical processes are integrated with those of the UCTADM1 model, to give a complete kinetic model for competitive ...

  3. Uncertainty in biology a computational modeling approach

    CERN Document Server

    Gomez-Cabrero, David

    2016-01-01

    Computational modeling of biomedical processes is gaining more and more weight in the current research into the etiology of biomedical problems and potential treatment strategies.  Computational modeling allows to reduce, refine and replace animal experimentation as well as to translate findings obtained in these experiments to the human background. However these biomedical problems are inherently complex with a myriad of influencing factors, which strongly complicates the model building and validation process.  This book wants to address four main issues related to the building and validation of computational models of biomedical processes: Modeling establishment under uncertainty Model selection and parameter fitting Sensitivity analysis and model adaptation Model predictions under uncertainty In each of the abovementioned areas, the book discusses a number of key-techniques by means of a general theoretical description followed by one or more practical examples.  This book is intended for graduate stude...

  4. Modeling biological tissue growth: discrete to continuum representations.

    Science.gov (United States)

    Hywood, Jack D; Hackett-Jones, Emily J; Landman, Kerry A

    2013-09-01

    There is much interest in building deterministic continuum models from discrete agent-based models governed by local stochastic rules where an agent represents a biological cell. In developmental biology, cells are able to move and undergo cell division on and within growing tissues. A growing tissue is itself made up of cells which undergo cell division, thereby providing a significant transport mechanism for other cells within it. We develop a discrete agent-based model where domain agents represent tissue cells. Each agent has the ability to undergo a proliferation event whereby an additional domain agent is incorporated into the lattice. If a probability distribution describes the waiting times between proliferation events for an individual agent, then the total length of the domain is a random variable. The average behavior of these stochastically proliferating agents defining the growing lattice is determined in terms of a Fokker-Planck equation, with an advection and diffusion term. The diffusion term differs from the one obtained Landman and Binder [J. Theor. Biol. 259, 541 (2009)] when the rate of growth of the domain is specified, but the choice of agents is random. This discrepancy is reconciled by determining a discrete-time master equation for this process and an associated asymmetric nonexclusion random walk, together with consideration of synchronous and asynchronous updating schemes. All theoretical results are confirmed with numerical simulations. This study furthers our understanding of the relationship between agent-based rules, their implementation, and their associated partial differential equations. Since tissue growth is a significant cellular transport mechanism during embryonic growth, it is important to use the correct partial differential equation description when combining with other cellular functions.

  5. A Modeling Approach to Teaching Evolutionary Biology in High Schools.

    Science.gov (United States)

    Passmore, Cynthia; Stewart, Jim

    2002-01-01

    Describes the commitments and research that went into the design of a 9-week high school course in evolutionary biology designed to bring students to an understanding of the practice of evolutionary biology by engaging them in developing, elaborating, and using one of the discipline's most important explanatory models. (Contains 39 references.)…

  6. Markov Chain-Like Quantum Biological Modeling of Mutations, Aging, and Evolution

    Directory of Open Access Journals (Sweden)

    Ivan B. Djordjevic

    2015-08-01

    Full Text Available Recent evidence suggests that quantum mechanics is relevant in photosynthesis, magnetoreception, enzymatic catalytic reactions, olfactory reception, photoreception, genetics, electron-transfer in proteins, and evolution; to mention few. In our recent paper published in Life, we have derived the operator-sum representation of a biological channel based on codon basekets, and determined the quantum channel model suitable for study of the quantum biological channel capacity. However, this model is essentially memoryless and it is not able to properly model the propagation of mutation errors in time, the process of aging, and evolution of genetic information through generations. To solve for these problems, we propose novel quantum mechanical models to accurately describe the process of creation spontaneous, induced, and adaptive mutations and their propagation in time. Different biological channel models with memory, proposed in this paper, include: (i Markovian classical model, (ii Markovian-like quantum model, and (iii hybrid quantum-classical model. We then apply these models in a study of aging and evolution of quantum biological channel capacity through generations. We also discuss key differences of these models with respect to a multilevel symmetric channel-based Markovian model and a Kimura model-based Markovian process. These models are quite general and applicable to many open problems in biology, not only biological channel capacity, which is the main focus of the paper. We will show that the famous quantum Master equation approach, commonly used to describe different biological processes, is just the first-order approximation of the proposed quantum Markov chain-like model, when the observation interval tends to zero. One of the important implications of this model is that the aging phenotype becomes determined by different underlying transition probabilities in both programmed and random (damage Markov chain-like models of aging, which

  7. Spatial Modeling Tools for Cell Biology

    Science.gov (United States)

    2006-10-01

    of the cells total volume. The cytosol contains thousands of enzymes that are responsible for the catalyzation of glycolysis and gluconeogenesis ... dog , swine and pig models [Pantely, 1990, 1991; Stanley 1992]. In these studies, blood flow through the left anterior descending (LAD) coronary...perfusion. In conclusion, even thought our model falls within the (rather large) error bounds of experimental dog , pig and swine models, the

  8. Computational Modeling, Formal Analysis, and Tools for Systems Biology.

    Directory of Open Access Journals (Sweden)

    Ezio Bartocci

    2016-01-01

    Full Text Available As the amount of biological data in the public domain grows, so does the range of modeling and analysis techniques employed in systems biology. In recent years, a number of theoretical computer science developments have enabled modeling methodology to keep pace. The growing interest in systems biology in executable models and their analysis has necessitated the borrowing of terms and methods from computer science, such as formal analysis, model checking, static analysis, and runtime verification. Here, we discuss the most important and exciting computational methods and tools currently available to systems biologists. We believe that a deeper understanding of the concepts and theory highlighted in this review will produce better software practice, improved investigation of complex biological processes, and even new ideas and better feedback into computer science.

  9. Modeling dynamics of biological and chemical components of aquatic ecosystems

    International Nuclear Information System (INIS)

    Lassiter, R.R.

    1975-05-01

    To provide capability to model aquatic ecosystems or their subsystems as needed for particular research goals, a modeling strategy was developed. Submodels of several processes common to aquatic ecosystems were developed or adapted from previously existing ones. Included are submodels for photosynthesis as a function of light and depth, biological growth rates as a function of temperature, dynamic chemical equilibrium, feeding and growth, and various types of losses to biological populations. These submodels may be used as modules in the construction of models of subsystems or ecosystems. A preliminary model for the nitrogen cycle subsystem was developed using the modeling strategy and applicable submodels. (U.S.)

  10. Integrated modelling of physical, chemical and biological weather

    DEFF Research Database (Denmark)

    Kurganskiy, Alexander

    Integrated modelling of physical, chemical and biological weather has been widely considered during the recent decades. Such modelling includes interactions of atmospheric physics and chemical/biological aerosol concentrations. Emitted aerosols are subject to atmospheric transport, dispersion...... and deposition, but in turn they impact the radiation as well as cloud and precipitation formation. The present study focuses on birch pollen modelling as well as on physical and chemical weather with emphasis on black carbon (BC) aerosol modelling. The Enviro-HIRLAM model has been used for the study...

  11. Systems modelling and the development of coherent cell biological knowledge

    NARCIS (Netherlands)

    Verhoeff, R.; Waarlo, A.J.; Boersma, K.T.

    2008-01-01

    This article reports on educational design research concerning a learning and teaching strategy for cell biology in upper-secondary education introducing systems modelling as a key competence. The strategy consists of four modelling phases in which students subsequently develop models of freeliving

  12. Some Issues of Biological Shape Modelling with Applications

    DEFF Research Database (Denmark)

    Larsen, Rasmus; Hilger, Klaus Baggesen; Skoglund, Karl

    2003-01-01

    This paper illustrates current research at Informatics and Mathematical Modelling at the Technical University of Denmark within biological shape modelling. We illustrate a series of generalizations to, modifications to, and applications of the elements of constructing models of shape or appearanc...

  13. Problem-based learning through field investigation: Boosting questioning skill, biological literacy, and academic achievement

    Science.gov (United States)

    Suwono, Hadi; Wibowo, Agung

    2018-01-01

    Biology learning emphasizes problem-based learning as a learning strategy to develop students ability in identifying and solving problems in the surrounding environment. Problem identification skills are closely correlated with questioning skills. By holding this skill, students tend to deliver a procedural question instead of the descriptive one. Problem-based learning through field investigation is an instruction model which directly exposes the students to problems or phenomena that occur in the environment, and then the students design the field investigation activities to solve these problems. The purpose of this research was to describe the improvement of undergraduate biology students on questioning skills, biological literacy, and academic achievement through problem-based learning through field investigation (PBFI) compared with the lecture-based instruction (LBI). This research was a time series quasi-experimental design. The research was conducted on August - December 2015 and involved 26 undergraduate biology students at the State University of Malang on the Freshwater Ecology course. The data were collected during the learning with LBI and PBFI, in which questioning skills, biological literacy, and academic achievement were collected 3 times in each learning model. The data showed that the procedural correlative and causal types of questions are produced by the students to guide them in conducting investigations and problem-solving in PBFI. The biological literacy and academic achievement of the students at PBFI are significantly higher than those at LBI. The results show that PBFI increases the questioning skill, biological literacy, and the academic achievement of undergraduate biology students.

  14. A dynamic model for functional mapping of biological rhythms.

    Science.gov (United States)

    Fu, Guifang; Luo, Jiangtao; Berg, Arthur; Wang, Zhong; Li, Jiahan; Das, Kiranmoy; Li, Runze; Wu, Rongling

    2011-01-01

    Functional mapping is a statistical method for mapping quantitative trait loci (QTLs) that regulate the dynamic pattern of a biological trait. This method integrates mathematical aspects of biological complexity into a mixture model for genetic mapping and tests the genetic effects of QTLs by comparing genotype-specific curve parameters. As a way of quantitatively specifying the dynamic behavior of a system, differential equations have proven to be powerful for modeling and unraveling the biochemical, molecular, and cellular mechanisms of a biological process, such as biological rhythms. The equipment of functional mapping with biologically meaningful differential equations provides new insights into the genetic control of any dynamic processes. We formulate a new functional mapping framework for a dynamic biological rhythm by incorporating a group of ordinary differential equations (ODE). The Runge-Kutta fourth order algorithm was implemented to estimate the parameters that define the system of ODE. The new model will find its implications for understanding the interplay between gene interactions and developmental pathways in complex biological rhythms.

  15. Ontology- and graph-based similarity assessment in biological networks.

    Science.gov (United States)

    Wang, Haiying; Zheng, Huiru; Azuaje, Francisco

    2010-10-15

    A standard systems-based approach to biomarker and drug target discovery consists of placing putative biomarkers in the context of a network of biological interactions, followed by different 'guilt-by-association' analyses. The latter is typically done based on network structural features. Here, an alternative analysis approach in which the networks are analyzed on a 'semantic similarity' space is reported. Such information is extracted from ontology-based functional annotations. We present SimTrek, a Cytoscape plugin for ontology-based similarity assessment in biological networks. http://rosalind.infj.ulst.ac.uk/SimTrek.html francisco.azuaje@crp-sante.lu Supplementary data are available at Bioinformatics online.

  16. Chemo-mechanical model of biological membranes for actuation mechanisms

    Science.gov (United States)

    Sundaresan, Vishnu-Baba; Leo, Donald J.

    2005-05-01

    Plants have the ability to develop large mechanical force from chemical energy available with bio-fuels. The energy released by ATP hydrolysis assists the transport of ions and fluids to achieve volumetric expansion and homeostasis. Materials that develop pressure and hence strain similar to bio-materials are classified as nastic materials. Recent calculations for controlled actuation of an active material inspired by biological transport mechanism demonstrated the feasibility of developing such a material with actuation energy densities on the order of 100 kJ/m3. Our initial investigation was based on capsules that generate pressure thus causing strain in the surrounding matrix material. Our present work focuses on our efforts to fabricate a representative actuation structure and describes the chemo-mechanical constitutive equation for such a material. The actuator considered in this work is a laminated arrangement of a hydraulic actuator plate with microscopic barrels and a fluid reservoir kept separated by a semi-permeable membrane dispersed with biological transporters. We present here our initial design and a mathematical model to predict the fluid flux and strain developed in such an actuator.

  17. A literature-based similarity metric for biological processes

    Directory of Open Access Journals (Sweden)

    Chagoyen Monica

    2006-07-01

    Full Text Available Abstract Background Recent analyses in systems biology pursue the discovery of functional modules within the cell. Recognition of such modules requires the integrative analysis of genome-wide experimental data together with available functional schemes. In this line, methods to bridge the gap between the abstract definitions of cellular processes in current schemes and the interlinked nature of biological networks are required. Results This work explores the use of the scientific literature to establish potential relationships among cellular processes. To this end we haveused a document based similarity method to compute pair-wise similarities of the biological processes described in the Gene Ontology (GO. The method has been applied to the biological processes annotated for the Saccharomyces cerevisiae genome. We compared our results with similarities obtained with two ontology-based metrics, as well as with gene product annotation relationships. We show that the literature-based metric conserves most direct ontological relationships, while reveals biologically sounded similarities that are not obtained using ontology-based metrics and/or genome annotation. Conclusion The scientific literature is a valuable source of information from which to compute similarities among biological processes. The associations discovered by literature analysis are a valuable complement to those encoded in existing functional schemes, and those that arise by genome annotation. These similarities can be used to conveniently map the interlinked structure of cellular processes in a particular organism.

  18. Knowledge base and functionality of concepts of some Filipino biology teachers in five biology topics

    Science.gov (United States)

    Barquilla, Manuel B.

    2018-01-01

    This mixed research, is a snapshot of some Filipino Biology teachers' knowledge structure and how their concepts of the five topics in Biology (Photosynthesis, Cellular Respiration, human reproductive system, Mendelian genetics and NonMendelian genetics) functions and develops inside a biology classroom. The study focuses on the six biology teachers and a total of 222 students in their respective classes. Of the Six (6) teachers, three (3) are under the Science curriculum and the other three (3) are under regular curriculum in both public and private schools in Iligan city and Lanao del Norte, Philippines. The study utilized classroom discourses, concept maps, interpretative case-study method, bracketing method, and concept analysis for qualitative part; the quantitative part uses a nonparametric statistical tool, Kendall's tau Coefficient for determining relationship and congruency while measures of central tendencies and dispersion (mean, and standard deviation) for concept maps scores interpretation. Knowledge Base of Biology teachers were evaluated by experts in field of specialization having a doctorate program (e.g. PhD in Genetics) and PhD Biology candidates. The data collection entailed seven (7) months immersion: one (1) month for preliminary phase for the researcher to gain teachers' and students' confidence and the succeeding six (6) months for main observation and data collection. The evaluation of teachers' knowledge base by experts indicated that teachers' knowledge of (65%) is lower than the minimum (75%) recommended by ABD-el-Khalick and Boujaoude (1997). Thus, the experts believe that content knowledge of the teachers is hardly adequate for their teaching assignment. Moreover, the teachers in this study do not systematically use reallife situation to apply the concepts they teach. They can identify concepts too abstract for their student; however, they seldom use innovative ways to bring the discussion to their students' level of readiness and

  19. A Transformative Model for Undergraduate Quantitative Biology Education

    Science.gov (United States)

    Driscoll, Tobin A.; Dhurjati, Prasad; Pelesko, John A.; Rossi, Louis F.; Schleiniger, Gilberto; Pusecker, Kathleen; White, Harold B.

    2010-01-01

    The BIO2010 report recommended that students in the life sciences receive a more rigorous education in mathematics and physical sciences. The University of Delaware approached this problem by (1) developing a bio-calculus section of a standard calculus course, (2) embedding quantitative activities into existing biology courses, and (3) creating a new interdisciplinary major, quantitative biology, designed for students interested in solving complex biological problems using advanced mathematical approaches. To develop the bio-calculus sections, the Department of Mathematical Sciences revised its three-semester calculus sequence to include differential equations in the first semester and, rather than using examples traditionally drawn from application domains that are most relevant to engineers, drew models and examples heavily from the life sciences. The curriculum of the B.S. degree in Quantitative Biology was designed to provide students with a solid foundation in biology, chemistry, and mathematics, with an emphasis on preparation for research careers in life sciences. Students in the program take core courses from biology, chemistry, and physics, though mathematics, as the cornerstone of all quantitative sciences, is given particular prominence. Seminars and a capstone course stress how the interplay of mathematics and biology can be used to explain complex biological systems. To initiate these academic changes required the identification of barriers and the implementation of solutions. PMID:20810949

  20. A transformative model for undergraduate quantitative biology education.

    Science.gov (United States)

    Usher, David C; Driscoll, Tobin A; Dhurjati, Prasad; Pelesko, John A; Rossi, Louis F; Schleiniger, Gilberto; Pusecker, Kathleen; White, Harold B

    2010-01-01

    The BIO2010 report recommended that students in the life sciences receive a more rigorous education in mathematics and physical sciences. The University of Delaware approached this problem by (1) developing a bio-calculus section of a standard calculus course, (2) embedding quantitative activities into existing biology courses, and (3) creating a new interdisciplinary major, quantitative biology, designed for students interested in solving complex biological problems using advanced mathematical approaches. To develop the bio-calculus sections, the Department of Mathematical Sciences revised its three-semester calculus sequence to include differential equations in the first semester and, rather than using examples traditionally drawn from application domains that are most relevant to engineers, drew models and examples heavily from the life sciences. The curriculum of the B.S. degree in Quantitative Biology was designed to provide students with a solid foundation in biology, chemistry, and mathematics, with an emphasis on preparation for research careers in life sciences. Students in the program take core courses from biology, chemistry, and physics, though mathematics, as the cornerstone of all quantitative sciences, is given particular prominence. Seminars and a capstone course stress how the interplay of mathematics and biology can be used to explain complex biological systems. To initiate these academic changes required the identification of barriers and the implementation of solutions.

  1. Fuzzy Stochastic Petri Nets for Modeling Biological Systems with Uncertain Kinetic Parameters.

    Science.gov (United States)

    Liu, Fei; Heiner, Monika; Yang, Ming

    2016-01-01

    Stochastic Petri nets (SPNs) have been widely used to model randomness which is an inherent feature of biological systems. However, for many biological systems, some kinetic parameters may be uncertain due to incomplete, vague or missing kinetic data (often called fuzzy uncertainty), or naturally vary, e.g., between different individuals, experimental conditions, etc. (often called variability), which has prevented a wider application of SPNs that require accurate parameters. Considering the strength of fuzzy sets to deal with uncertain information, we apply a specific type of stochastic Petri nets, fuzzy stochastic Petri nets (FSPNs), to model and analyze biological systems with uncertain kinetic parameters. FSPNs combine SPNs and fuzzy sets, thereby taking into account both randomness and fuzziness of biological systems. For a biological system, SPNs model the randomness, while fuzzy sets model kinetic parameters with fuzzy uncertainty or variability by associating each parameter with a fuzzy number instead of a crisp real value. We introduce a simulation-based analysis method for FSPNs to explore the uncertainties of outputs resulting from the uncertainties associated with input parameters, which works equally well for bounded and unbounded models. We illustrate our approach using a yeast polarization model having an infinite state space, which shows the appropriateness of FSPNs in combination with simulation-based analysis for modeling and analyzing biological systems with uncertain information.

  2. Contemporary Phage Biology: From Classic Models to New Insights.

    Science.gov (United States)

    Ofir, Gal; Sorek, Rotem

    2018-03-08

    Bacteriophages, discovered about a century ago, have been pivotal as models for understanding the fundamental principles of molecular biology. While interest in phage biology declined after the phage "golden era," key recent developments, including advances in phage genomics, microscopy, and the discovery of the CRISPR-Cas anti-phage defense system, have sparked a renaissance in phage research in the past decade. This review highlights recently discovered unexpected complexities in phage biology, describes a new arsenal of phage genes that help them overcome bacterial defenses, and discusses advances toward documentation of the phage biodiversity on a global scale. Copyright © 2017 Elsevier Inc. All rights reserved.

  3. Modeling life the mathematics of biological systems

    CERN Document Server

    Garfinkel, Alan; Guo, Yina

    2017-01-01

    From predator-prey populations in an ecosystem, to hormone regulation within the body, the natural world abounds in dynamical systems that affect us profoundly. This book develops the mathematical tools essential for students in the life sciences to describe these interacting systems and to understand and predict their behavior. Complex feedback relations and counter-intuitive responses are common in dynamical systems in nature; this book develops the quantitative skills needed to explore these interactions. Differential equations are the natural mathematical tool for quantifying change, and are the driving force throughout this book. The use of Euler’s method makes nonlinear examples tractable and accessible to a broad spectrum of early-stage undergraduates, thus providing a practical alternative to the procedural approach of a traditional Calculus curriculum. Tools are developed within numerous, relevant examples, with an emphasis on the construction, evaluation, and interpretation of mathematical models ...

  4. Integrated modelling of physical, chemical and biological weather

    DEFF Research Database (Denmark)

    Kurganskiy, Alexander

    forecasts. The BC modelling study was performed for a modelling domain covering most of the Northern Hemisphere with focus on the EU and Arctic regions. Verification of BC concentrations against observations showed a good agreement for the EU air quality measurement sites. However, the Arctic region turned......Integrated modelling of physical, chemical and biological weather has been widely considered during the recent decades. Such modelling includes interactions of atmospheric physics and chemical/biological aerosol concentrations. Emitted aerosols are subject to atmospheric transport, dispersion...... and deposition, but in turn they impact the radiation as well as cloud and precipitation formation. The present study focuses on birch pollen modelling as well as on physical and chemical weather with emphasis on black carbon (BC) aerosol modelling. The Enviro-HIRLAM model has been used for the study...

  5. Inferring biological structures from super-resolution single molecule images using generative models.

    Directory of Open Access Journals (Sweden)

    Suvrajit Maji

    Full Text Available Localization-based super resolution imaging is presently limited by sampling requirements for dynamic measurements of biological structures. Generating an image requires serial acquisition of individual molecular positions at sufficient density to define a biological structure, increasing the acquisition time. Efficient analysis of biological structures from sparse localization data could substantially improve the dynamic imaging capabilities of these methods. Using a feature extraction technique called the Hough Transform simple biological structures are identified from both simulated and real localization data. We demonstrate that these generative models can efficiently infer biological structures in the data from far fewer localizations than are required for complete spatial sampling. Analysis at partial data densities revealed efficient recovery of clathrin vesicle size distributions and microtubule orientation angles with as little as 10% of the localization data. This approach significantly increases the temporal resolution for dynamic imaging and provides quantitatively useful biological information.

  6. Model of Biological Quantum Logic in DNA

    Directory of Open Access Journals (Sweden)

    F. Matthew Mihelic

    2013-08-01

    Full Text Available The DNA molecule has properties that allow it to act as a quantum logic processor. It has been demonstrated that there is coherent conduction of electrons longitudinally along the DNA molecule through pi stacking interactions of the aromatic nucleotide bases, and it has also been demonstrated that electrons moving longitudinally along the DNA molecule are subject to a very efficient electron spin filtering effect as the helicity of the DNA molecule interacts with the spin of the electron. This means that, in DNA, electrons are coherently conducted along a very efficient spin filter. Coherent electron spin is held in a logically and thermodynamically reversible chiral symmetry between the C2-endo and C3-endo enantiomers of the deoxyribose moiety in each nucleotide, which enables each nucleotide to function as a quantum gate. The symmetry break that provides for quantum decision in the system is determined by the spin direction of an electron that has an orbital angular momentum that is sufficient to overcome the energy barrier of the double well potential separating the C2-endo and C3-endo enantiomers, and that enantiomeric energy barrier is appropriate to the Landauer limit of the energy necessary to randomize one bit of information.

  7. Development of a General Modeling Framework for Investigating Complex Interactions among Biological and Physical Ecosystem Dynamics

    Science.gov (United States)

    Bennett, C.; Poole, G. C.; Kimball, J. S.; Stanford, J. A.; O'Daniel, S. J.; Mertes, L. A.

    2005-05-01

    Historically, physical scientists have developed models with highly accurate governing equations, while biologists have excelled at abstraction (the strategic simplification of system complexity). These different modeling paradigms yield biological (e.g. food web) and physical (e.g. hydrologic) models that can be difficult to integrate. Complex biological dynamics may be impossible to represent with governing equations. Conversely, physical processes may be oversimplified in biological models. Using agent-based modeling, a technique applied widely in social sciences and economics, we are developing a general modeling system to integrate accurate representations of physical dynamics such as water and heat flux with abstracted biological processes such as nutrient transformations. The modeling system represents an ecosystem as a complex integrated network of intelligent physical and biological "agents" that store, transform, and trade ecosystem resources (e.g., water, heat, nutrients, carbon) using equations that describe either abstracted concepts and/or physical laws. The modular design of the system allows resource submodels to be developed independently and installed into the simulation architecture. The modeling system provides a useful heuristic tool to support integrated physical and biological research topics, such as the influence of hydrologic dynamics and spatio-temporal physical heterogeneity on trophic (food web) dynamics and/or nutrient cycling.

  8. Biological information systems: Evolution as cognition-based information management.

    Science.gov (United States)

    Miller, William B

    2018-05-01

    An alternative biological synthesis is presented that conceptualizes evolutionary biology as an epiphenomenon of integrated self-referential information management. Since all biological information has inherent ambiguity, the systematic assessment of information is required by living organisms to maintain self-identity and homeostatic equipoise in confrontation with environmental challenges. Through their self-referential attachment to information space, cells are the cornerstone of biological action. That individualized assessment of information space permits self-referential, self-organizing niche construction. That deployment of information and its subsequent selection enacted the dominant stable unicellular informational architectures whose biological expressions are the prokaryotic, archaeal, and eukaryotic unicellular forms. Multicellularity represents the collective appraisal of equivocal environmental information through a shared information space. This concerted action can be viewed as systematized information management to improve information quality for the maintenance of preferred homeostatic boundaries among the varied participants. When reiterated in successive scales, this same collaborative exchange of information yields macroscopic organisms as obligatory multicellular holobionts. Cognition-Based Evolution (CBE) upholds that assessment of information precedes biological action, and the deployment of information through integrative self-referential niche construction and natural cellular engineering antecedes selection. Therefore, evolutionary biology can be framed as a complex reciprocating interactome that consists of the assessment, communication, deployment and management of information by self-referential organisms at multiple scales in continuous confrontation with environmental stresses. Copyright © 2017 Elsevier Ltd. All rights reserved.

  9. Systematically biological prioritizing remediation sites based on datasets of biological investigations and heavy metals in soil

    Science.gov (United States)

    Lin, Wei-Chih; Lin, Yu-Pin; Anthony, Johnathen

    2015-04-01

    Heavy metal pollution has adverse effects on not only the focal invertebrate species of this study, such as reduction in pupa weight and increased larval mortality, but also on the higher trophic level organisms which feed on them, either directly or indirectly, through the process of biomagnification. Despite this, few studies regarding remediation prioritization take species distribution or biological conservation priorities into consideration. This study develops a novel approach for delineating sites which are both contaminated by any of 5 readily bioaccumulated heavy metal soil contaminants and are of high ecological importance for the highly mobile, low trophic level focal species. The conservation priority of each site was based on the projected distributions of 6 moth species simulated via the presence-only maximum entropy species distribution model followed by the subsequent application of a systematic conservation tool. In order to increase the number of available samples, we also integrated crowd-sourced data with professionally-collected data via a novel optimization procedure based on a simulated annealing algorithm. This integration procedure was important since while crowd-sourced data can drastically increase the number of data samples available to ecologists, still the quality or reliability of crowd-sourced data can be called into question, adding yet another source of uncertainty in projecting species distributions. The optimization method screens crowd-sourced data in terms of the environmental variables which correspond to professionally-collected data. The sample distribution data was derived from two different sources, including the EnjoyMoths project in Taiwan (crowd-sourced data) and the Global Biodiversity Information Facility (GBIF) ?eld data (professional data). The distributions of heavy metal concentrations were generated via 1000 iterations of a geostatistical co-simulation approach. The uncertainties in distributions of the heavy

  10. A distributed approach for parameters estimation in System Biology models

    International Nuclear Information System (INIS)

    Mosca, E.; Merelli, I.; Alfieri, R.; Milanesi, L.

    2009-01-01

    Due to the lack of experimental measurements, biological variability and experimental errors, the value of many parameters of the systems biology mathematical models is yet unknown or uncertain. A possible computational solution is the parameter estimation, that is the identification of the parameter values that determine the best model fitting respect to experimental data. We have developed an environment to distribute each run of the parameter estimation algorithm on a different computational resource. The key feature of the implementation is a relational database that allows the user to swap the candidate solutions among the working nodes during the computations. The comparison of the distributed implementation with the parallel one showed that the presented approach enables a faster and better parameter estimation of systems biology models.

  11. Development of a coupled physical-biological ecosystem model ECOSMO - Part I: Model description and validation for the North Sea

    DEFF Research Database (Denmark)

    Schrum, Corinna; Alekseeva, I.; St. John, Michael

    2006-01-01

    A 3-D coupled biophysical model ECOSMO (ECOSystem MOdel) has been developed. The biological module of ECOSMO is based on lower trophic level interactions between two phyto- and two zooplankton components. The dynamics of the different phytoplankton components are governed by the availability...... of the macronutrients nitrogen, phosphate and silicate as well as light. Zooplankton production is simulated based on the consumption of the different phytoplankton groups and detritus. The biological module is coupled to a nonlinear 3-D baroclinic model. The physical and biological modules are driven by surface...... showed that the model, based on consideration of limiting processes, is able to reproduce the observed spatial and seasonal variability of the North Sea ecosystem e.g. the spring bloom, summer sub-surface production and the fall bloom. Distinct differences in regional characteristics of diatoms...

  12. A biological model of tamponade gases following pneumatic retinopexy.

    Science.gov (United States)

    Hutter, Joseph; Luu, Hoan; Schroeder, LeRoy

    2002-10-01

    Predict the persistence and expansion of intra-ocular tamponade gases used in retinal detachment surgery. Quantify factors that contribute to elevations in the intraocular pressure. We developed a non-equilibrium physiological model of intraocular gas transfer in vitreoretinal surgery. The model was calibrated using published volumetric decay measurements for four perfluorocarbon gases (CF(4), C(2)F(6), C(3)F(8), C( 4)F(10)) injected into the New Zealand red rabbit. We validated the model by comparing predicted and experimental results at different conditions in the rabbit. Using the rabbit results, the model was scaled up to humans. Predictions of gas expansion, half-life, and intraocular pressure in humans were found to correlate very well with clinical results. Gas transfer in the eye was controlled by diffusion through plasma and membranes. Although intraocular pressure depended on several complicating factors such as the physiological condition of the eye as well as the medications being used, prediction of conditions that favor elevations in intraocular pressure were identified based on the transport and thermodynamic properties of the gases. The biological model accurately predicted the dynamics of intraocular gases in the human eye. The major factor affecting the intraocular pressure was the aqueous humor dynamics, which is highly dependent on the physiological conditions in the eye. However, for long duration gases such as perfluoropropane, elevations in intraocular pressure are possible following an increase in volume and/or purity of the injected gas. By injecting a mixture of air with an expansive gas, it is possible to reduce elevations in intraocular pressure in patients with the trade off of a reduced longevity of the gas bubble. For gases that diffuse faster than perfluoropropane, there are minimal effects on intraocular pressure due to these changes.

  13. Preservice Biology Teachers' Conceptions About the Tentative Nature of Theories and Models in Biology

    Science.gov (United States)

    Reinisch, Bianca; Krüger, Dirk

    2018-02-01

    In research on the nature of science, there is a need to investigate the role and status of different scientific knowledge forms. Theories and models are two of the most important knowledge forms within biology and are the focus of this study. During interviews, preservice biology teachers ( N = 10) were asked about their understanding of theories and models. They were requested to give reasons why they see theories and models as either tentative or certain constructs. Their conceptions were then compared to philosophers' positions (e.g., Popper, Giere). A category system was developed from the qualitative content analysis of the interviews. These categories include 16 conceptions for theories ( n tentative = 11; n certai n = 5) and 18 conceptions for models ( n tentative = 10; n certain = 8). The analysis of the interviews showed that the preservice teachers gave reasons for the tentativeness or certainty of theories and models either due to their understanding of the terms or due to their understanding of the generation or evaluation of theories and models. Therefore, a variety of different terminology, from different sources, should be used in learning-teaching situations. Additionally, an understanding of which processes lead to the generation, evaluation, and refinement or rejection of theories and models should be discussed with preservice teachers. Within philosophy of science, there has been a shift from theories to models. This should be transferred to educational contexts by firstly highlighting the role of models and also their connections to theories.

  14. Modeling Biology Spanning Different Scales: An Open Challenge

    Directory of Open Access Journals (Sweden)

    Filippo Castiglione

    2014-01-01

    Full Text Available It is coming nowadays more clear that in order to obtain a unified description of the different mechanisms governing the behavior and causality relations among the various parts of a living system, the development of comprehensive computational and mathematical models at different space and time scales is required. This is one of the most formidable challenges of modern biology characterized by the availability of huge amount of high throughput measurements. In this paper we draw attention to the importance of multiscale modeling in the framework of studies of biological systems in general and of the immune system in particular.

  15. BayesMD: flexible biological modeling for motif discovery

    DEFF Research Database (Denmark)

    Tang, Man-Hung Eric; Krogh, Anders; Winther, Ole

    2008-01-01

    We present BayesMD, a Bayesian Motif Discovery model with several new features. Three different types of biological a priori knowledge are built into the framework in a modular fashion. A mixture of Dirichlets is used as prior over nucleotide probabilities in binding sites. It is trained on trans......We present BayesMD, a Bayesian Motif Discovery model with several new features. Three different types of biological a priori knowledge are built into the framework in a modular fashion. A mixture of Dirichlets is used as prior over nucleotide probabilities in binding sites. It is trained...

  16. A model for Monte Carlo simulation of low angle photon scattering in biological tissues

    CERN Document Server

    Tartari, A; Bonifazzi, C

    2001-01-01

    In order to include the molecular interference effect, a simple procedure is proposed and demonstrated to be able to update the usual cross section database for photon coherent scattering modelling in Monte Carlo codes. This effect was evaluated by measurement of coherent scattering distributions and by means of a model based on four basic materials composing biological tissues.

  17. Bio-logic builder: a non-technical tool for building dynamical, qualitative models.

    Science.gov (United States)

    Helikar, Tomáš; Kowal, Bryan; Madrahimov, Alex; Shrestha, Manish; Pedersen, Jay; Limbu, Kahani; Thapa, Ishwor; Rowley, Thaine; Satalkar, Rahul; Kochi, Naomi; Konvalina, John; Rogers, Jim A

    2012-01-01

    Computational modeling of biological processes is a promising tool in biomedical research. While a large part of its potential lies in the ability to integrate it with laboratory research, modeling currently generally requires a high degree of training in mathematics and/or computer science. To help address this issue, we have developed a web-based tool, Bio-Logic Builder, that enables laboratory scientists to define mathematical representations (based on a discrete formalism) of biological regulatory mechanisms in a modular and non-technical fashion. As part of the user interface, generalized "bio-logic" modules have been defined to provide users with the building blocks for many biological processes. To build/modify computational models, experimentalists provide purely qualitative information about a particular regulatory mechanisms as is generally found in the laboratory. The Bio-Logic Builder subsequently converts the provided information into a mathematical representation described with Boolean expressions/rules. We used this tool to build a number of dynamical models, including a 130-protein large-scale model of signal transduction with over 800 interactions, influenza A replication cycle with 127 species and 200+ interactions, and mammalian and budding yeast cell cycles. We also show that any and all qualitative regulatory mechanisms can be built using this tool.

  18. Web Based VRML Modelling

    NARCIS (Netherlands)

    Kiss, S.; Sarfraz, M.

    2004-01-01

    Presents a method to connect VRML (Virtual Reality Modeling Language) and Java components in a Web page using EAI (External Authoring Interface), which makes it possible to interactively generate and edit VRML meshes. The meshes used are based on regular grids, to provide an interaction and modeling

  19. Web Based VRML Modelling

    NARCIS (Netherlands)

    Kiss, S.; Banissi, E.; Khosrowshahi, F.; Sarfraz, M.; Ursyn, A.

    2001-01-01

    Presents a method to connect VRML (Virtual Reality Modeling Language) and Java components in a Web page using EAI (External Authoring Interface), which makes it possible to interactively generate and edit VRML meshes. The meshes used are based on regular grids, to provide an interaction and modeling

  20. Biology learning evaluation model in Senior High Schools

    Directory of Open Access Journals (Sweden)

    Sri Utari

    2017-06-01

    Full Text Available The study was to develop a Biology learning evaluation model in senior high schools that referred to the research and development model by Borg & Gall and the logic model. The evaluation model included the components of input, activities, output and outcomes. The developing procedures involved a preliminary study in the form of observation and theoretical review regarding the Biology learning evaluation in senior high schools. The product development was carried out by designing an evaluation model, designing an instrument, performing instrument experiment and performing implementation. The instrument experiment involved teachers and Students from Grade XII in senior high schools located in the City of Yogyakarta. For the data gathering technique and instrument, the researchers implemented observation sheet, questionnaire and test. The questionnaire was applied in order to attain information regarding teacher performance, learning performance, classroom atmosphere and scientific attitude; on the other hand, test was applied in order to attain information regarding Biology concept mastery. Then, for the analysis of instrument construct, the researchers performed confirmatory factor analysis by means of Lisrel 0.80 software and the results of this analysis showed that the evaluation instrument valid and reliable. The construct validity was between 0.43-0.79 while the reliability of measurement model was between 0.88-0.94. Last but not the least, the model feasibility test showed that the theoretical model had been supported by the empirical data.

  1. Modelling of environmental impacts from biological treatment of organic municipal waste in EASEWASTE

    DEFF Research Database (Denmark)

    Boldrin, Alessio; Neidel, Trine Lund; Damgaard, Anders

    2011-01-01

    The waste-LCA model EASEWASTE quantifies potential environmental effects from biological treatment of organic waste, based on mass and energy flows, emissions to air, water, soil and groundwater as well as effects from upstream and downstream processes. Default technologies for composting, anaero...... the environmental performance of alternative biological treatment technologies in relation to their mass flows, energy consumption, gaseous emissions, biogas recovery and compost/digestate utilization....

  2. Boolean Models of Biological Processes Explain Cascade-Like Behavior

    Science.gov (United States)

    Chen, Hao; Wang, Guanyu; Simha, Rahul; Du, Chenghang; Zeng, Chen

    2016-01-01

    Biological networks play a key role in determining biological function and therefore, an understanding of their structure and dynamics is of central interest in systems biology. In Boolean models of such networks, the status of each molecule is either “on” or “off” and along with the molecules interact with each other, their individual status changes from “on” to “off” or vice-versa and the system of molecules in the network collectively go through a sequence of changes in state. This sequence of changes is termed a biological process. In this paper, we examine the common perception that events in biomolecular networks occur sequentially, in a cascade-like manner, and ask whether this is likely to be an inherent property. In further investigations of the budding and fission yeast cell-cycle, we identify two generic dynamical rules. A Boolean system that complies with these rules will automatically have a certain robustness. By considering the biological requirements in robustness and designability, we show that those Boolean dynamical systems, compared to an arbitrary dynamical system, statistically present the characteristics of cascadeness and sequentiality, as observed in the budding and fission yeast cell- cycle. These results suggest that cascade-like behavior might be an intrinsic property of biological processes. PMID:26821940

  3. Natural crayfish clone as emerging model for various biological ...

    Indian Academy of Sciences (India)

    Home; Journals; Journal of Biosciences; Volume 36; Issue 2. Marmorkrebs: Natural crayfish clone as emerging model for various biological disciplines. Günter Vogt. Mini-review Volume 36 Issue 2 June 2011 pp 377-382. Fulltext. Click here to view fulltext PDF. Permanent link:

  4. Continuous time boolean modeling for biological signaling: application of Gillespie algorithm

    Directory of Open Access Journals (Sweden)

    Stoll Gautier

    2012-08-01

    Full Text Available Abstract Mathematical modeling is used as a Systems Biology tool to answer biological questions, and more precisely, to validate a network that describes biological observations and predict the effect of perturbations. This article presents an algorithm for modeling biological networks in a discrete framework with continuous time. Background There exist two major types of mathematical modeling approaches: (1 quantitative modeling, representing various chemical species concentrations by real numbers, mainly based on differential equations and chemical kinetics formalism; (2 and qualitative modeling, representing chemical species concentrations or activities by a finite set of discrete values. Both approaches answer particular (and often different biological questions. Qualitative modeling approach permits a simple and less detailed description of the biological systems, efficiently describes stable state identification but remains inconvenient in describing the transient kinetics leading to these states. In this context, time is represented by discrete steps. Quantitative modeling, on the other hand, can describe more accurately the dynamical behavior of biological processes as it follows the evolution of concentration or activities of chemical species as a function of time, but requires an important amount of information on the parameters difficult to find in the literature. Results Here, we propose a modeling framework based on a qualitative approach that is intrinsically continuous in time. The algorithm presented in this article fills the gap between qualitative and quantitative modeling. It is based on continuous time Markov process applied on a Boolean state space. In order to describe the temporal evolution of the biological process we wish to model, we explicitly specify the transition rates for each node. For that purpose, we built a language that can be seen as a generalization of Boolean equations. Mathematically, this approach can be

  5. Biological Impact of Music and Software-Based Auditory Training

    Science.gov (United States)

    Kraus, Nina

    2012-01-01

    Auditory-based communication skills are developed at a young age and are maintained throughout our lives. However, some individuals--both young and old--encounter difficulties in achieving or maintaining communication proficiency. Biological signals arising from hearing sounds relate to real-life communication skills such as listening to speech in…

  6. A Project-Based Biologically-Inspired Robotics Module

    Science.gov (United States)

    Crowder, R. M.; Zauner, K.-P.

    2013-01-01

    The design of any robotic system requires input from engineers from a variety of technical fields. This paper describes a project-based module, "Biologically-Inspired Robotics," that is offered to Electronics and Computer Science students at the University of Southampton, U.K. The overall objective of the module is for student groups to…

  7. Systems Biology in Immunology – A Computational Modeling Perspective

    Science.gov (United States)

    Germain, Ronald N.; Meier-Schellersheim, Martin; Nita-Lazar, Aleksandra; Fraser, Iain D. C.

    2011-01-01

    Systems biology is an emerging discipline that combines high-content, multiplexed measurements with informatic and computational modeling methods to better understand biological function at various scales. Here we present a detailed review of the methods used to create computational models and conduct simulations of immune function, We provide descriptions of the key data gathering techniques employed to generate the quantitative and qualitative data required for such modeling and simulation and summarize the progress to date in applying these tools and techniques to questions of immunological interest, including infectious disease. We include comments on what insights modeling can provide that complement information obtained from the more familiar experimental discovery methods used by most investigators and why quantitative methods are needed to eventually produce a better understanding of immune system operation in health and disease. PMID:21219182

  8. Bacteriophage-based synthetic biology for the study of infectious diseases

    Science.gov (United States)

    Lu, Timothy K.

    2014-01-01

    Since their discovery, bacteriophages have contributed enormously to our understanding of molecular biology as model systems. Furthermore, bacteriophages have provided many tools that have advanced the fields of genetic engineering and synthetic biology. Here, we discuss bacteriophage-based technologies and their application to the study of infectious diseases. New strategies for engineering genomes have the potential to accelerate the design of novel phages as therapies, diagnostics, and tools. Though almost a century has elapsed since their discovery, bacteriophages continue to have a major impact on modern biological sciences, especially with the growth of multidrug-resistant bacteria and interest in the microbiome. PMID:24997401

  9. Probabilistic Model Checking of Biological Systems with Uncertain Kinetic Rates

    Science.gov (United States)

    Barbuti, Roberto; Levi, Francesca; Milazzo, Paolo; Scatena, Guido

    We present an abstraction of the probabilistic semantics of Multiset Rewriting to formally express systems of reactions with uncertain kinetic rates. This allows biological systems modelling when the exact rates are not known, but are supposed to lie in some intervals. On these (abstract) models we perform probabilistic model checking obtaining lower and upper bounds for the probabilities of reaching states satisfying given properties. These bounds are under- and over-approximations, respectively, of the probabilities one would obtain by verifying the models with exact kinetic rates belonging to the intervals.

  10. Modeling and Simulation Tools: From Systems Biology to Systems Medicine.

    Science.gov (United States)

    Olivier, Brett G; Swat, Maciej J; Moné, Martijn J

    2016-01-01

    Modeling is an integral component of modern biology. In this chapter we look into the role of the model, as it pertains to Systems Medicine, and the software that is required to instantiate and run it. We do this by comparing the development, implementation, and characteristics of tools that have been developed to work with two divergent methodologies: Systems Biology and Pharmacometrics. From the Systems Biology perspective we consider the concept of "Software as a Medical Device" and what this may imply for the migration of research-oriented, simulation software into the domain of human health.In our second perspective, we see how in practice hundreds of computational tools already accompany drug discovery and development at every stage of the process. Standardized exchange formats are required to streamline the model exchange between tools, which would minimize translation errors and reduce the required time. With the emergence, almost 15 years ago, of the SBML standard, a large part of the domain of interest is already covered and models can be shared and passed from software to software without recoding them. Until recently the last stage of the process, the pharmacometric analysis used in clinical studies carried out on subject populations, lacked such an exchange medium. We describe a new emerging exchange format in Pharmacometrics which covers the non-linear mixed effects models, the standard statistical model type used in this area. By interfacing these two formats the entire domain can be covered by complementary standards and subsequently the according tools.

  11. AIEgen-Based Fluorescent Nanomaterials: Fabrication and Biological Applications

    Directory of Open Access Journals (Sweden)

    Hui Gao

    2018-02-01

    Full Text Available In recent years, luminogens with the feature of aggregation-induced emission (AIEgen have emerged as advanced luminescent materials for fluorescent nanomaterial preparation. AIEgen-based nanomaterials show enhanced fluorescence efficiency and superior photostability, which thusly offer unique advantages in biological applications. In this review, we will summarize the fabrication methods of AIEgen-based nanomaterials and their applications in in vitro/in vivo imaging, cell tracing, photodynamic therapy and drug delivery, focusing on the recent progress.

  12. Biological impact of music and software-based auditory training

    OpenAIRE

    Kraus, Nina

    2012-01-01

    Auditory-based communication skills are developed at a young age and are maintained throughout our lives. However, some individuals – both young and old – encounter difficulties in achieving or maintaining communication proficiency. Biological signals arising from hearing sounds relate to real-life communication skills such as listening to speech in noisy environments and reading, pointing to an intersection between hearing and cognition. Musical experience, amplification, and software-based ...

  13. Synthetic biology for microbial production of lipid-based biofuels.

    Science.gov (United States)

    d'Espaux, Leo; Mendez-Perez, Daniel; Li, Rachel; Keasling, Jay D

    2015-12-01

    The risks of maintaining current CO2 emission trends have led to interest in producing biofuels using engineered microbes. Microbial biofuels reduce emissions because CO2 produced by fuel combustion is offset by CO2 captured by growing biomass, which is later used as feedstock for biofuel fermentation. Hydrocarbons found in petroleum fuels share striking similarity with biological lipids. Here we review synthetic metabolic pathways based on fatty acid and isoprenoid metabolism to produce alkanes and other molecules suitable as biofuels. We further discuss engineering strategies to optimize engineered biosynthetic routes, as well as the potential of synthetic biology for sustainable manufacturing. Published by Elsevier Ltd.

  14. Construction of a Linux based chemical and biological information system.

    Science.gov (United States)

    Molnár, László; Vágó, István; Fehér, András

    2003-01-01

    A chemical and biological information system with a Web-based easy-to-use interface and corresponding databases has been developed. The constructed system incorporates all chemical, numerical and textual data related to the chemical compounds, including numerical biological screen results. Users can search the database by traditional textual/numerical and/or substructure or similarity queries through the web interface. To build our chemical database management system, we utilized existing IT components such as ORACLE or Tripos SYBYL for database management and Zope application server for the web interface. We chose Linux as the main platform, however, almost every component can be used under various operating systems.

  15. Synthesis, characterization and biological evaluation of tryptamine based benzamide derivatives.

    Science.gov (United States)

    Aftab, Kiran; Aslam, Kinza; Kousar, Shazia; Nadeem, Muhammad Jawad Ul Hasan

    2016-03-01

    Benzamides and tryptamine are biologically significant compounds, therefore, various benzamide analogous of tryptamine have been efficiently synthesized using tryptamine and different benzoyl chlorides, in order to find new biologically active compounds. The resulting products were then characterized by melting point determination, calculation of Rf values and LC-MS techniques. At last, structure activity relationship (SAR) of the synthesized compounds was evaluated against two microbial strains; Bacillus subtilis and Aspergillus niger. All the five prepared products have shown high yield, sharp characterization and significant resistance against the growth of tested microorganism, providing a new range of tryptamine based benzamide derivatives having significant antimicrobial activities.

  16. Synthetic biology for microbial production of lipid-based biofuels

    Energy Technology Data Exchange (ETDEWEB)

    d' Espaux, L; Mendez-Perez, D; Li, R; Keasling, JD

    2015-10-23

    The risks of maintaining current CO2 emission trends have led to interest in producing biofuels using engineered microbes. Microbial biofuels reduce emissions because CO2 produced by fuel combustion is offset by CO2 captured by growing biomass, which is later used as feedstock for biofuel fermentation. Hydrocarbons found in petroleum fuels share striking similarity with biological lipids. Here in this paper we review synthetic metabolic pathways based on fatty acid and isoprenoid metabolism to produce alkanes and other molecules suitable as biofuels. Lastly, we further discuss engineering strategies to optimize engineered biosynthetic routes, as well as the potential of synthetic biology for sustainable manufacturing.

  17. An Improved Swarm Optimization for Parameter Estimation and Biological Model Selection

    Science.gov (United States)

    Abdullah, Afnizanfaizal; Deris, Safaai; Mohamad, Mohd Saberi; Anwar, Sohail

    2013-01-01

    One of the key aspects of computational systems biology is the investigation on the dynamic biological processes within cells. Computational models are often required to elucidate the mechanisms and principles driving the processes because of the nonlinearity and complexity. The models usually incorporate a set of parameters that signify the physical properties of the actual biological systems. In most cases, these parameters are estimated by fitting the model outputs with the corresponding experimental data. However, this is a challenging task because the available experimental data are frequently noisy and incomplete. In this paper, a new hybrid optimization method is proposed to estimate these parameters from the noisy and incomplete experimental data. The proposed method, called Swarm-based Chemical Reaction Optimization, integrates the evolutionary searching strategy employed by the Chemical Reaction Optimization, into the neighbouring searching strategy of the Firefly Algorithm method. The effectiveness of the method was evaluated using a simulated nonlinear model and two biological models: synthetic transcriptional oscillators, and extracellular protease production models. The results showed that the accuracy and computational speed of the proposed method were better than the existing Differential Evolution, Firefly Algorithm and Chemical Reaction Optimization methods. The reliability of the estimated parameters was statistically validated, which suggests that the model outputs produced by these parameters were valid even when noisy and incomplete experimental data were used. Additionally, Akaike Information Criterion was employed to evaluate the model selection, which highlighted the capability of the proposed method in choosing a plausible model based on the experimental data. In conclusion, this paper presents the effectiveness of the proposed method for parameter estimation and model selection problems using noisy and incomplete experimental data. This

  18. An improved swarm optimization for parameter estimation and biological model selection.

    Directory of Open Access Journals (Sweden)

    Afnizanfaizal Abdullah

    Full Text Available One of the key aspects of computational systems biology is the investigation on the dynamic biological processes within cells. Computational models are often required to elucidate the mechanisms and principles driving the processes because of the nonlinearity and complexity. The models usually incorporate a set of parameters that signify the physical properties of the actual biological systems. In most cases, these parameters are estimated by fitting the model outputs with the corresponding experimental data. However, this is a challenging task because the available experimental data are frequently noisy and incomplete. In this paper, a new hybrid optimization method is proposed to estimate these parameters from the noisy and incomplete experimental data. The proposed method, called Swarm-based Chemical Reaction Optimization, integrates the evolutionary searching strategy employed by the Chemical Reaction Optimization, into the neighbouring searching strategy of the Firefly Algorithm method. The effectiveness of the method was evaluated using a simulated nonlinear model and two biological models: synthetic transcriptional oscillators, and extracellular protease production models. The results showed that the accuracy and computational speed of the proposed method were better than the existing Differential Evolution, Firefly Algorithm and Chemical Reaction Optimization methods. The reliability of the estimated parameters was statistically validated, which suggests that the model outputs produced by these parameters were valid even when noisy and incomplete experimental data were used. Additionally, Akaike Information Criterion was employed to evaluate the model selection, which highlighted the capability of the proposed method in choosing a plausible model based on the experimental data. In conclusion, this paper presents the effectiveness of the proposed method for parameter estimation and model selection problems using noisy and incomplete

  19. Inquiry-based Science Instruction in High School Biology Courses: A Multiple Case Study

    Science.gov (United States)

    Aso, Eze

    A lack of research exists about how secondary school science teachers use inquiry-based instruction to improve student learning. The purpose of this qualitative study was to explore how science teachers used inquiry-based instruction to improve student learning in high school biology courses. The conceptual framework was based on Banchi and Bell's model of increasing levels of complexity for inquiry-based instruction. A multiple case study research design was conducted of biology programs at 3 high schools in an urban school district in the northeastern region of the United States. Participants included 2 biology teachers from each of the 3 high schools. Data were collected from individual interviews with biology teachers, observations of lessons in biology, and documents related to state standards, assessments, and professional development. The first level of data analysis involved coding and categorizing the interview and observation data. A content analysis was used for the documents. The second level of data analysis involved examining data across all sources and all cases for themes and discrepancies. According to study findings, biology teachers used confirmation, structure, and guided inquiry to improve student learning. However, they found open inquiry challenging and frustrating to implement because professional development about scaffolding of instruction over time was needed, and students' reading and writing skills needed to improve. This study contributes to positive social change by providing educators and researchers with a deeper understanding about how to scaffold levels of inquiry-based science instruction in order to help students become scientifically literate citizens.

  20. A modified microdosimetric kinetic model for relative biological effectiveness calculation

    Science.gov (United States)

    Chen, Yizheng; Li, Junli; Li, Chunyan; Qiu, Rui; Wu, Zhen

    2018-01-01

    In the heavy ion therapy, not only the distribution of physical absorbed dose, but also the relative biological effectiveness (RBE) weighted dose needs to be taken into account. The microdosimetric kinetic model (MKM) can predict the RBE value of heavy ions with saturation-corrected dose-mean specific energy, which has been used in clinical treatment planning at the National Institute of Radiological Sciences. In the theoretical assumption of the MKM, the yield of the primary lesion is independent of the radiation quality, while the experimental data shows that DNA double strand break (DSB) yield, considered as the main primary lesion, depends on the LET of the particle. Besides, the β parameter of the MKM is constant with LET resulting from this assumption, which also differs from the experimental conclusion. In this study, a modified MKM was developed, named MMKM. Based on the experimental DSB yield of mammalian cells under the irradiation of ions with different LETs, a RBEDSB (RBE for the induction of DSB)-LET curve was fitted as the correction factor to modify the primary lesion yield in the MKM, and the variation of the primary lesion yield with LET is considered in the MMKM. Compared with the present the MKM, not only the α parameter of the MMKM for mono-energetic ions agree with the experimental data, but also the β parameter varies with LET and the variation trend of the experimental result can be reproduced on the whole. Then a spread-out Bragg peaks (SOBP) distribution of physical dose was simulated with Geant4 Monte Carlo code, and the biological and clinical dose distributions were calculated, under the irradiation of carbon ions. The results show that the distribution of clinical dose calculated with the MMKM is closed to the distribution with the MKM in the SOBP, while the discrepancy before and after the SOBP are both within 10%. Moreover, the MKM might overestimate the clinical dose at the distal end of the SOBP more than 5% because of its

  1. Analyzing Students' Understanding of Models and Modeling Referring to the Disciplines Biology, Chemistry, and Physics

    Science.gov (United States)

    Krell, Moritz; Reinisch, Bianca; Krüger, Dirk

    2015-01-01

    In this study, secondary school students' (N?=?617; grades 7 to 10) understanding of models and modeling was assessed using tasks which explicitly refer to the scientific disciplines of biology, chemistry, and physics and, as a control, to no scientific discipline. The students' responses are interpreted as their biology-, chemistry-, and…

  2. The potential of standards-based agriculture biology as an alternative to traditional biology in California

    Science.gov (United States)

    Sellu, George Sahr

    schools. Thoron & Meyer (2011) suggested that research into the contribution of integrated science courses toward higher test scores yielded mixed results. This finding may have been due in part to the fact that integrated science courses only incorporate select topics into agriculture education courses. In California, however, agriculture educators have developed standards-based courses such as Agriculture Biology (AgBio) that cover the same content standards as core traditional courses such as traditional biology. Students in both AgBio and traditional biology take the same standardized biology test. This is the first time there has been an opportunity for a fair comparison and a uniform metric for an agriscience course such as AgBio to be directly compared to traditional biology. This study will examine whether there are differences between AgBio and traditional biology with regard to standardized test scores in biology. Furthermore, the study examines differences in perception between teachers and students regarding teaching and learning activities associated with higher achievement in science. The findings of the study could provide a basis for presenting AgBio as a potential alternative to traditional biology. The findings of this study suggest that there are no differences between AgBio and traditional biology students with regard to standardized biology test scores. Additionally, the findings indicate that co-curricular activities in AgBio could contribute higher student achievement in biology. However, further research is required to identify specific activities in AgBio that contribute to higher achievement in science.

  3. Dynamics of mathematical models in biology bringing mathematics to life

    CERN Document Server

    Zazzu, Valeria; Guarracino, Mario

    2016-01-01

    This volume focuses on contributions from both the mathematics and life science community surrounding the concepts of time and dynamicity of nature, two significant elements which are often overlooked in modeling process to avoid exponential computations. The book is divided into three distinct parts: dynamics of genomes and genetic variation, dynamics of motifs, and dynamics of biological networks. Chapters included in dynamics of genomes and genetic variation analyze the molecular mechanisms and evolutionary processes that shape the structure and function of genomes and those that govern genome dynamics. The dynamics of motifs portion of the volume provides an overview of current methods for motif searching in DNA, RNA and proteins, a key process to discover emergent properties of cells, tissues, and organisms. The part devoted to the dynamics of biological networks covers networks aptly discusses networks in complex biological functions and activities that interpret processes in cells. Moreover, chapters i...

  4. Model Based Temporal Reasoning

    Science.gov (United States)

    Rabin, Marla J.; Spinrad, Paul R.; Fall, Thomas C.

    1988-03-01

    Systems that assess the real world must cope with evidence that is uncertain, ambiguous, and spread over time. Typically, the most important function of an assessment system is to identify when activities are occurring that are unusual or unanticipated. Model based temporal reasoning addresses both of these requirements. The differences among temporal reasoning schemes lies in the methods used to avoid computational intractability. If we had n pieces of data and we wanted to examine how they were related, the worst case would be where we had to examine every subset of these points to see if that subset satisfied the relations. This would be 2n, which is intractable. Models compress this; if several data points are all compatible with a model, then that model represents all those data points. Data points are then considered related if they lie within the same model or if they lie in models that are related. Models thus address the intractability problem. They also address the problem of determining unusual activities if the data do not agree with models that are indicated by earlier data then something out of the norm is taking place. The models can summarize what we know up to that time, so when they are not predicting correctly, either something unusual is happening or we need to revise our models. The model based reasoner developed at Advanced Decision Systems is thus both intuitive and powerful. It is currently being used on one operational system and several prototype systems. It has enough power to be used in domains spanning the spectrum from manufacturing engineering and project management to low-intensity conflict and strategic assessment.

  5. A data integration approach for cell cycle analysis oriented to model simulation in systems biology

    Directory of Open Access Journals (Sweden)

    Mosca Ettore

    2007-08-01

    Full Text Available Abstract Background The cell cycle is one of the biological processes most frequently investigated in systems biology studies and it involves the knowledge of a large number of genes and networks of protein interactions. A deep knowledge of the molecular aspect of this biological process can contribute to making cancer research more accurate and innovative. In this context the mathematical modelling of the cell cycle has a relevant role to quantify the behaviour of each component of the systems. The mathematical modelling of a biological process such as the cell cycle allows a systemic description that helps to highlight some features such as emergent properties which could be hidden when the analysis is performed only from a reductionism point of view. Moreover, in modelling complex systems, a complete annotation of all the components is equally important to understand the interaction mechanism inside the network: for this reason data integration of the model components has high relevance in systems biology studies. Description In this work, we present a resource, the Cell Cycle Database, intended to support systems biology analysis on the Cell Cycle process, based on two organisms, yeast and mammalian. The database integrates information about genes and proteins involved in the cell cycle process, stores complete models of the interaction networks and allows the mathematical simulation over time of the quantitative behaviour of each component. To accomplish this task, we developed, a web interface for browsing information related to cell cycle genes, proteins and mathematical models. In this framework, we have implemented a pipeline which allows users to deal with the mathematical part of the models, in order to solve, using different variables, the ordinary differential equation systems that describe the biological process. Conclusion This integrated system is freely available in order to support systems biology research on the cell cycle and

  6. Differential Equations Models in Biology, Epidemiology and Ecology

    CERN Document Server

    Martelli, Mario

    1991-01-01

    The past forty years have been the stage for the maturation of mathematical biolo~ as a scientific field. The foundations laid by the pioneers of the field during the first half of this century have been combined with advances in ap­ plied mathematics and the computational sciences to create a vibrant area of scientific research with established research journals, professional societies, deep subspecialty areas, and graduate education programs. Mathematical biology is by its very nature cross-disciplinary, and research papers appear in mathemat­ ics, biology and other scientific journals, as well as in the specialty journals devoted to mathematical and theoretical biology. Multiple author papers are common, and so are collaborations between individuals who have academic bases in different traditional departments. Those who seek to keep abreast of current trends and problems need to interact with research workers from a much broader spectrum of fields than is common in the traditional mono-culture discipline...

  7. An Abstraction Theory for Qualitative Models of Biological Systems

    Directory of Open Access Journals (Sweden)

    Richard Banks

    2010-10-01

    Full Text Available Multi-valued network models are an important qualitative modelling approach used widely by the biological community. In this paper we consider developing an abstraction theory for multi-valued network models that allows the state space of a model to be reduced while preserving key properties of the model. This is important as it aids the analysis and comparison of multi-valued networks and in particular, helps address the well-known problem of state space explosion associated with such analysis. We also consider developing techniques for efficiently identifying abstractions and so provide a basis for the automation of this task. We illustrate the theory and techniques developed by investigating the identification of abstractions for two published MVN models of the lysis-lysogeny switch in the bacteriophage lambda.

  8. Generalized Beer-Lambert model for near-infrared light propagation in thick biological tissues

    Science.gov (United States)

    Bhatt, Manish; Ayyalasomayajula, Kalyan R.; Yalavarthy, Phaneendra K.

    2016-07-01

    The attenuation of near-infrared (NIR) light intensity as it propagates in a turbid medium like biological tissue is described by modified the Beer-Lambert law (MBLL). The MBLL is generally used to quantify the changes in tissue chromophore concentrations for NIR spectroscopic data analysis. Even though MBLL is effective in terms of providing qualitative comparison, it suffers from its applicability across tissue types and tissue dimensions. In this work, we introduce Lambert-W function-based modeling for light propagation in biological tissues, which is a generalized version of the Beer-Lambert model. The proposed modeling provides parametrization of tissue properties, which includes two attenuation coefficients μ0 and η. We validated our model against the Monte Carlo simulation, which is the gold standard for modeling NIR light propagation in biological tissue. We included numerous human and animal tissues to validate the proposed empirical model, including an inhomogeneous adult human head model. The proposed model, which has a closed form (analytical), is first of its kind in providing accurate modeling of NIR light propagation in biological tissues.

  9. Extended Problem-Based Learning Improves Scientific Communication in Senior Biology Students

    Science.gov (United States)

    Kolber, Benedict J.

    2011-01-01

    This article describes a model of extended problem-based learning that instructed upper-level undergraduate students to focus on a single biological problem while improving their critical thinking, presentation, and scientific-writing skills. This course was developed in response to students' requests for formal training in oral presentation…

  10. Bifurcations of a class of singular biological economic models

    International Nuclear Information System (INIS)

    Zhang Xue; Zhang Qingling; Zhang Yue

    2009-01-01

    This paper studies systematically a prey-predator singular biological economic model with time delay. It shows that this model exhibits two bifurcation phenomena when the economic profit is zero. One is transcritical bifurcation which changes the stability of the system, and the other is singular induced bifurcation which indicates that zero economic profit brings impulse, i.e., rapid expansion of the population in biological explanation. On the other hand, if the economic profit is positive, at a critical value of bifurcation parameter, the system undergoes a Hopf bifurcation, i.e., the increase of delay destabilizes the system and bifurcates into small amplitude periodic solution. Finally, by using Matlab software, numerical simulations illustrate the effectiveness of the results obtained here. In addition, we study numerically that the system undergoes a saddle-node bifurcation when the bifurcation parameter goes through critical value of positive economic profit.

  11. Enterococcus infection biology: lessons from invertebrate host models.

    Science.gov (United States)

    Yuen, Grace J; Ausubel, Frederick M

    2014-03-01

    The enterococci are commensals of the gastrointestinal tract of many metazoans, from insects to humans. While they normally do not cause disease in the intestine, they can become pathogenic when they infect sites outside of the gut. Recently, the enterococci have become important nosocomial pathogens, with the majority of human enterococcal infections caused by two species, Enterococcus faecalis and Enterococcus faecium. Studies using invertebrate infection models have revealed insights into the biology of enterococcal infections, as well as general principles underlying host innate immune defense. This review highlights recent findings on Enterococcus infection biology from two invertebrate infection models, the greater wax moth Galleria mellonella and the free-living bacteriovorous nematode Caenorhabditis elegans.

  12. Competency-based reforms of the undergraduate biology curriculum: integrating the physical and biological sciences.

    Science.gov (United States)

    Thompson, Katerina V; Chmielewski, Jean; Gaines, Michael S; Hrycyna, Christine A; LaCourse, William R

    2013-06-01

    The National Experiment in Undergraduate Science Education project funded by the Howard Hughes Medical Institute is a direct response to the Scientific Foundations for Future Physicians report, which urged a shift in premedical student preparation from a narrow list of specific course work to a more flexible curriculum that helps students develop broad scientific competencies. A consortium of four universities is working to create, pilot, and assess modular, competency-based curricular units that require students to use higher-order cognitive skills and reason across traditional disciplinary boundaries. Purdue University; the University of Maryland, Baltimore County; and the University of Miami are each developing modules and case studies that integrate the biological, chemical, physical, and mathematical sciences. The University of Maryland, College Park, is leading the effort to create an introductory physics for life sciences course that is reformed in both content and pedagogy. This course has prerequisites of biology, chemistry, and calculus, allowing students to apply strategies from the physical sciences to solving authentic biological problems. A comprehensive assessment plan is examining students' conceptual knowledge of physics, their attitudes toward interdisciplinary approaches, and the development of specific scientific competencies. Teaching modules developed during this initial phase will be tested on multiple partner campuses in preparation for eventual broad dissemination.

  13. What is infidelity? Perceptions based on biological sex and personality

    OpenAIRE

    Thornton, Victoria; Nagurney, Alexander

    2011-01-01

    Victoria Thornton, Alexander NagurneyTexas State University – San Marcos, San Marcos, Texas, USAAbstract: The study examines perceptions of infidelity, paying particular attention to how these perceptions differ based on biological sex and personality traits, specifically agency and communion and their unmitigated counterparts. The study utilizes a sample of 125 male and 233 female college students. In addition to the personality measures, participants completed a 19-item checklist ...

  14. A Biologically Based Chemo-Sensing UAV for Humanitarian Demining

    Directory of Open Access Journals (Sweden)

    Paul F.M.J. Verschure

    2008-11-01

    Full Text Available Antipersonnel mines, weapons of cheap manufacture but lethal effect, have a high impact on the population even decades after the conflicts have finished. Here we investigate the use of a chemo-sensing Unmanned Aerial Vehicle (cUAV for demining tasks. We developed a blimp based UAV that is equipped with a broadly tuned metal-thin oxide chemo-sensor. A number of chemical mapping strategies were investigated including two biologically based localization strategies derived from the moth chemical search that can optimize the efficiency of the detection and localization of explosives and therefore be used in the demining process. Additionally, we developed a control layer that allows for both fully autonomous and manual controlled flight, as well as for the scheduling of a fleet of cUAVs. Our results confirm the feasibility of this technology for demining in real-world scenarios and give further support to a biologically based approach where the understanding of biological systems is used to solve difficult engineering problems.

  15. A Biologically Based Chemo-Sensing UAV for Humanitarian Demining

    Directory of Open Access Journals (Sweden)

    Sergi Bermúdez i Badia

    2007-06-01

    Full Text Available Antipersonnel mines, weapons of cheap manufacture but lethal effect, have a high impact on the population even decades after the conflicts have finished. Here we investigate the use of a chemo-sensing Unmanned Aerial Vehicle (cUAV for demining tasks. We developed a blimp based UAV that is equipped with a broadly tuned metal-thin oxide chemo-sensor. A number of chemical mapping strategies were investigated including two biologically based localization strategies derived from the moth chemical search that can optimize the efficiency of the detection and localization of explosives and therefore be used in the demining process. Additionally, we developed a control layer that allows for both fully autonomous and manual controlled flight, as well as for the scheduling of a fleet of cUAVs. Our results confirm the feasibility of this technology for demining in real-world scenarios and give further support to a biologically based approach where the understanding of biological systems is used to solve difficult engineering problems.

  16. Evaluation of the risk of perchlorate exposure in a population of late-gestation pregnant women in the United States: Application of probabilistic biologically-based dose response modeling

    International Nuclear Information System (INIS)

    Lumen, A; George, N I

    2017-01-01

    The risk of ubiquitous perchlorate exposure and the dose-response on thyroid hormone levels in pregnant women in the United States (U.S.) have yet to be characterized. In the current work, we integrated a previously developed perchlorate submodel into a recently developed population-based pregnancy model to predict reductions in maternal serum free thyroxine (fT4) levels for late-gestation pregnant women in the U.S. Our findings indicated no significant difference in geometric mean estimates of fT4 when perchlorate exposure from food only was compared to no perchlorate exposure. The reduction in maternal fT4 levels reached statistical significance when an added contribution from drinking water (i.e., 15 μg/L, 20 μg/L, or 24.5 μg/L) was assumed in addition to the 90th percentile of food intake for pregnant women (0.198 μg/kg/day). We determined that a daily intake of 0.45 to 0.50 μg/kg/day of perchlorate was necessary to produce results that were significantly different than those obtained from no perchlorate exposure. Adjusting for this food intake dose, the relative source contribution of perchlorate from drinking water (or other non-dietary sources) was estimated to range from 0.25–0.3 μg/kg/day. Assuming a drinking water intake rate of 0.033 L/kg/day, the drinking water concentration allowance for perchlorate equates to 7.6–9.2 μg/L. In summary, we have demonstrated the utility of a probabilistic biologically-based dose-response model for perchlorate risk assessment in a sensitive life-stage at a population level; however, there is a need for continued monitoring in regions of the U.S. where perchlorate exposure may be higher. - Highlights: • Probabilistic risk assessment for perchlorate in U.S. pregnant women was conducted. • No significant change in maternal fT4 predicted due to perchlorate from food alone. • Drinking water concentration allowance for perchlorate estimated as 7.6–9.2 μg/L

  17. Boolean Networks in Inference and Dynamic Modeling of Biological Systems at the Molecular and Physiological Level

    Science.gov (United States)

    Thakar, Juilee; Albert, Réka

    The following sections are included: * Introduction * Boolean Network Concepts and History * Extensions of the Classical Boolean Framework * Boolean Inference Methods and Examples in Biology * Dynamic Boolean Models: Examples in Plant Biology, Developmental Biology and Immunology * Conclusions * References

  18. Skull base tumor model.

    Science.gov (United States)

    Gragnaniello, Cristian; Nader, Remi; van Doormaal, Tristan; Kamel, Mahmoud; Voormolen, Eduard H J; Lasio, Giovanni; Aboud, Emad; Regli, Luca; Tulleken, Cornelius A F; Al-Mefty, Ossama

    2010-11-01

    Resident duty-hours restrictions have now been instituted in many countries worldwide. Shortened training times and increased public scrutiny of surgical competency have led to a move away from the traditional apprenticeship model of training. The development of educational models for brain anatomy is a fascinating innovation allowing neurosurgeons to train without the need to practice on real patients and it may be a solution to achieve competency within a shortened training period. The authors describe the use of Stratathane resin ST-504 polymer (SRSP), which is inserted at different intracranial locations to closely mimic meningiomas and other pathological entities of the skull base, in a cadaveric model, for use in neurosurgical training. Silicone-injected and pressurized cadaveric heads were used for studying the SRSP model. The SRSP presents unique intrinsic metamorphic characteristics: liquid at first, it expands and foams when injected into the desired area of the brain, forming a solid tumorlike structure. The authors injected SRSP via different passages that did not influence routes used for the surgical approach for resection of the simulated lesion. For example, SRSP injection routes included endonasal transsphenoidal or transoral approaches if lesions were to be removed through standard skull base approach, or, alternatively, SRSP was injected via a cranial approach if the removal was planned to be via the transsphenoidal or transoral route. The model was set in place in 3 countries (US, Italy, and The Netherlands), and a pool of 13 physicians from 4 different institutions (all surgeons and surgeons in training) participated in evaluating it and provided feedback. All 13 evaluating physicians had overall positive impressions of the model. The overall score on 9 components evaluated--including comparison between the tumor model and real tumor cases, perioperative requirements, general impression, and applicability--was 88% (100% being the best possible

  19. Continuous Modeling of Calcium Transport Through Biological Membranes

    Science.gov (United States)

    Jasielec, J. J.; Filipek, R.; Szyszkiewicz, K.; Sokalski, T.; Lewenstam, A.

    2016-08-01

    In this work an approach to the modeling of the biological membranes where a membrane is treated as a continuous medium is presented. The Nernst-Planck-Poisson model including Poisson equation for electric potential is used to describe transport of ions in the mitochondrial membrane—the interface which joins mitochondrial matrix with cellular cytosis. The transport of calcium ions is considered. Concentration of calcium inside the mitochondrion is not known accurately because different analytical methods give dramatically different results. We explain mathematically these differences assuming the complexing reaction inside mitochondrion and the existence of the calcium set-point (concentration of calcium in cytosis below which calcium stops entering the mitochondrion).

  20. MODEL OF METHODS OF FORMING BIOLOGICAL PICTURE OF THE WORLD OF SECONDARY SCHOOL PUPILS

    Directory of Open Access Journals (Sweden)

    Mikhail A. Yakunchev

    2016-12-01

    Full Text Available Introduction: the problem of development of a model of methods of forming the biological picture of the world of pupils as a multicomponent and integrative expression of the complete educational process is considered in the article. It is stated that the results of the study have theoretical and practical importance for effective subject preparation of senior pupils based on acquiring of systematic and generalized knowledge about wildlife. The correspondence of the main idea of the article to the scientific profile of the journal “Integration of Education” determines the choice of the periodical for publication. Materials and Methods: the results of the analysis of materials on modeling of the educational process, on specific models of the formation of a complete comprehension of the scientific picture of the world and its biological component make it possible to suggest a lack of elaboration of the aspect of pedagogical research under study. Therefore, the search for methods to overcome these gaps and to substantiate a particular model, relevant for its practical application by a teacher, is important. The study was based on the use of methods of theoretical level, including the analysis of pedagogical and methodological literature, modeling and generalized expression of the model of forming the biological picture of the world of secondary school senior pupils, which were of higher priority. Results: the use of models of organization of subject preparation of secondary school pupils takes a priority position, as they help to achieve the desired results of training, education and development. The model of methods of forming a biological picture of the world is represented as a theoretical construct in the unity of objective, substantive, procedural, diagnostic and effective blocks. Discussion and Conclusions: in a generalized form the article expresses the model of methods of forming the biological picture of the world of secondary school

  1. Biological profiling and dose-response modeling tools ...

    Science.gov (United States)

    Through its ToxCast project, the U.S. EPA has developed a battery of in vitro high throughput screening (HTS) assays designed to assess the potential toxicity of environmental chemicals. At present, over 1800 chemicals have been tested in up to 600 assays, yielding a large number of concentration-response data sets. Standard processing of these data sets involves finding a best fitting mathematical model and set of model parameters that specify this model. The model parameters include quantities such as the half-maximal activity concentration (or “AC50”) that have biological significance and can be used to inform the efficacy or potency of a given chemical with respect to a given assay. All of this data is processed and stored in an online-accessible database and website: http://actor.epa.gov/dashboard2. Results from these in vitro assays are used in a multitude of ways. New pathways and targets can be identified and incorporated into new or existing adverse outcome pathways (AOPs). Pharmacokinetic models such as those implemented EPA’s HTTK R package can be used to translate an in vitro concentration into an in vivo dose; i.e., one can predict the oral equivalent dose that might be expected to activate a specific biological pathway. Such predicted values can then be compared with estimated actual human exposures prioritize chemicals for further testing.Any quantitative examination should be accompanied by estimation of uncertainty. We are developing met

  2. Bernstein approximations in glasso-based estimation of biological networks

    NARCIS (Netherlands)

    Purutcuoglu, Vilda; Agraz, Melih; Wit, Ernst

    The Gaussian graphical model (GGM) is one of the common dynamic modelling approaches in the construction of gene networks. In inference of this modelling the interaction between genes can be detected mainly via graphical lasso (glasso) or coordinate descent-based approaches. Although these methods

  3. Biological impact of music and software-based auditory training

    Science.gov (United States)

    Kraus, Nina

    2012-01-01

    Auditory-based communication skills are developed at a young age and are maintained throughout our lives. However, some individuals – both young and old – encounter difficulties in achieving or maintaining communication proficiency. Biological signals arising from hearing sounds relate to real-life communication skills such as listening to speech in noisy environments and reading, pointing to an intersection between hearing and cognition. Musical experience, amplification, and software-based training can improve these biological signals. These findings of biological plasticity, in a variety of subject populations, relate to attention and auditory memory, and represent an integrated auditory system influenced by both sensation and cognition. Learning outcomes The reader will (1) understand that the auditory system is malleable to experience and training, (2) learn the ingredients necessary for auditory learning to successfully be applied to communication, (3) learn that the auditory brainstem response to complex sounds (cABR) is a window into the integrated auditory system, and (4) see examples of how cABR can be used to track the outcome of experience and training. PMID:22789822

  4. The model of drugs distribution dynamics in biological tissue

    Science.gov (United States)

    Ginevskij, D. A.; Izhevskij, P. V.; Sheino, I. N.

    2017-09-01

    The dose distribution by Neutron Capture Therapy follows the distribution of 10B in the tissue. The modern models of pharmacokinetics of drugs describe the processes occurring in conditioned "chambers" (blood-organ-tumor), but fail to describe the spatial distribution of the drug in the tumor and in normal tissue. The mathematical model of the spatial distribution dynamics of drugs in the tissue, depending on the concentration of the drug in the blood, was developed. The modeling method is the representation of the biological structure in the form of a randomly inhomogeneous medium in which the 10B distribution occurs. The parameters of the model, which cannot be determined rigorously in the experiment, are taken as the quantities subject to the laws of the unconnected random processes. The estimates of 10B distribution preparations in the tumor and healthy tissue, inside/outside the cells, are obtained.

  5. Biology-based combined-modality radiotherapy: workshop report

    International Nuclear Information System (INIS)

    Mason, Kathryn A.; Komaki, Ritsuko; Cox, James D.; Milas, Luka

    2001-01-01

    Purpose: The purpose of this workshop summary is to provide an overview of preclinical and clinical data on combined-modality radiotherapy. Methods and Materials: The 8th Annual Radiation Workshop at Round Top was held April 13-16, 2000 at the International Festival Institute (Round Top, TX). Results: Presentations by 30 speakers (from Germany, Netherlands, Australia, England, and France along with U.S. participants and M. D. Anderson Cancer Center faculty) formed the framework for discussions on the current status and future perspectives of biology-based combined-modality radiotherapy. Conclusion: Cellular and molecular pathways available for radiation modification by chemical and biologic agents are numerous, providing new opportunities for translational research in radiation oncology and for more effective combined-modality treatment of cancer

  6. Mouse models for gastric cancer: Matching models to biological questions.

    Science.gov (United States)

    Poh, Ashleigh R; O'Donoghue, Robert J J; Ernst, Matthias; Putoczki, Tracy L

    2016-07-01

    Gastric cancer is the third leading cause of cancer-related mortality worldwide. This is in part due to the asymptomatic nature of the disease, which often results in late-stage diagnosis, at which point there are limited treatment options. Even when treated successfully, gastric cancer patients have a high risk of tumor recurrence and acquired drug resistance. It is vital to gain a better understanding of the molecular mechanisms underlying gastric cancer pathogenesis to facilitate the design of new-targeted therapies that may improve patient survival. A number of chemically and genetically engineered mouse models of gastric cancer have provided significant insight into the contribution of genetic and environmental factors to disease onset and progression. This review outlines the strengths and limitations of current mouse models of gastric cancer and their relevance to the pre-clinical development of new therapeutics. © 2016 The Authors Journal of Gastroenterology and Hepatology published by Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.

  7. Unified Modeling of Filtration and Expression of Biological Sludge

    DEFF Research Database (Denmark)

    Sørensen, Peter Borgen

    Dewatering is a costly operation in both industry, e.g . when dewatering drilling mud, harbor sludge or biomass, and at municipal wastewater treatment plants when dewatering biological sludges. In practice, design and operation of dewatering equipment are mostly based on empirical knowledge, and ......, and normally results are not satisfactory, e.g. in terms of cake solids or capacity of equipment. Thus, there is a need for theoretical and technical developments to improve dewatering performance, based on better scientific knowledge and well defined principles and rules....

  8. Group Active Engagements Using Quantitative Modeling of Physiology Concepts in Large-Enrollment Biology Classes

    Directory of Open Access Journals (Sweden)

    Karen L. Carleton

    2016-12-01

    Full Text Available Organismal Biology is the third introductory biology course taught at the University of Maryland. Students learn about the geometric, physical, chemical, and thermodynamic constraints that are common to all life, and their implications for the evolution of multicellular organisms based on a common genetic “toolbox.”  An additional goal is helping students to improve their scientific logic and comfort with quantitative modeling.  We recently developed group active engagement exercises (GAEs for this Organismal Biology class.  Currently, our class is built around twelve GAE activities implemented in an auditorium lecture hall in a large enrollment class.  The GAEs examine scientific concepts using a variety of models including physical models, qualitative models, and Excel-based quantitative models. Three quantitative GAEs give students an opportunity to build their understanding of key physiological ideas. 1 The Escape from Planet Ranvier exercise reinforces student understanding that membrane permeability means that ions move through open channels in the membrane.  2 The Stressing and Straining exercise requires students to quantify the elastic modulus from data gathered either in class or from scientific literature. 3 In Leveraging Your Options exercise, students learn about lever systems and apply this knowledge to biological systems.

  9. Wave basin model tests of technical-biological bank protection

    Science.gov (United States)

    Eisenmann, J.

    2012-04-01

    Sloped embankments of inland waterways are usually protected from erosion and other negative im-pacts of ship-induced hydraulic loads by technical revetments consisting of riprap. Concerning the dimensioning of such bank protection there are several design rules available, e.g. the "Principles for the Design of Bank and Bottom Protection for Inland Waterways" or the Code of Practice "Use of Standard Construction Methods for Bank and Bottom Protection on Waterways" issued by the BAW (Federal Waterways Engineering and Research Institute). Since the European Water Framework Directive has been put into action special emphasis was put on natural banks. Therefore the application of technical-biological bank protection is favoured. Currently design principles for technical-biological bank protection on inland waterways are missing. The existing experiences mainly refer to flowing waters with no or low ship-induced hydraulic loads on the banks. Since 2004 the Federal Waterways Engineering and Research Institute has been tracking the re-search and development project "Alternative Technical-Biological Bank Protection on Inland Water-ways" in company with the Federal Institute of Hydrology. The investigation to date includes the ex-amination of waterway sections where technical- biological bank protection is applied locally. For the development of design rules for technical-biological bank protection investigations shall be carried out in a next step, considering the mechanics and resilience of technical-biological bank protection with special attention to ship-induced hydraulic loads. The presentation gives a short introduction into hydraulic loads at inland waterways and their bank protection. More in detail model tests of a willow brush mattress as a technical-biological bank protec-tion in a wave basin are explained. Within the scope of these tests the brush mattresses were ex-posed to wave impacts to determine their resilience towards hydraulic loads. Since the

  10. Topic modeling for cluster analysis of large biological and medical datasets.

    Science.gov (United States)

    Zhao, Weizhong; Zou, Wen; Chen, James J

    2014-01-01

    that topic model-based methods could provide an analytic advancement in the analysis of large biological or medical datasets.

  11. Invited review liquid crystal models of biological materials and silk spinning.

    Science.gov (United States)

    Rey, Alejandro D; Herrera-Valencia, Edtson E

    2012-06-01

    A review of thermodynamic, materials science, and rheological liquid crystal models is presented and applied to a wide range of biological liquid crystals, including helicoidal plywoods, biopolymer solutions, and in vivo liquid crystals. The distinguishing characteristics of liquid crystals (self-assembly, packing, defects, functionalities, processability) are discussed in relation to biological materials and the strong correspondence between different synthetic and biological materials is established. Biological polymer processing based on liquid crystalline precursors includes viscoelastic flow to form and shape fibers. Viscoelastic models for nematic and chiral nematics are reviewed and discussed in terms of key parameters that facilitate understanding and quantitative information from optical textures and rheometers. It is shown that viscoelastic modeling the silk spinning process using liquid crystal theories sheds light on textural transitions in the duct of spiders and silk worms as well as on tactoidal drops and interfacial structures. The range and consistency of the predictions demonstrates that the use of mesoscopic liquid crystal models is another tool to develop the science and biomimetic applications of mesogenic biological soft matter. Copyright © 2011 Wiley Periodicals, Inc.

  12. Model Based Definition

    Science.gov (United States)

    Rowe, Sidney E.

    2010-01-01

    In September 2007, the Engineering Directorate at the Marshall Space Flight Center (MSFC) created the Design System Focus Team (DSFT). MSFC was responsible for the in-house design and development of the Ares 1 Upper Stage and the Engineering Directorate was preparing to deploy a new electronic Configuration Management and Data Management System with the Design Data Management System (DDMS) based upon a Commercial Off The Shelf (COTS) Product Data Management (PDM) System. The DSFT was to establish standardized CAD practices and a new data life cycle for design data. Of special interest here, the design teams were to implement Model Based Definition (MBD) in support of the Upper Stage manufacturing contract. It is noted that this MBD does use partially dimensioned drawings for auxiliary information to the model. The design data lifecycle implemented several new release states to be used prior to formal release that allowed the models to move through a flow of progressive maturity. The DSFT identified some 17 Lessons Learned as outcomes of the standards development, pathfinder deployments and initial application to the Upper Stage design completion. Some of the high value examples are reviewed.

  13. Revision history aware repositories of computational models of biological systems.

    Science.gov (United States)

    Miller, Andrew K; Yu, Tommy; Britten, Randall; Cooling, Mike T; Lawson, James; Cowan, Dougal; Garny, Alan; Halstead, Matt D B; Hunter, Peter J; Nickerson, David P; Nunns, Geo; Wimalaratne, Sarala M; Nielsen, Poul M F

    2011-01-14

    Building repositories of computational models of biological systems ensures that published models are available for both education and further research, and can provide a source of smaller, previously verified models to integrate into a larger model. One problem with earlier repositories has been the limitations in facilities to record the revision history of models. Often, these facilities are limited to a linear series of versions which were deposited in the repository. This is problematic for several reasons. Firstly, there are many instances in the history of biological systems modelling where an 'ancestral' model is modified by different groups to create many different models. With a linear series of versions, if the changes made to one model are merged into another model, the merge appears as a single item in the history. This hides useful revision history information, and also makes further merges much more difficult, as there is no record of which changes have or have not already been merged. In addition, a long series of individual changes made outside of the repository are also all merged into a single revision when they are put back into the repository, making it difficult to separate out individual changes. Furthermore, many earlier repositories only retain the revision history of individual files, rather than of a group of files. This is an important limitation to overcome, because some types of models, such as CellML 1.1 models, can be developed as a collection of modules, each in a separate file. The need for revision history is widely recognised for computer software, and a lot of work has gone into developing version control systems and distributed version control systems (DVCSs) for tracking the revision history. However, to date, there has been no published research on how DVCSs can be applied to repositories of computational models of biological systems. We have extended the Physiome Model Repository software to be fully revision history aware

  14. Revision history aware repositories of computational models of biological systems

    Directory of Open Access Journals (Sweden)

    Nickerson David P

    2011-01-01

    Full Text Available Abstract Background Building repositories of computational models of biological systems ensures that published models are available for both education and further research, and can provide a source of smaller, previously verified models to integrate into a larger model. One problem with earlier repositories has been the limitations in facilities to record the revision history of models. Often, these facilities are limited to a linear series of versions which were deposited in the repository. This is problematic for several reasons. Firstly, there are many instances in the history of biological systems modelling where an 'ancestral' model is modified by different groups to create many different models. With a linear series of versions, if the changes made to one model are merged into another model, the merge appears as a single item in the history. This hides useful revision history information, and also makes further merges much more difficult, as there is no record of which changes have or have not already been merged. In addition, a long series of individual changes made outside of the repository are also all merged into a single revision when they are put back into the repository, making it difficult to separate out individual changes. Furthermore, many earlier repositories only retain the revision history of individual files, rather than of a group of files. This is an important limitation to overcome, because some types of models, such as CellML 1.1 models, can be developed as a collection of modules, each in a separate file. The need for revision history is widely recognised for computer software, and a lot of work has gone into developing version control systems and distributed version control systems (DVCSs for tracking the revision history. However, to date, there has been no published research on how DVCSs can be applied to repositories of computational models of biological systems. Results We have extended the Physiome Model

  15. Human pluripotent stem cells: an emerging model in developmental biology.

    Science.gov (United States)

    Zhu, Zengrong; Huangfu, Danwei

    2013-02-01

    Developmental biology has long benefited from studies of classic model organisms. Recently, human pluripotent stem cells (hPSCs), including human embryonic stem cells and human induced pluripotent stem cells, have emerged as a new model system that offers unique advantages for developmental studies. Here, we discuss how studies of hPSCs can complement classic approaches using model organisms, and how hPSCs can be used to recapitulate aspects of human embryonic development 'in a dish'. We also summarize some of the recently developed genetic tools that greatly facilitate the interrogation of gene function during hPSC differentiation. With the development of high-throughput screening technologies, hPSCs have the potential to revolutionize gene discovery in mammalian development.

  16. A model of heavy ion detection in physical and biological systems

    International Nuclear Information System (INIS)

    Waligorski, M.P.R.

    1988-01-01

    Track structure theory (the Katz model) and its application to the detection of heavy ions in physical and biological systems are reviewed. Following the use of a new corrected formula describing the radial distribution of average dose around the path of a heavy ion, based on results of Monte Carlo calculations and on results of experimental measurements, better agreement is achieved between model calculations and experimentally measured relative effectiveness, for enzymatic and viral systems, for the Fricke dosemeter and for alanine and thermoluminescent (TDL-700) dosemeters irradiated with beams of heavy charged particles. From experimentally measured RBE dependences for survival and frequency of neoplastic transformations in a mammalian cell culture irradiated with beams of energetic heavy ions, values of model parameters for these biological endpoints have been extracted, and a model extrapolation to the low-dose region performed. Results of model calculations are then compared with evaluations of the lung cancer hazard in populations exposed to radon and its progeny. The model can be applied to practical phenomenological analysis of radiation damage in solid-state systems and to dosimetry of charged particle and fast neutron beams using a variety of detectors. The model can also serve as a guide in building more basic models of the action of ionizing radiation with physical and biological systems and guide of development of models of radiation risk more relevant than that used presently. 185 refs., 31 figs., 3 tabs. (author)

  17. The quest for a new modelling framework in mathematical biology. Comment on "On the interplay between mathematics and biology: Hallmarks towards a new systems biology" by N. Bellomo et al.

    Science.gov (United States)

    Eftimie, Raluca

    2015-03-01

    One of the main unsolved problems of modern physics is finding a "theory of everything" - a theory that can explain, with the help of mathematics, all physical aspects of the universe. While the laws of physics could explain some aspects of the biology of living systems (e.g., the phenomenological interpretation of movement of cells and animals), there are other aspects specific to biology that cannot be captured by physics models. For example, it is generally accepted that the evolution of a cell-based system is influenced by the activation state of cells (e.g., only activated and functional immune cells can fight diseases); on the other hand, the evolution of an animal-based system can be influenced by the psychological state (e.g., distress) of animals. Therefore, the last 10-20 years have seen also a quest for a "theory of everything"-approach extended to biology, with researchers trying to propose mathematical modelling frameworks that can explain various biological phenomena ranging from ecology to developmental biology and medicine [1,2,6]. The basic idea behind this approach can be found in a few reviews on ecology and cell biology [6,7,9-11], where researchers suggested that due to the parallel between the micro-scale dynamics and the emerging macro-scale phenomena in both cell biology and in ecology, many mathematical methods used for ecological processes could be adapted to cancer modelling [7,9] or to modelling in immunology [11]. However, this approach generally involved the use of different models to describe different biological aspects (e.g., models for cell and animal movement, models for competition between cells or animals, etc.).

  18. Identifying biological concepts from a protein-related corpus with a probabilistic topic model

    Directory of Open Access Journals (Sweden)

    Lu Xinghua

    2006-02-01

    Full Text Available Abstract Background Biomedical literature, e.g., MEDLINE, contains a wealth of knowledge regarding functions of proteins. Major recurring biological concepts within such text corpora represent the domains of this body of knowledge. The goal of this research is to identify the major biological topics/concepts from a corpus of protein-related MEDLINE© titles and abstracts by applying a probabilistic topic model. Results The latent Dirichlet allocation (LDA model was applied to the corpus. Based on the Bayesian model selection, 300 major topics were extracted from the corpus. The majority of identified topics/concepts was found to be semantically coherent and most represented biological objects or concepts. The identified topics/concepts were further mapped to the controlled vocabulary of the Gene Ontology (GO terms based on mutual information. Conclusion The major and recurring biological concepts within a collection of MEDLINE documents can be extracted by the LDA model. The identified topics/concepts provide parsimonious and semantically-enriched representation of the texts in a semantic space with reduced dimensionality and can be used to index text.

  19. Invertebrates as model organisms for research on aging biology.

    Science.gov (United States)

    Murthy, Mahadev; Ram, Jeffrey L

    2015-01-30

    Invertebrate model systems, such as nematodes and fruit flies, have provided valuable information about the genetics and cellular biology involved in aging. However, limitations of these simple, genetically tractable organisms suggest the need for other model systems, some of them invertebrate, to facilitate further advances in the understanding of mechanisms of aging and longevity in mammals, including humans. This paper introduces 10 review articles about the use of invertebrate model systems for the study of aging by authors who participated in an 'NIA-NIH symposium on aging in invertebrate model systems' at the 2013 International Congress for Invertebrate Reproduction and Development. In contrast to the highly derived characteristics of nematodes and fruit flies as members of the superphylum Ecdysozoa, cnidarians, such as Hydra, are more 'basal' organisms that have a greater number of genetic orthologs in common with humans. Moreover, some other new model systems, such as the urochordate Botryllus schlosseri , the tunicate Ciona , and the sea urchins (Echinodermata) are members of the Deuterostomia, the same superphylum that includes all vertebrates, and thus have mechanisms that are likely to be more closely related to those occurring in humans. Additional characteristics of these new model systems, such as the recent development of new molecular and genetic tools and a more similar pattern to humans of regeneration and stem cell function suggest that these new model systems may have unique advantages for the study of mechanisms of aging and longevity.

  20. Automated numerical simulation of biological pattern formation based on visual feedback simulation framework.

    Science.gov (United States)

    Sun, Mingzhu; Xu, Hui; Zeng, Xingjuan; Zhao, Xin

    2017-01-01

    There are various fantastic biological phenomena in biological pattern formation. Mathematical modeling using reaction-diffusion partial differential equation systems is employed to study the mechanism of pattern formation. However, model parameter selection is both difficult and time consuming. In this paper, a visual feedback simulation framework is proposed to calculate the parameters of a mathematical model automatically based on the basic principle of feedback control. In the simulation framework, the simulation results are visualized, and the image features are extracted as the system feedback. Then, the unknown model parameters are obtained by comparing the image features of the simulation image and the target biological pattern. Considering two typical applications, the visual feedback simulation framework is applied to fulfill pattern formation simulations for vascular mesenchymal cells and lung development. In the simulation framework, the spot, stripe, labyrinthine patterns of vascular mesenchymal cells, the normal branching pattern and the branching pattern lacking side branching for lung branching are obtained in a finite number of iterations. The simulation results indicate that it is easy to achieve the simulation targets, especially when the simulation patterns are sensitive to the model parameters. Moreover, this simulation framework can expand to other types of biological pattern formation.

  1. Biologically inspired control and modeling of (biorobotic systems and some applications of fractional calculus in mechanics

    Directory of Open Access Journals (Sweden)

    Lazarević Mihailo P.

    2013-01-01

    Full Text Available In this paper, the applications of biologically inspired modeling and control of (biomechanical (nonredundant mechanisms are presented, as well as newly obtained results of author in mechanics which are based on using fractional calculus. First, it is proposed to use biological analog-synergy due to existence of invariant features in the execution of functional motion. Second, the model of (biomechanical system may be obtained using another biological concept called distributed positioning (DP, which is based on the inertial properties and actuation of joints of considered mechanical system. In addition, it is proposed to use other biological principles such as: principle of minimum interaction, which takes a main role in hierarchical structure of control and self-adjusting principle (introduce local positive/negative feedback on control with great amplifying, which allows efficiently realization of control based on iterative natural learning. Also, new, recently obtained results of the author in the fields of stability, electroviscoelasticity, and control theory are presented which are based on using fractional calculus (FC. [Projekat Ministarstva nauke Republike Srbije, br. 35006

  2. Learning Cell Biology as a Team: A Project-Based Approach to Upper-Division Cell Biology

    Science.gov (United States)

    Wright, Robin; Boggs, James

    2002-01-01

    To help students develop successful strategies for learning how to learn and communicate complex information in cell biology, we developed a quarter-long cell biology class based on team projects. Each team researches a particular human disease and presents information about the cellular structure or process affected by the disease, the cellular…

  3. Biology

    Indian Academy of Sciences (India)

    I am particularly happy that the Academy is bringing out this document by Professor M S. Valiathan on Ayurvedic Biology. It is an effort to place before the scientific community, especially that of India, the unique scientific opportunities that arise out of viewing Ayurveda from the perspective of contemporary science, its tools ...

  4. Panel 4: Recent advances in otitis media in molecular biology, biochemistry, genetics, and animal models.

    Science.gov (United States)

    Li, Jian-Dong; Hermansson, Ann; Ryan, Allen F; Bakaletz, Lauren O; Brown, Steve D; Cheeseman, Michael T; Juhn, Steven K; Jung, Timothy T K; Lim, David J; Lim, Jae Hyang; Lin, Jizhen; Moon, Sung-Kyun; Post, J Christopher

    2013-04-01

    Otitis media (OM) is the most common childhood bacterial infection and also the leading cause of conductive hearing loss in children. Currently, there is an urgent need for developing novel therapeutic agents for treating OM based on full understanding of molecular pathogenesis in the areas of molecular biology, biochemistry, genetics, and animal model studies in OM. To provide a state-of-the-art review concerning recent advances in OM in the areas of molecular biology, biochemistry, genetics, and animal model studies and to discuss the future directions of OM studies in these areas. A structured search of the current literature (since June 2007). The authors searched PubMed for published literature in the areas of molecular biology, biochemistry, genetics, and animal model studies in OM. Over the past 4 years, significant progress has been made in the areas of molecular biology, biochemistry, genetics, and animal model studies in OM. These studies brought new insights into our understanding of the molecular and biochemical mechanisms underlying the molecular pathogenesis of OM and helped identify novel therapeutic targets for OM. Our understanding of the molecular pathogenesis of OM has been significantly advanced, particularly in the areas of inflammation, innate immunity, mucus overproduction, mucosal hyperplasia, middle ear and inner ear interaction, genetics, genome sequencing, and animal model studies. Although these studies are still in their experimental stages, they help identify new potential therapeutic targets. Future preclinical and clinical studies will help to translate these exciting experimental research findings into clinical applications.

  5. Bayesian Network Webserver: a comprehensive tool for biological network modeling.

    Science.gov (United States)

    Ziebarth, Jesse D; Bhattacharya, Anindya; Cui, Yan

    2013-11-01

    The Bayesian Network Webserver (BNW) is a platform for comprehensive network modeling of systems genetics and other biological datasets. It allows users to quickly and seamlessly upload a dataset, learn the structure of the network model that best explains the data and use the model to understand relationships between network variables. Many datasets, including those used to create genetic network models, contain both discrete (e.g. genotype) and continuous (e.g. gene expression traits) variables, and BNW allows for modeling hybrid datasets. Users of BNW can incorporate prior knowledge during structure learning through an easy-to-use structural constraint interface. After structure learning, users are immediately presented with an interactive network model, which can be used to make testable hypotheses about network relationships. BNW, including a downloadable structure learning package, is available at http://compbio.uthsc.edu/BNW. (The BNW interface for adding structural constraints uses HTML5 features that are not supported by current version of Internet Explorer. We suggest using other browsers (e.g. Google Chrome or Mozilla Firefox) when accessing BNW). ycui2@uthsc.edu. Supplementary data are available at Bioinformatics online.

  6. Continuous time Boolean modeling for biological signaling: application of Gillespie algorithm.

    OpenAIRE

    Stoll, Gautier; Viara, Eric; Barillot, Emmanuel; Calzone, Laurence

    2012-01-01

    Abstract Mathematical modeling is used as a Systems Biology tool to answer biological questions, and more precisely, to validate a network that describes biological observations and predict the effect of perturbations. This article presents an algorithm for modeling biological networks in a discrete framework with continuous time. Background There exist two major types of mathematical modeling approaches: (1) quantitative modeling, representing various chemical species concentrations by real...

  7. Fluctuating Nonlinear Spring Model of Mechanical Deformation of Biological Particles.

    Directory of Open Access Journals (Sweden)

    Olga Kononova

    2016-01-01

    Full Text Available The mechanical properties of virus capsids correlate with local conformational dynamics in the capsid structure. They also reflect the required stability needed to withstand high internal pressures generated upon genome loading and contribute to the success of important events in viral infectivity, such as capsid maturation, genome uncoating and receptor binding. The mechanical properties of biological nanoparticles are often determined from monitoring their dynamic deformations in Atomic Force Microscopy nanoindentation experiments; but a comprehensive theory describing the full range of observed deformation behaviors has not previously been described. We present a new theory for modeling dynamic deformations of biological nanoparticles, which considers the non-linear Hertzian deformation, resulting from an indenter-particle physical contact, and the bending of curved elements (beams modeling the particle structure. The beams' deformation beyond the critical point triggers a dynamic transition of the particle to the collapsed state. This extreme event is accompanied by a catastrophic force drop as observed in the experimental or simulated force (F-deformation (X spectra. The theory interprets fine features of the spectra, including the nonlinear components of the FX-curves, in terms of the Young's moduli for Hertzian and bending deformations, and the structural damage dependent beams' survival probability, in terms of the maximum strength and the cooperativity parameter. The theory is exemplified by successfully describing the deformation dynamics of natural nanoparticles through comparing theoretical curves with experimental force-deformation spectra for several virus particles. This approach provides a comprehensive description of the dynamic structural transitions in biological and artificial nanoparticles, which is essential for their optimal use in nanotechnology and nanomedicine applications.

  8. Modeling human risk: Cell & molecular biology in context

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1997-06-01

    It is anticipated that early in the next century manned missions into outer space will occur, with a mission to Mars scheduled between 2015 and 2020. However, before such missions can be undertaken, a realistic estimation of the potential risks to the flight crews is required. One of the uncertainties remaining in this risk estimation is that posed by the effects of exposure to the radiation environment of outer space. Although the composition of this environment is fairly well understood, the biological effects arising from exposure to it are not. The reasons for this are three-fold: (1) A small but highly significant component of the radiation spectrum in outer space consists of highly charged, high energy (HZE) particles which are not routinely experienced on earth, and for which there are insufficient data on biological effects; (2) Most studies on the biological effects of radiation to date have been high-dose, high dose-rate, whereas in space, with the exception of solar particle events, radiation exposures will be low-dose, low dose-rate; (3) Although it has been established that the virtual absence of gravity in space has a profound effect on human physiology, it is not clear whether these effects will act synergistically with those of radiation exposure. A select panel will evaluate the utilizing experiments and models to accurately predict the risks associated with exposure to HZE particles. Topics of research include cellular and tissue response, health effects associated with radiation damage, model animal systems, and critical markers of Radiation response.

  9. Modeling human risk: Cell ampersand molecular biology in context

    International Nuclear Information System (INIS)

    1997-06-01

    It is anticipated that early in the next century manned missions into outer space will occur, with a mission to Mars scheduled between 2015 and 2020. However, before such missions can be undertaken, a realistic estimation of the potential risks to the flight crews is required. One of the uncertainties remaining in this risk estimation is that posed by the effects of exposure to the radiation environment of outer space. Although the composition of this environment is fairly well understood, the biological effects arising from exposure to it are not. The reasons for this are three-fold: (1) A small but highly significant component of the radiation spectrum in outer space consists of highly charged, high energy (HZE) particles which are not routinely experienced on earth, and for which there are insufficient data on biological effects; (2) Most studies on the biological effects of radiation to date have been high-dose, high dose-rate, whereas in space, with the exception of solar particle events, radiation exposures will be low-dose, low dose-rate; (3) Although it has been established that the virtual absence of gravity in space has a profound effect on human physiology, it is not clear whether these effects will act synergistically with those of radiation exposure. A select panel will evaluate the utilizing experiments and models to accurately predict the risks associated with exposure to HZE particles. Topics of research include cellular and tissue response, health effects associated with radiation damage, model animal systems, and critical markers of Radiation response

  10. Exploring Neural Network Models with Hierarchical Memories and Their Use in Modeling Biological Systems

    Science.gov (United States)

    Pusuluri, Sai Teja

    Energy landscapes are often used as metaphors for phenomena in biology, social sciences and finance. Different methods have been implemented in the past for the construction of energy landscapes. Neural network models based on spin glass physics provide an excellent mathematical framework for the construction of energy landscapes. This framework uses a minimal number of parameters and constructs the landscape using data from the actual phenomena. In the past neural network models were used to mimic the storage and retrieval process of memories (patterns) in the brain. With advances in the field now, these models are being used in machine learning, deep learning and modeling of complex phenomena. Most of the past literature focuses on increasing the storage capacity and stability of stored patterns in the network but does not study these models from a modeling perspective or an energy landscape perspective. This dissertation focuses on neural network models both from a modeling perspective and from an energy landscape perspective. I firstly show how the cellular interconversion phenomenon can be modeled as a transition between attractor states on an epigenetic landscape constructed using neural network models. The model allows the identification of a reaction coordinate of cellular interconversion by analyzing experimental and simulation time course data. Monte Carlo simulations of the model show that the initial phase of cellular interconversion is a Poisson process and the later phase of cellular interconversion is a deterministic process. Secondly, I explore the static features of landscapes generated using neural network models, such as sizes of basins of attraction and densities of metastable states. The simulation results show that the static landscape features are strongly dependent on the correlation strength and correlation structure between patterns. Using different hierarchical structures of the correlation between patterns affects the landscape features

  11. Modeling complexity: cognitive constraints and computational model-building in integrative systems biology.

    Science.gov (United States)

    MacLeod, Miles; Nersessian, Nancy J

    2018-01-08

    Modern integrative systems biology defines itself by the complexity of the problems it takes on through computational modeling and simulation. However in integrative systems biology computers do not solve problems alone. Problem solving depends as ever on human cognitive resources. Current philosophical accounts hint at their importance, but it remains to be understood what roles human cognition plays in computational modeling. In this paper we focus on practices through which modelers in systems biology use computational simulation and other tools to handle the cognitive complexity of their modeling problems so as to be able to make significant contributions to understanding, intervening in, and controlling complex biological systems. We thus show how cognition, especially processes of simulative mental modeling, is implicated centrally in processes of model-building. At the same time we suggest how the representational choices of what to model in systems biology are limited or constrained as a result. Such constraints help us both understand and rationalize the restricted form that problem solving takes in the field and why its results do not always measure up to expectations.

  12. A Self-Assisting Protein Folding Model for Teaching Structural Molecular Biology.

    Science.gov (United States)

    Davenport, Jodi; Pique, Michael; Getzoff, Elizabeth; Huntoon, Jon; Gardner, Adam; Olson, Arthur

    2017-04-04

    Structural molecular biology is now becoming part of high school science curriculum thus posing a challenge for teachers who need to convey three-dimensional (3D) structures with conventional text and pictures. In many cases even interactive computer graphics does not go far enough to address these challenges. We have developed a flexible model of the polypeptide backbone using 3D printing technology. With this model we have produced a polypeptide assembly kit to create an idealized model of the Triosephosphate isomerase mutase enzyme (TIM), which forms a structure known as TIM barrel. This kit has been used in a laboratory practical where students perform a step-by-step investigation into the nature of protein folding, starting with the handedness of amino acids to the formation of secondary and tertiary structure. Based on the classroom evidence we collected, we conclude that these models are valuable and inexpensive resource for teaching structural molecular biology. Copyright © 2017 Elsevier Ltd. All rights reserved.

  13. Naumovozyma castellii: an alternative model for budding yeast molecular biology.

    Science.gov (United States)

    Karademir Andersson, Ahu; Cohn, Marita

    2017-03-01

    Naumovozyma castellii (Saccharomyces castellii) is a member of the budding yeast family Saccharomycetaceae. It has been extensively used as a model organism for telomere biology research and has gained increasing interest as a budding yeast model for functional analyses owing to its amenability to genetic modifications. Owing to the suitable phylogenetic distance to S. cerevisiae, the whole genome sequence of N. castellii has provided unique data for comparative genomic studies, and it played a key role in the establishment of the timing of the whole genome duplication and the evolutionary events that took place in the subsequent genomic evolution of the Saccharomyces lineage. Here we summarize the historical background of its establishment as a laboratory yeast species, and the development of genetic and molecular tools and strains. We review the research performed on N. castellii, focusing on areas where it has significantly contributed to the discovery of new features of molecular biology and to the advancement of our understanding of molecular evolution. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  14. Differential geometry based multiscale models.

    Science.gov (United States)

    Wei, Guo-Wei

    2010-08-01

    Large chemical and biological systems such as fuel cells, ion channels, molecular motors, and viruses are of great importance to the scientific community and public health. Typically, these complex systems in conjunction with their aquatic environment pose a fabulous challenge to theoretical description, simulation, and prediction. In this work, we propose a differential geometry based multiscale paradigm to model complex macromolecular systems, and to put macroscopic and microscopic descriptions on an equal footing. In our approach, the differential geometry theory of surfaces and geometric measure theory are employed as a natural means to couple the macroscopic continuum mechanical description of the aquatic environment with the microscopic discrete atomistic description of the macromolecule. Multiscale free energy functionals, or multiscale action functionals are constructed as a unified framework to derive the governing equations for the dynamics of different scales and different descriptions. Two types of aqueous macromolecular complexes, ones that are near equilibrium and others that are far from equilibrium, are considered in our formulations. We show that generalized Navier-Stokes equations for the fluid dynamics, generalized Poisson equations or generalized Poisson-Boltzmann equations for electrostatic interactions, and Newton's equation for the molecular dynamics can be derived by the least action principle. These equations are coupled through the continuum-discrete interface whose dynamics is governed by potential driven geometric flows. Comparison is given to classical descriptions of the fluid and electrostatic interactions without geometric flow based micro-macro interfaces. The detailed balance of forces is emphasized in the present work. We further extend the proposed multiscale paradigm to micro-macro analysis of electrohydrodynamics, electrophoresis, fuel cells, and ion channels. We derive generalized Poisson-Nernst-Planck equations that are

  15. Differential Geometry Based Multiscale Models

    Science.gov (United States)

    Wei, Guo-Wei

    2010-01-01

    Large chemical and biological systems such as fuel cells, ion channels, molecular motors, and viruses are of great importance to the scientific community and public health. Typically, these complex systems in conjunction with their aquatic environment pose a fabulous challenge to theoretical description, simulation, and prediction. In this work, we propose a differential geometry based multiscale paradigm to model complex macromolecular systems, and to put macroscopic and microscopic descriptions on an equal footing. In our approach, the differential geometry theory of surfaces and geometric measure theory are employed as a natural means to couple the macroscopic continuum mechanical description of the aquatic environment with the microscopic discrete atom-istic description of the macromolecule. Multiscale free energy functionals, or multiscale action functionals are constructed as a unified framework to derive the governing equations for the dynamics of different scales and different descriptions. Two types of aqueous macromolecular complexes, ones that are near equilibrium and others that are far from equilibrium, are considered in our formulations. We show that generalized Navier–Stokes equations for the fluid dynamics, generalized Poisson equations or generalized Poisson–Boltzmann equations for electrostatic interactions, and Newton's equation for the molecular dynamics can be derived by the least action principle. These equations are coupled through the continuum-discrete interface whose dynamics is governed by potential driven geometric flows. Comparison is given to classical descriptions of the fluid and electrostatic interactions without geometric flow based micro-macro interfaces. The detailed balance of forces is emphasized in the present work. We further extend the proposed multiscale paradigm to micro-macro analysis of electrohydrodynamics, electrophoresis, fuel cells, and ion channels. We derive generalized Poisson–Nernst–Planck equations that

  16. Quasi – biological model of radiogenic cancer morbidity

    Directory of Open Access Journals (Sweden)

    A. T. Gubin

    2015-01-01

    Full Text Available The methods: Linear differential equations were used to formalize contemporary assumptions of self –sustaining tissue cell kinetics under the impact of adverse factors, on the formation and repairing of cell “pre-cancer” defects, on inheritance and retaining such defects in daughter cells which results in malignant neoplasms, on age-dependent impairment of human body’s function to eliminate such cells.The results: The model reproduces the well-known regularities of radiogenic cancer morbidity increase depending on instantaneous radiation exposure age and on attained age: the relative reduction at increased radiation age which the model attributes to age decrease of stem cells, relative reduction at increased time after radiation induced by “sorting out” of cells with “pre-cancer” defects, absolute increase with age proportional to natural cause mortality rate.The relevance of the developed quasi-biological model is displayed via comparison to the ICRP model for radiogenic increase of solid carcinomas’ morbidity after single radiation exposure. The latter model had been developed after Japanese cohort observations. For both genders high goodness-of-fit was achieved between the models at values of Gompertz’ law factor which had been defined for men and women in this cohort via selecting the value of the only free parameter indicating age-dependent exponential retardation of stem cells’ division.The conclusion: The proposed model suggests that the estimation of radiogenic risk inter-population transfer can be done on the basis of the data on age-dependent mortality intensity increase from all natural causes. The model also creates the premises for inter-species transfer of risk following the well-known parameters of cell populations’ kinetics in animal’s organs and tissues and Gompertz’s law parameters. This model is applicable also for analyses of age-dependent changes of background cancer morbidity. 

  17. Spatial landscape model to characterize biological diversity using R statistical computing environment.

    Science.gov (United States)

    Singh, Hariom; Garg, R D; Karnatak, Harish C; Roy, Arijit

    2018-01-15

    Due to urbanization and population growth, the degradation of natural forests and associated biodiversity are now widely recognized as a global environmental concern. Hence, there is an urgent need for rapid assessment and monitoring of biodiversity on priority using state-of-art tools and technologies. The main purpose of this research article is to develop and implement a new methodological approach to characterize biological diversity using spatial model developed during the study viz. Spatial Biodiversity Model (SBM). The developed model is scale, resolution and location independent solution for spatial biodiversity richness modelling. The platform-independent computation model is based on parallel computation. The biodiversity model based on open-source software has been implemented on R statistical computing platform. It provides information on high disturbance and high biological richness areas through different landscape indices and site specific information (e.g. forest fragmentation (FR), disturbance index (DI) etc.). The model has been developed based on the case study of Indian landscape; however it can be implemented in any part of the world. As a case study, SBM has been tested for Uttarakhand state in India. Inputs for landscape ecology are derived through multi-criteria decision making (MCDM) techniques in an interactive command line environment. MCDM with sensitivity analysis in spatial domain has been carried out to illustrate the model stability and robustness. Furthermore, spatial regression analysis has been made for the validation of the output. Copyright © 2017 Elsevier Ltd. All rights reserved.

  18. Biological sequence analysis: probabilistic models of proteins and nucleic acids

    National Research Council Canada - National Science Library

    Durbin, Richard

    1998-01-01

    ... analysis methods are now based on principles of probabilistic modelling. Examples of such methods include the use of probabilistically derived score matrices to determine the significance of sequence alignments, the use of hidden Markov models as the basis for profile searches to identify distant members of sequence families, and the inference...

  19. Computational brain models: Advances from system biology and future challenges

    Directory of Open Access Journals (Sweden)

    George E. Barreto

    2015-02-01

    Full Text Available Computational brain models focused on the interactions between neurons and astrocytes, modeled via metabolic reconstructions, are reviewed. The large source of experimental data provided by the -omics techniques and the advance/application of computational and data-management tools are being fundamental. For instance, in the understanding of the crosstalk between these cells, the key neuroprotective mechanisms mediated by astrocytes in specific metabolic scenarios (1 and the identification of biomarkers for neurodegenerative diseases (2,3. However, the modeling of these interactions demands a clear view of the metabolic and signaling pathways implicated, but most of them are controversial and are still under evaluation (4. Hence, to gain insight into the complexity of these interactions a current view of the main pathways implicated in the neuron-astrocyte communication processes have been made from recent experimental reports and reviews. Furthermore, target problems, limitations and main conclusions have been identified from metabolic models of the brain reported from 2010. Finally, key aspects to take into account into the development of a computational model of the brain and topics that could be approached from a systems biology perspective in future research are highlighted.

  20. Models for integrated pest control and their biological implications.

    Science.gov (United States)

    Tang, Sanyi; Cheke, Robert A

    2008-09-01

    Successful integrated pest management (IPM) control programmes depend on many factors which include host-parasitoid ratios, starting densities, timings of parasitoid releases, dosages and timings of insecticide applications and levels of host-feeding and parasitism. Mathematical models can help us to clarify and predict the effects of such factors on the stability of host-parasitoid systems, which we illustrate here by extending the classical continuous and discrete host-parasitoid models to include an IPM control programme. The results indicate that one of three control methods can maintain the host level below the economic threshold (ET) in relation to different ET levels, initial densities of host and parasitoid populations and host-parasitoid ratios. The effects of host intrinsic growth rate and parasitoid searching efficiency on host mean outbreak period can be calculated numerically from the models presented. The instantaneous pest killing rate of an insecticide application is also estimated from the models. The results imply that the modelling methods described can help in the design of appropriate control strategies and assist management decision-making. The results also indicate that a high initial density of parasitoids (such as in inundative releases) and high parasitoid inter-generational survival rates will lead to more frequent host outbreaks and, therefore, greater economic damage. The biological implications of this counter intuitive result are discussed.

  1. CEBS object model for systems biology data, SysBio-OM.

    Science.gov (United States)

    Xirasagar, Sandhya; Gustafson, Scott; Merrick, B Alex; Tomer, Kenneth B; Stasiewicz, Stanley; Chan, Denny D; Yost, Kenneth J; Yates, John R; Sumner, Susan; Xiao, Nianqing; Waters, Michael D

    2004-09-01

    To promote a systems biology approach to understanding the biological effects of environmental stressors, the Chemical Effects in Biological Systems (CEBS) knowledge base is being developed to house data from multiple complex data streams in a systems friendly manner that will accommodate extensive querying from users. Unified data representation via a single object model will greatly aid in integrating data storage and management, and facilitate reuse of software to analyze and display data resulting from diverse differential expression or differential profile technologies. Data streams include, but are not limited to, gene expression analysis (transcriptomics), protein expression and protein-protein interaction analysis (proteomics) and changes in low molecular weight metabolite levels (metabolomics). To enable the integration of microarray gene expression, proteomics and metabolomics data in the CEBS system, we designed an object model, Systems Biology Object Model (SysBio-OM). The model is comprehensive and leverages other open source efforts, namely the MicroArray Gene Expression Object Model (MAGE-OM) and the Proteomics Experiment Data Repository (PEDRo) object model. SysBio-OM is designed by extending MAGE-OM to represent protein expression data elements (including those from PEDRo), protein-protein interaction and metabolomics data. SysBio-OM promotes the standardization of data representation and data quality by facilitating the capture of the minimum annotation required for an experiment. Such standardization refines the accuracy of data mining and interpretation. The open source SysBio-OM model, which can be implemented on varied computing platforms is presented here. A universal modeling language depiction of the entire SysBio-OM is available at http://cebs.niehs.nih.gov/SysBioOM/. The Rational Rose object model package is distributed under an open source license that permits unrestricted academic and commercial use and is available at http

  2. Respectful Modeling: Addressing Uncertainty in Dynamic System Models for Molecular Biology.

    Science.gov (United States)

    Tsigkinopoulou, Areti; Baker, Syed Murtuza; Breitling, Rainer

    2017-06-01

    Although there is still some skepticism in the biological community regarding the value and significance of quantitative computational modeling, important steps are continually being taken to enhance its accessibility and predictive power. We view these developments as essential components of an emerging 'respectful modeling' framework which has two key aims: (i) respecting the models themselves and facilitating the reproduction and update of modeling results by other scientists, and (ii) respecting the predictions of the models and rigorously quantifying the confidence associated with the modeling results. This respectful attitude will guide the design of higher-quality models and facilitate the use of models in modern applications such as engineering and manipulating microbial metabolism by synthetic biology. Copyright © 2016 Elsevier Ltd. All rights reserved.

  3. Investigating How German Biology Teachers Use Three-Dimensional Physical Models in Classroom Instruction: a Video Study

    Science.gov (United States)

    Werner, Sonja; Förtsch, Christian; Boone, William; von Kotzebue, Lena; Neuhaus, Birgit J.

    2017-07-01

    To obtain a general understanding of science, model use as part of National Education Standards is important for instruction. Model use can be characterized by three aspects: (1) the characteristics of the model, (2) the integration of the model into instruction, and (3) the use of models to foster scientific reasoning. However, there were no empirical results describing the implementation of National Education Standards in science instruction concerning the use of models. Therefore, the present study investigated the implementation of different aspects of model use in German biology instruction. Two biology lessons on the topic neurobiology in grade nine of 32 biology teachers were videotaped (N = 64 videos). These lessons were analysed using an event-based coding manual according to three aspects of model described above. Rasch analysis of the coded categories was conducted and showed reliable measurement. In the first analysis, we identified 68 lessons where a total of 112 different models were used. The in-depth analysis showed that special aspects of an elaborate model use according to several categories of scientific reasoning were rarely implemented in biology instruction. A critical reflection of the used model (N = 25 models; 22.3%) and models to demonstrate scientific reasoning (N = 26 models; 23.2%) were seldom observed. Our findings suggest that pre-service biology teacher education and professional development initiatives in Germany have to focus on both aspects.

  4. Effect of amino acid supplementation on titer and glycosylation distribution in hybridoma cell cultures-Systems biology-based interpretation using genome-scale metabolic flux balance model and multivariate data analysis.

    Science.gov (United States)

    Reimonn, Thomas M; Park, Seo-Young; Agarabi, Cyrus D; Brorson, Kurt A; Yoon, Seongkyu

    2016-09-01

    Genome-scale flux balance analysis (FBA) is a powerful systems biology tool to characterize intracellular reaction fluxes during cell cultures. FBA estimates intracellular reaction rates by optimizing an objective function, subject to the constraints of a metabolic model and media uptake/excretion rates. A dynamic extension to FBA, dynamic flux balance analysis (DFBA), can calculate intracellular reaction fluxes as they change during cell cultures. In a previous study by Read et al. (2013), a series of informed amino acid supplementation experiments were performed on twelve parallel murine hybridoma cell cultures, and this data was leveraged for further analysis (Read et al., Biotechnol Prog. 2013;29:745-753). In order to understand the effects of media changes on the model murine hybridoma cell line, a systems biology approach is applied in the current study. Dynamic flux balance analysis was performed using a genome-scale mouse metabolic model, and multivariate data analysis was used for interpretation. The calculated reaction fluxes were examined using partial least squares and partial least squares discriminant analysis. The results indicate media supplementation increases product yield because it raises nutrient levels extending the growth phase, and the increased cell density allows for greater culture performance. At the same time, the directed supplementation does not change the overall metabolism of the cells. This supports the conclusion that product quality, as measured by glycoform assays, remains unchanged because the metabolism remains in a similar state. Additionally, the DFBA shows that metabolic state varies more at the beginning of the culture but less by the middle of the growth phase, possibly due to stress on the cells during inoculation. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:1163-1173, 2016. © 2016 American Institute of Chemical Engineers.

  5. WE-B-304-02: Treatment Planning Evaluation and Optimization Should Be Biologically and Not Dose/volume Based

    International Nuclear Information System (INIS)

    Deasy, J.

    2015-01-01

    The ultimate goal of radiotherapy treatment planning is to find a treatment that will yield a high tumor control probability (TCP) with an acceptable normal tissue complication probability (NTCP). Yet most treatment planning today is not based upon optimization of TCPs and NTCPs, but rather upon meeting physical dose and volume constraints defined by the planner. It has been suggested that treatment planning evaluation and optimization would be more effective if they were biologically and not dose/volume based, and this is the claim debated in this month’s Point/Counterpoint. After a brief overview of biologically and DVH based treatment planning by the Moderator Colin Orton, Joseph Deasy (for biological planning) and Charles Mayo (against biological planning) will begin the debate. Some of the arguments in support of biological planning include: this will result in more effective dose distributions for many patients DVH-based measures of plan quality are known to have little predictive value there is little evidence that either D95 or D98 of the PTV is a good predictor of tumor control sufficient validated outcome prediction models are now becoming available and should be used to drive planning and optimization Some of the arguments against biological planning include: several decades of experience with DVH-based planning should not be discarded we do not know enough about the reliability and errors associated with biological models the radiotherapy community in general has little direct experience with side by side comparisons of DVH vs biological metrics and outcomes it is unlikely that a clinician would accept extremely cold regions in a CTV or hot regions in a PTV, despite having acceptable TCP values Learning Objectives: To understand dose/volume based treatment planning and its potential limitations To understand biological metrics such as EUD, TCP, and NTCP To understand biologically based treatment planning and its potential limitations

  6. Intelligence-based anti-doping from an equine biological passport.

    Science.gov (United States)

    Cawley, Adam T; Keledjian, John

    2017-09-01

    The move towards personalized medicine derived from individually focused clinical chemistry measurements has been translated by the human anti-doping movement over the past decade into developing the athlete biological passport. There is considerable potential for animal sports to adapt this model to facilitate an intelligence-based anti-doping system. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  7. Erythrocytes as a biological model for screening of xenobiotics toxicity.

    Science.gov (United States)

    Farag, Mayada Ragab; Alagawany, Mahmoud

    2018-01-05

    Erythrocytes are the main cells in circulation. They are devoid of internal membrane structures and easy to be isolated and handled providing a good model for different assays. Red blood cells (RBCs) plasma membrane is a multi-component structure that keeps the cell morphology, elasticity, flexibility and deformability. Alteration of membrane structure upon exposure to xenobiotics could induce various cellular abnormalities and releasing of intracellular components. Therefore the morphological changes and extracellular release of haemoglobin [hemolysis] and increased content of extracellular adenosine triphosphate (ATP) [as signs of membrane stability] could be used to evaluate the cytotoxic effects of various molecules. The nucleated RBCs from birds, fish and amphibians can be used to evaluate genotoxicity of different xenobiotics using comet, DNA fragmentation and micronucleus assays. The RBCs could undergo programmed cell death (eryptosis) in response to injury providing a useful model to analyze some mechanisms of toxicity that could be implicated in apoptosis of nucleated cells. Erythrocytes are vulnerable to peroxidation making it a good biological membrane model for analyzing the oxidative stress and lipid peroxidation of various xenobiotics. The RBCs contain a large number of enzymatic and non-enzymatic antioxidants. The changes of the RBCs antioxidant capacity could reflect the capability of xenobiotics to generate reactive oxygen species (ROS) resulting in oxidative damage of tissue. These criteria make RBCs a valuable in vitro model to evaluate the cytotoxicity of different natural or synthetic and organic or inorganic molecules by cellular damage measures. Copyright © 2017. Published by Elsevier B.V.

  8. High school and college biology: A multi-level model of the effects of high school biology courses on student academic performance in introductory college biology courses

    Science.gov (United States)

    Loehr, John Francis

    The issue of student preparation for college study in science has been an ongoing concern for both college-bound students and educators of various levels. This study uses a national sample of college students enrolled in introductory biology courses to address the relationship between high school biology preparation and subsequent introductory college biology performance. Multi-Level Modeling was used to investigate the relationship between students' high school science and mathematics experiences and college biology performance. This analysis controls for student demographic and educational background factors along with factors associated with the college or university attended. The results indicated that high school course-taking and science instructional experiences have the largest impact on student achievement in the first introductory college biology course. In particular, enrollment in courses, such as high school Calculus and Advanced Placement (AP) Biology, along with biology course content that focuses on developing a deep understanding of the topics is found to be positively associated with student achievement in introductory college biology. On the other hand, experiencing high numbers of laboratory activities, demonstrations, and independent projects along with higher levels of laboratory freedom are associated with negative achievement. These findings are relevant to high school biology teachers, college students, their parents, and educators looking beyond the goal of high school graduation.

  9. [Kinetic model of enhanced biological phosphorus removal with mixed acetic and propionic acids as carbon sources. (I): Model constitution].

    Science.gov (United States)

    Zhang, Chao; Chen, Yin-Guang

    2013-03-01

    Based on activated sludge model No. 2 (ASM2), the anaerobic/aerobic kinetic model of phosphorus-accumulating organisms (PAO) was established with mixed short-chain fatty acids (SCFAs) as the base substance in enhanced biological phosphorus removal process. The characteristic of the PAO model was that the anaerobic metabolism rates of glycogen degradation, poly-beta-hydroxyalkanoates synthesis and polyphosphate hydrolysis were expressed by SCFAs uptake equation, and the effects of anaerobic maintenance on kinetics and stoichiometry were considered. The PAO kinetic model was composed of 3 soluble components, 4 particulate components and a pH parameter, which constituted the matrix of stoichiometric coefficients. On the basis of PAO model, the GAO kinetic model was established, which included 7 processes, and phosphorus content influenced the aerobic metabolism only.

  10. An novel frequent probability pattern mining algorithm based on circuit simulation method in uncertain biological networks

    Science.gov (United States)

    2014-01-01

    Background Motif mining has always been a hot research topic in bioinformatics. Most of current research on biological networks focuses on exact motif mining. However, due to the inevitable experimental error and noisy data, biological network data represented as the probability model could better reflect the authenticity and biological significance, therefore, it is more biological meaningful to discover probability motif in uncertain biological networks. One of the key steps in probability motif mining is frequent pattern discovery which is usually based on the possible world model having a relatively high computational complexity. Methods In this paper, we present a novel method for detecting frequent probability patterns based on circuit simulation in the uncertain biological networks. First, the partition based efficient search is applied to the non-tree like subgraph mining where the probability of occurrence in random networks is small. Then, an algorithm of probability isomorphic based on circuit simulation is proposed. The probability isomorphic combines the analysis of circuit topology structure with related physical properties of voltage in order to evaluate the probability isomorphism between probability subgraphs. The circuit simulation based probability isomorphic can avoid using traditional possible world model. Finally, based on the algorithm of probability subgraph isomorphism, two-step hierarchical clustering method is used to cluster subgraphs, and discover frequent probability patterns from the clusters. Results The experiment results on data sets of the Protein-Protein Interaction (PPI) networks and the transcriptional regulatory networks of E. coli and S. cerevisiae show that the proposed method can efficiently discover the frequent probability subgraphs. The discovered subgraphs in our study contain all probability motifs reported in the experiments published in other related papers. Conclusions The algorithm of probability graph isomorphism

  11. Models to Study NK Cell Biology and Possible Clinical Application.

    Science.gov (United States)

    Zamora, Anthony E; Grossenbacher, Steven K; Aguilar, Ethan G; Murphy, William J

    2015-08-03

    Natural killer (NK) cells are large granular lymphocytes of the innate immune system, responsible for direct targeting and killing of both virally infected and transformed cells. NK cells rapidly recognize and respond to abnormal cells in the absence of prior sensitization due to their wide array of germline-encoded inhibitory and activating receptors, which differs from the receptor diversity found in B and T lymphocytes that is due to the use of recombination-activation gene (RAG) enzymes. Although NK cells have traditionally been described as natural killers that provide a first line of defense prior to the induction of adaptive immunity, a more complex view of NK cells is beginning to emerge, indicating they may also function in various immunoregulatory roles and have the capacity to shape adaptive immune responses. With the growing appreciation for the diverse functions of NK cells, and recent technological advancements that allow for a more in-depth understanding of NK cell biology, we can now begin to explore new ways to manipulate NK cells to increase their clinical utility. In this overview unit, we introduce the reader to various aspects of NK cell biology by reviewing topics ranging from NK cell diversity and function, mouse models, and the roles of NK cells in health and disease, to potential clinical applications. © 2015 by John Wiley & Sons, Inc. Copyright © 2015 John Wiley & Sons, Inc.

  12. Experimental "evolutional machines": mathematical and experimental modeling of biological evolution

    Science.gov (United States)

    Brilkov, A. V.; Loginov, I. A.; Morozova, E. V.; Shuvaev, A. N.; Pechurkin, N. S.

    Experimentalists possess model systems of two major types for study of evolution continuous cultivation in the chemostat and long-term development in closed laboratory microecosystems with several trophic structure If evolutionary changes or transfer from one steady state to another in the result of changing qualitative properties of the system take place in such systems the main characteristics of these evolution steps can be measured By now this has not been realized from the point of view of methodology though a lot of data on the work of both types of evolutionary machines has been collected In our experiments with long-term continuous cultivation we used the bacterial strains containing in plasmids the cloned genes of bioluminescence and green fluorescent protein which expression level can be easily changed and controlled In spite of the apparent kinetic diversity of evolutionary transfers in two types of systems the general mechanisms characterizing the increase of used energy flow by populations of primer producent can be revealed at their study According to the energy approach at spontaneous transfer from one steady state to another e g in the process of microevolution competition or selection heat dissipation characterizing the rate of entropy growth should increase rather then decrease or maintain steady as usually believed The results of our observations of experimental evolution require further development of thermodynamic theory of open and closed biological systems and further study of general mechanisms of biological

  13. Micrasterias as a model system in plant cell biology

    Directory of Open Access Journals (Sweden)

    Ursula Luetz-Meindl

    2016-07-01

    Full Text Available The unicellular freshwater alga Micrasterias denticulata is an exceptional organism due to its extraordinary star-shaped, highly symmetric morphology and has thus attracted the interest of researchers for many decades. As a member of the Streptophyta, Micrasterias is not only genetically closely related to higher land plants but shares common features with them in many physiological and cell biological aspects. These facts, together with its considerable cell size of about 200 µm, its modest cultivation conditions and the uncomplicated accessibility particularly to any microscopic techniques, make Micrasterias a very well suited cell biological plant model system. The review focuses particularly on cell wall formation and composition, dictyosomal structure and function, cytoskeleton control of growth and morphogenesis as well as on ionic regulation and signal transduction. It has been also shown in the recent years that Micrasterias is a highly sensitive indicator for environmental stress impact such as heavy metals, high salinity, oxidative stress or starvation. Stress induced organelle degradation, autophagy, adaption and detoxification mechanisms have moved in the center of interest and have been investigated with modern microscopic techniques such as 3-D- and analytical electron microscopy as well as with biochemical, physiological and molecular approaches. This review is intended to summarize and discuss the most important results obtained in Micrasterias in the last 20 years and to compare the results to similar processes in higher plant cells.

  14. Phase-field theories for mathematical modeling of biological membranes.

    Science.gov (United States)

    Lázaro, Guillermo R; Pagonabarraga, Ignacio; Hernández-Machado, Aurora

    2015-01-01

    Biological membranes are complex structures whose mechanics are usually described at a mesoscopic level, such as the Helfrich bending theory. In this article, we present the phase-field methods, a useful tool for studying complex membrane problems which can be applied to very different phenomena. We start with an overview of the general theory of elasticity, paying special attention to its derivation from a molecular scale. We then study the particular case of membrane elasticity, explicitly obtaining the Helfrich bending energy. Within the framework of this theory, we derive a phase-field model for biological membranes and explore its physical basis and interpretation in terms of membrane elasticity. We finally explain three examples of applications of these methods to membrane related problems. First, the case of vesicle pearling and tubulation, when lipidic vesicles are exposed to the presence of hydrophobic polymers that anchor to the membrane, inducing a shape instability. Finally, we study the behavior of red blood cells while flowing in narrow microchannels, focusing on the importance of membrane elasticity to the cell flow capabilities. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  15. The SEEK: a platform for sharing data and models in systems biology.

    Science.gov (United States)

    Wolstencroft, Katy; Owen, Stuart; du Preez, Franco; Krebs, Olga; Mueller, Wolfgang; Goble, Carole; Snoep, Jacky L

    2011-01-01

    Systems biology research is typically performed by multidisciplinary groups of scientists, often in large consortia and in distributed locations. The data generated in these projects tend to be heterogeneous and often involves high-throughput "omics" analyses. Models are developed iteratively from data generated in the projects and from the literature. Consequently, there is a growing requirement for exchanging experimental data, mathematical models, and scientific protocols between consortium members and a necessity to record and share the outcomes of experiments and the links between data and models. The overall output of a research consortium is also a valuable commodity in its own right. The research and associated data and models should eventually be available to the whole community for reuse and future analysis. The SEEK is an open-source, Web-based platform designed for the management and exchange of systems biology data and models. The SEEK was originally developed for the SysMO (systems biology of microorganisms) consortia, but the principles and objectives are applicable to any systems biology project. The SEEK provides an index of consortium resources and acts as gateway to other tools and services commonly used in the community. For example, the model simulation tool, JWS Online, has been integrated into the SEEK, and a plug-in to PubMed allows publications to be linked to supporting data and author profiles in the SEEK. The SEEK is a pragmatic solution to data management which encourages, but does not force, researchers to share and disseminate their data to community standard formats. It provides tools to assist with management and annotation as well as incentives and added value for following these recommendations. Data exchange and reuse rely on sufficient annotation, consistent metadata descriptions, and the use of standard exchange formats for models, data, and the experiments they are derived from. In this chapter, we present the SEEK platform

  16. What is infidelity? Perceptions based on biological sex and personality

    Science.gov (United States)

    Thornton, Victoria; Nagurney, Alexander

    2011-01-01

    The study examines perceptions of infidelity, paying particular attention to how these perceptions differ based on biological sex and personality traits, specifically agency and communion and their unmitigated counterparts. The study utilizes a sample of 125 male and 233 female college students. In addition to the personality measures, participants completed a 19-item checklist that assessed their perceptions of specific items that could potentially be construed as infidelity. It was hypothesized that females would construe more items as infidelity than would males. It was also predicted that unmitigated communion and communion would be positively correlated with these perceptions and that unmitigated agency would be negatively correlated with these perceptions. No correlation was predicted between agency and infidelity. All hypotheses were supported. Implications and suggestions for future research are discussed. PMID:22114535

  17. What is infidelity? Perceptions based on biological sex and personality

    Directory of Open Access Journals (Sweden)

    Thornton V

    2011-05-01

    Full Text Available Victoria Thornton, Alexander NagurneyTexas State University – San Marcos, San Marcos, Texas, USAAbstract: The study examines perceptions of infidelity, paying particular attention to how these perceptions differ based on biological sex and personality traits, specifically agency and communion and their unmitigated counterparts. The study utilizes a sample of 125 male and 233 female college students. In addition to the personality measures, participants completed a 19-item checklist that assessed their perceptions of specific items that could potentially be construed as infidelity. It was hypothesized that females would construe more items as infidelity than would males. It was also predicted that unmitigated communion and communion would be positively correlated with these perceptions and that unmitigated agency would be negatively correlated with these perceptions. No correlation was predicted between agency and infidelity. All hypotheses were supported. Implications and suggestions for future research are discussed.Keywords: infidelity, communion, agency, questionnaire, relationship

  18. What is infidelity? Perceptions based on biological sex and personality.

    Science.gov (United States)

    Thornton, Victoria; Nagurney, Alexander

    2011-01-01

    The study examines perceptions of infidelity, paying particular attention to how these perceptions differ based on biological sex and personality traits, specifically agency and communion and their unmitigated counterparts. The study utilizes a sample of 125 male and 233 female college students. In addition to the personality measures, participants completed a 19-item checklist that assessed their perceptions of specific items that could potentially be construed as infidelity. It was hypothesized that females would construe more items as infidelity than would males. It was also predicted that unmitigated communion and communion would be positively correlated with these perceptions and that unmitigated agency would be negatively correlated with these perceptions. No correlation was predicted between agency and infidelity. All hypotheses were supported. Implications and suggestions for future research are discussed.

  19. Synthetic biology in cell-based cancer immunotherapy.

    Science.gov (United States)

    Chakravarti, Deboki; Wong, Wilson W

    2015-08-01

    The adoptive transfer of genetically engineered T cells with cancer-targeting receptors has shown tremendous promise for eradicating tumors in clinical trials. This form of cellular immunotherapy presents a unique opportunity to incorporate advanced systems and synthetic biology approaches to create cancer therapeutics with novel functions. We first review the development of synthetic receptors, switches, and circuits to control the location, duration, and strength of T cell activity against tumors. In addition, we discuss the cellular engineering and genome editing of host cells (or the chassis) to improve the efficacy of cell-based cancer therapeutics, and to reduce the time and cost of manufacturing. Copyright © 2015 Elsevier Ltd. All rights reserved.

  20. Theories and models on the Biology of Cells in Space

    Science.gov (United States)

    Todd, P.; Klaus, D. M.

    A wide variety of observations on cells in space, admittedly made under constraining and unnatural conditions in many cases, have led to experimental results that were surprising or unexpected. Reproducibility, freedom from artifacts, and plausibility must be considered in all cases, even when results are not surprising. The papers in the symposium on ``Theories and Models on the Biology of Cells in Space'' are dedicated to the subject of theplausibility of cellular responses to gravity -- inertial accelerations between 0 and 9.8 m/s^2 and higher. The mechanical phenomena inside the cell, the gravitactic locomotion of single eukaryotic and prokaryotic cells, and the effects of inertial unloading on cellular physiology are addressed in theoretical and experimental studies.

  1. Xenografted tissue models for the study of human endometrial biology.

    Science.gov (United States)

    Kuokkanen, Satu; Zhu, Liyin; Pollard, Jeffrey W

    The human endometrium undergoes extensive morphological, biochemical and molecular changes under the influence of female sex steroid hormones. Besides the fact that estrogen stimulates endometrial cell proliferation and progesterone inhibits this proliferation and induces differentiation, there is limited knowledge about precise molecular mechanisms underlying human endometrial biology. The importance of paracrine signaling in endometrial physiology explains why in vitro culture of endometrial cells has been challenging. Researchers, therefore, have developed alternative experimental in vivo models for the study of endometrial biology. The objective of this review is to summarize the recent developments and work on these in vivo endometrial research models. The in vivo recombinant tissue models in which wild-type endometrial cells are combined with endometrial cells from a gene-targeted mouse strain followed by xenografting to host mice have been critical in confirming the significance of paracrine signaling between the epithelium and stroma in the growth regulation of the endometrium. Additionally, these studies have uncovered differences between the mouse and human, emphasizing the need for the development of experimental models specifically of the human endometrium. Recently, xenotransplants of human endometrial fragments into the subcutaneous space of host mice and endometrial xenografts of dissociated and recombined epithelial and stromal cells beneath the kidney capsule of immunodeficient host mice have proven to be highly promising tools for in vivo research of endometrial functions. For the first time, the latter approach provides an immense opportunity for the application of genome engineering, such as targeted ablation of endometrial genes for example by using CRISPR/CAS9 system. This research will begin to elucidate the functional role of specific genes in this complex tissue. Another advantage of xenotransplantation and xenograft models of the human

  2. Monitoring and modeling of microbial and biological water quality

    Science.gov (United States)

    Microbial and biological water quality informs on the health of water systems and their suitability for uses in irrigation, recreation, aquaculture, and other activities. Indicators of microbial and biological water quality demonstrate high spatial and temporal variability. Therefore, monitoring str...

  3. A model of engineering materials inspired by biological tissues

    Directory of Open Access Journals (Sweden)

    Holeček M.

    2009-12-01

    Full Text Available The perfect ability of living tissues to control and adapt their mechanical properties to varying external conditions may be an inspiration for designing engineering materials. An interesting example is the smooth muscle tissue since this "material" is able to change its global mechanical properties considerably by a subtle mechanism within individual muscle cells. Multi-scale continuum models may be useful in designing essentially simpler engineering materials having similar properties. As an illustration we present the model of an incompressible material whose microscopic structure is formed by flexible, soft but incompressible balls connected mutually by linear springs. This simple model, however, shows a nontrivial nonlinear behavior caused by the incompressibility of balls and is very sensitive on some microscopic parameters. It may elucidate the way by which "small" changes in biopolymer networks within individual muscular cells may control the stiffness of the biological tissue, which outlines a way of designing similar engineering materials. The 'balls and springs' material presents also prestress-induced stiffening and allows elucidating a contribution of extracellular fluids into the tissue’s viscous properties.

  4. Modelling biological invasions: Individual to population scales at interfaces

    KAUST Repository

    Belmonte-Beitia, J.

    2013-10-01

    Extracting the population level behaviour of biological systems from that of the individual is critical in understanding dynamics across multiple scales and thus has been the subject of numerous investigations. Here, the influence of spatial heterogeneity in such contexts is explored for interfaces with a separation of the length scales characterising the individual and the interface, a situation that can arise in applications involving cellular modelling. As an illustrative example, we consider cell movement between white and grey matter in the brain which may be relevant in considering the invasive dynamics of glioma. We show that while one can safely neglect intrinsic noise, at least when considering glioma cell invasion, profound differences in population behaviours emerge in the presence of interfaces with only subtle alterations in the dynamics at the individual level. Transport driven by local cell sensing generates predictions of cell accumulations along interfaces where cell motility changes. This behaviour is not predicted with the commonly used Fickian diffusion transport model, but can be extracted from preliminary observations of specific cell lines in recent, novel, cryo-imaging. Consequently, these findings suggest a need to consider the impact of individual behaviour, spatial heterogeneity and especially interfaces in experimental and modelling frameworks of cellular dynamics, for instance in the characterisation of glioma cell motility. © 2013 Elsevier Ltd.

  5. A Best-Practice Model for Academic Advising of University Biology Majors

    Science.gov (United States)

    Heekin, Jonathan Ralph Calvin

    Biology faculty at an East Coast university believed their undergraduate students were not being well served by the existing academic advising program. The purpose of this mixed methods project study was to evaluate the effectiveness of the academic advising model in a biology department. Guided by system-based organizational theory, a learning organization model, and holistic theory emphasizing an individual's journey of academic and personal growth, an online survey, student focus groups, and faculty interviews were used to collect data, which developed recommendations for improving undergraduate academic advising in the biology department. Using Survey Monkey, 35 surveys were returned. Frequency tables, ANOVAs, and t tests produced the results of the survey. The results of the ANOVAs and t tests indicated statically significant differences (p focus groups. The results from the interviews and focus groups indicated that the role of mentor should remain at the faculty level, guiding students in what they can do with their degrees and discussing options that students may not have considered. The proposed model for academic advising may improve student success rates for undergraduates enrolled in the biology department at the current institution, as well as in science-oriented programs at other institutions, by providing better guidance to those who serve them in academic advising.

  6. Modeling Cancer Metastasis using Global, Quantitative and Integrative Network Biology

    DEFF Research Database (Denmark)

    Schoof, Erwin; Erler, Janine

    computational analysis, it is possible to gain a better understanding of colorectal cancer metastasis, and obtain potential clinical benefits. Chapter IV briefly summarizes the findings of the thesis and closes by proposing some future directions based on the work that was presented. Overall, the thesis aims...... a particular tumor, but also the phenotypic response to perturbations. Thus, there is a critical need for an integrative global approach, which assesses a biological system such as cancer from several molecular aspects in an un-biased fashion. This thesis summarizes the efforts that were undertaken as part...... of my PhD in an attempt to positively contribute to this fundamental challenge. The thesis is divided into four parts. In Chapter I, we introduce the complexity of cancer, and describe some underlying causes and ways to study the disease from different molecular perspectives. There is a nearly infinite...

  7. First Steps in Computational Systems Biology: A Practical Session in Metabolic Modeling and Simulation

    Science.gov (United States)

    Reyes-Palomares, Armando; Sanchez-Jimenez, Francisca; Medina, Miguel Angel

    2009-01-01

    A comprehensive understanding of biological functions requires new systemic perspectives, such as those provided by systems biology. Systems biology approaches are hypothesis-driven and involve iterative rounds of model building, prediction, experimentation, model refinement, and development. Developments in computer science are allowing for ever…

  8. Event-Based Conceptual Modeling

    DEFF Research Database (Denmark)

    Bækgaard, Lars

    The paper demonstrates that a wide variety of event-based modeling approaches are based on special cases of the same general event concept, and that the general event concept can be used to unify the otherwise unrelated fields of information modeling and process modeling. A set of event-based mod......The paper demonstrates that a wide variety of event-based modeling approaches are based on special cases of the same general event concept, and that the general event concept can be used to unify the otherwise unrelated fields of information modeling and process modeling. A set of event......-based modeling approaches are analyzed and the results are used to formulate a general event concept that can be used for unifying the seemingly unrelated event concepts. Events are characterized as short-duration processes that have participants, consequences, and properties, and that may be modeled in terms...

  9. Patient Preference for Dosing Frequency Based on Prior Biologic Experience.

    Science.gov (United States)

    Zhang, Mingliang; Carter, Chureen; Olson, William H; Johnson, Michael P; Brennem, Susan K; Lee, Seina; Farahi, Kamyar

    2017-03-01

    There is limited research exploring patient preferences regarding dosing frequency of biologic treatment of psoriasis. Patients with moderate-to-severe plaque psoriasis identified in a healthcare claims database completed a survey regarding experience with psoriasis treatments and preferred dosing frequency. Survey questions regarding preferences were posed in two ways: (1) by likelihood of choosing once per week or 2 weeks, or 12 weeks; and (2) by choosing one option among once every 1-2 or 3-4 weeks or 1-2 or 2-3 months. Data were analyzed by prior biologic history (biologic-experienced vs biologic-naïve, and with one or two specific biologics). Overall, 426 patients completed the survey: 163 biologic-naïve patients and 263 biologic-experienced patients (159 had some experience with etanercept, 105 with adalimumab, and 49 with ustekinumab). Among patients who indicated experience with one or two biologics, data were available for 219 (30 with three biologics and 14 did not specify which biologic experience). The majority of biologic-naïve (68.8%) and overall biologic-experienced (69.4%) patients indicated that they were very likely to choose the least frequent dosing option of once every 12 weeks (Table 1). In contrast, fewer biologic-naïve (9.1% and 16.7%) and biologic-experienced (22.5% and 25.3%) patients indicated that they were very likely to choose the 1-week and 2-week dosing interval options, respectively. In each cohort grouped by experience with specific biologics, among those with no experience with ustekinumab, the most chosen option was 1-2 weeks. The most frequently chosen option was every 2-3 months, among patients with any experience with ustekinumab, regardless of their experience with other biologics. The least frequent dosing interval was preferred among biologic naïve patients and patients who had any experience with ustekinumab. Dosing interval may influence the shared decision-making process for psoriasis treatment with biologics. J

  10. Biological Detection System Technologies Technology and Industrial Base Study. A Primer on Biological Detection Technologies

    National Research Council Canada - National Science Library

    2001-01-01

    .... and Canadian military personnel. In light of these concerns both defense departments have increased efforts to develop and field biological agent detection systems to help protect their military forces and fixed assets...

  11. Teaching the Big Ideas of Biology with Operon Models

    Science.gov (United States)

    Cooper, Robert A.

    2015-01-01

    This paper presents an activity that engages students in model-based reasoning, requiring them to predict the behavior of the trp and lac operons under different environmental conditions. Students are presented six scenarios for the "trp" operon and five for the "lac" operon. In most of the scenarios, specific mutations have…

  12. Facilitating problem based learning in an online biology laboratory course

    Science.gov (United States)

    Wesolowski, Meredith C.

    Online instruction offers many benefits to underserved populations in higher education, particularly increased access. However, incorporation of preferred pedagogical methods, particularly those involving student collaboration, can be more difficult to facilitate in online courses due to geographic separation. In the area of laboratory science education, there is a strong argument for use of constructivist, collaborative pedagogy to promote many facets of student learning. This EPP describes the process used to develop two problem based learning (PBL) laboratory activities based on recommendations found in the literature, their incorporation into an online biology laboratory science course (BIO101) and their impact on student achievement and critical thinking skills. Data analysis revealed a high level of achievement within the study semester. In addition, use of synchronous group discussions as part of the PBL framework resulted in a broad range of discussions reflective of successful problem solving interactions described in the literature. Together, these suggest a observed benefit from incorporation of PBL in this online course. In addition, specific areas for modification were identified as potential future improvements.

  13. Behavior of lyophilized biological valves in a chronic animal model.

    Science.gov (United States)

    Maizato, Marina J S; Taniguchi, Fabio P; Ambar, Rafael F; Pitombo, Ronaldo N M; Leirner, Adolfo A; Cestari, Idágene A; Stolf, Noedir A G

    2013-11-01

    Glutaraldehyde is used in order to improve the mechanical and immunogenic properties of biological tissues, such as bovine pericardium membranes, used to manufacture heart valve bioprostheses. Lyophilization, also known as freeze-drying, preserves biological material without damage by freezing the water content and removing ice by sublimation. Through this process, dehydrated products of high quality may be obtained; also, the material may be easily handled. The lyophilization process reduces aldehyde residues in biological tissue previously treated with glutaraldehyde, thus promoting reduction of cytotoxicity, increasing resistance to inflammation, and possibly decreasing the potential for tissue calcification. The objective of this study was to chronically evaluate the calcification of bovine pericardium heart valve prostheses, previously lyophilized or not, in an animal model. Six-month-old sheep received implants of lyophilized and unlyophilized heart valve prostheses in the pulmonary position with right bypass. The study followed 16 animals for a period of 90 days. Right ventricle-pulmonary artery (RV/PA) transvalvular pressure gradient was evaluated before and immediately after implantation and before explantation, as were tissue calcium, inflammation intensity, and thrombosis and pannus formation. The t-test was used for statistical analysis. Twelve animals survived to the end of the experiment, but one of the animals in the control group had endocarditis and was excluded from the data. Four animals died early. The mean RV/PA gradient on implantation was 2.0 ± 1.6 mm Hg in the control group and 6.2 ± 4.1 mm Hg in the lyophilized group (P = 0.064). This mean gradient increased at explantation to 7.7 ± 3.9 mm Hg and 8.6 ± 5.8 mm Hg, respectively (P = 0.777). The average calcium content in the tissue leaflets after 3 months was 21.6 ± 39.1 mg Ca(2+)/g dry weight in the control group, compared with an average content of 41.2 ± 46.9 mg Ca(2+)/g dry weight

  14. The philosophy of modelling or does the philosophy of biology have any use?

    Science.gov (United States)

    Orzack, Steven Hecht

    2012-01-19

    Biologists in search of answers to real-world issues such as the ecological consequences of global warming, the design of species' conservation plans, understanding landscape dynamics and understanding gene expression make decisions constantly that are based on a 'philosophical' stance as to how to create and test explanations of an observed phenomenon. For better or for worse, some kind of philosophy is an integral part of the doing of biology. Given this, it is more important than ever to undertake a practical assessment of what philosophy does mean and should mean to biologists. Here, I address three questions: should biologists pay any attention to 'philosophy'; should biologists pay any attention to 'philosophy of biology'; and should biologists pay any attention to the philosophy of biology literature on modelling? I describe why the last question is easily answered affirmatively, with the proviso that the practical benefits to be gained by biologists from this literature will be directly proportional to the extent to which biologists understand 'philosophy' to be a part of biology, not apart from biology.

  15. In vivo biological effects of stereotactic radiosurgery: A primate model

    Energy Technology Data Exchange (ETDEWEB)

    Lunsford, L.D.; Altschuler, E.M.; Flickinger, J.C.; Wu, A.; Martinez, A.J. (Univ. of Pittsburgh School of Medicine, PA (USA))

    1990-09-01

    Single-fraction, closed skull, small-volume irradiation (radiosurgery) of intact intracranial structures requires accurate knowledge of radiation tolerance. We have developed a baboon model to assess the in vivo destructive radiobiological effects of stereotactic radiosurgery. Three baboons received a single-fraction, 150-Gy lesion of the caudate nucleus, the thalamus, or the pons using the 8-mm diameter collimator of the gamma unit. Serial standard neurodiagnostic tests (neurological examination, computed tomographic scan, magnetic resonance imaging, stable xenon-enhanced computed tomographic scan of cerebral blood flow, somatosensory and brain stem evoked potentials, and myelin basic protein levels of cerebrospinal fluid) were compared with preoperative studies. Magnetic resonance imaging revealed the development of a lesion at the target site between 45 and 60 days after irradiation. Deterioration of the brain stem evoked potentials preceded imaging changes when the lesion encroached on auditory pathways. Myelin basic protein levels increased subsequent to imaging changes. Postmortem neuropathological examination confirmed a well-demarcated radionecrosis of the target volume. The baboon model appears to be an excellent method to study the in vivo biological effects of radiosurgery.

  16. CSML2SBML: a novel tool for converting quantitative biological pathway models from CSML into SBML.

    Science.gov (United States)

    Li, Chen; Nagasaki, Masao; Ikeda, Emi; Sekiya, Yayoi; Miyano, Satoru

    2014-07-01

    CSML and SBML are XML-based model definition standards which are developed with the aim of creating exchange formats for modeling, visualizing and simulating biological pathways. In this article we report a release of a format convertor for quantitative pathway models, namely CSML2SBML. It translates models encoded by CSML into SBML without loss of structural and kinetic information. The simulation and parameter estimation of the resulting SBML model can be carried out with compliant tool CellDesigner for further analysis. The convertor is based on the standards CSML version 3.0 and SBML Level 2 Version 4. In our experiments, 11 out of 15 pathway models in CSML model repository and 228 models in Macrophage Pathway Knowledgebase (MACPAK) are successfully converted to SBML models. The consistency of the resulting model is validated by libSBML Consistency Check of CellDesigner. Furthermore, the converted SBML model assigned with the kinetic parameters translated from CSML model can reproduce the same dynamics with CellDesigner as CSML one running on Cell Illustrator. CSML2SBML, along with its instructions and examples for use are available at http://csml2sbml.csml.org. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  17. The Implementation of Research-based Learning on Biology Seminar Course in Biology Education Study Program of FKIP UMRAH

    Science.gov (United States)

    Amelia, T.

    2018-04-01

    Biology Seminar is a course in Biology Education Study Program of Faculty of Teacher Training and Education University of Maritim Raja Ali Haji (FKIP UMRAH) that requires students to have the ability to apply scientific attitudes, perform scientific writing and undertake scientific publications on a small scale. One of the learning strategies that can drive the achievement of learning outcomes in this course is Research-Based Learning. Research-Based Learning principles are considered in accordance with learning outcomes in Biology Seminar courses and generally in accordance with the purpose of higher education. On this basis, this article which is derived from a qualitative research aims at describing Research-based Learning on Biology Seminar course. Based on a case study research, it was known that Research-Based Learning on Biology Seminar courses is applied through: designing learning activities around contemporary research issues; teaching research methods, techniques and skills explicitly within program; drawing on personal research in designing and teaching courses; building small-scale research activities into undergraduate assignment; and infusing teaching with the values of researchers.

  18. Biologically Inspired Model for Visual Cognition Achieving Unsupervised Episodic and Semantic Feature Learning.

    Science.gov (United States)

    Qiao, Hong; Li, Yinlin; Li, Fengfu; Xi, Xuanyang; Wu, Wei

    2016-10-01

    Recently, many biologically inspired visual computational models have been proposed. The design of these models follows the related biological mechanisms and structures, and these models provide new solutions for visual recognition tasks. In this paper, based on the recent biological evidence, we propose a framework to mimic the active and dynamic learning and recognition process of the primate visual cortex. From principle point of view, the main contributions are that the framework can achieve unsupervised learning of episodic features (including key components and their spatial relations) and semantic features (semantic descriptions of the key components), which support higher level cognition of an object. From performance point of view, the advantages of the framework are as follows: 1) learning episodic features without supervision-for a class of objects without a prior knowledge, the key components, their spatial relations and cover regions can be learned automatically through a deep neural network (DNN); 2) learning semantic features based on episodic features-within the cover regions of the key components, the semantic geometrical values of these components can be computed based on contour detection; 3) forming the general knowledge of a class of objects-the general knowledge of a class of objects can be formed, mainly including the key components, their spatial relations and average semantic values, which is a concise description of the class; and 4) achieving higher level cognition and dynamic updating-for a test image, the model can achieve classification and subclass semantic descriptions. And the test samples with high confidence are selected to dynamically update the whole model. Experiments are conducted on face images, and a good performance is achieved in each layer of the DNN and the semantic description learning process. Furthermore, the model can be generalized to recognition tasks of other objects with learning ability.

  19. ADDITION TO THE QUASI-BIOLOGICAL MODEL OF RADIOGENIC CANCER MORBIDITY

    Directory of Open Access Journals (Sweden)

    A. Т. Gubin

    2017-01-01

    Full Text Available Object: The purpose was to refine the quasi-biological model of the incidence of radiogenic solid cancer (published by the authors earlier in the journal “Radiation hygiene” to ensure better consistency with the Japanese cohort data and with the ICRP model in part of the description of the effect of age at exposure.Results: Initial presuppositions of a mathematical model was supplemented by the assumption that stem cells, received the “pre-cancerous” defect of DNA, with a higher probability compared to the intact cells follow the path of reproduction but not of differentiation. Structure of the refined model and its properties did not change, but one parameter was added. Analysis of the base mathematical relations of the supplemented model showed that there was no contradiction between the models of radiogenic cancer incidence presented in the Publication 103 ICRP and in the UNSCEAR 2006, despite their external differences.Conclusion: Further work with the model requires the verification of parameter values by comparison with the epidemiological data, primarily with data on the incidence of solid cancers in the Japanese cohort. However, since some of the assumptions of the model, including the new one, are not purely radiobiological, it would require analysis of a wider range of biological and cancer patterns.

  20. The Role of Stochastic Models in Interpreting the Origins of Biological Chirality

    Directory of Open Access Journals (Sweden)

    Gábor Lente

    2010-04-01

    Full Text Available This review summarizes recent stochastic modeling efforts in the theoretical research aimed at interpreting the origins of biological chirality. Stochastic kinetic models, especially those based on the continuous time discrete state approach, have great potential in modeling absolute asymmetric reactions, experimental examples of which have been reported in the past decade. An overview of the relevant mathematical background is given and several examples are presented to show how the significant numerical problems characteristic of the use of stochastic models can be overcome by non-trivial, but elementary algebra. In these stochastic models, a particulate view of matter is used rather than the concentration-based view of traditional chemical kinetics using continuous functions to describe the properties system. This has the advantage of giving adequate description of single-molecule events, which were probably important in the origin of biological chirality. The presented models can interpret and predict the random distribution of enantiomeric excess among repetitive experiments, which is the most striking feature of absolute asymmetric reactions. It is argued that the use of the stochastic kinetic approach should be much more widespread in the relevant literature.

  1. Organization of a radioisotope based molecular biology laboratory

    International Nuclear Information System (INIS)

    2006-12-01

    Polymerase chain reaction (PCR) has revolutionized the application of molecular techniques to medicine. Together with other molecular biology techniques it is being increasingly applied to human health for identifying prognostic markers and drug resistant profiles, developing diagnostic tests and genotyping systems and for treatment follow-up of certain diseases in developed countries. Developing Member States have expressed their need to also benefit from the dissemination of molecular advances. The use of radioisotopes, as a step in the detection process or for increased sensitivity and specificity is well established, making it ideally suitable for technology transfer. Many molecular based projects using isotopes for detecting and studying micro organisms, hereditary and neoplastic diseases are received for approval every year. In keeping with the IAEA's programme, several training activities and seminars have been organized to enhance the capabilities of developing Member States to employ in vitro nuclear medicine technologies for managing their important health problems and for undertaking related basic and clinical research. The background material for this publication was collected at training activities and from feedback received from participants at research and coordination meetings. In addition, a consultants' meeting was held in June 2004 to compile the first draft of this report. Previous IAEA TECDOCS, namely IAEA-TECDOC-748 and IAEA-TECDOC-1001, focused on molecular techniques and their application to medicine while the present publication provides information on organization of the laboratory, quality assurance and radio-safety. The technology has specific requirements of the way the laboratory is organized (e.g. for avoiding contamination and false positives in PCR) and of quality assurance in order to provide accurate information to decision makers. In addition while users of the technology accept the scientific rationale of using radio

  2. Modelling of biological nitrogen removal during treatment of piggery wastewater.

    Science.gov (United States)

    Béline, F; Boursier, H; Guiziou, F; Paul, E

    2007-01-01

    During this study, a mathematical model simulating piggery wastewater treatment was developed, with the objective of process optimisation. To achieve this, the effect of temperature and free ammonia concentration on the nitrification rate were experimentally studied using respirometry. The maximum growth rates obtained were higher for ammonium-oxidising biomass than for nitrite-oxidising biomass for the temperatures above 20 degrees C; values at 35 degrees C were equal to 1.9 and 1.35 day(-1), respectively. No inhibition of nitrification was observed for free ammonia concentrations up to 50 mgN/L. Using these data with others experimental data obtained from a pilot-scale reactor to treat piggery wastewater, a model based on a modified version of the ASM1 was developed and calibrated. In order to model the nitrite accumulation observed, the ASM1 model was extended with a two-step nitrification and denitrification including nitrite as intermediate. Finally, the produced model called PiWaT1 demonstrated a good fit with the experimental data. In addition to the temperature, oxygen concentration was identified as an important factor influencing the nitrite accumulation during nitrification. Even if some improvements of the model are still necessary, this model can already be used for process improvement.

  3. Spatial succession modeling of biological communities: a multi-model approach.

    Science.gov (United States)

    Zhang, WenJun; Wei, Wu

    2009-11-01

    Strong spatial correlation may exist in the spatial succession of biological communities, and the spatial succession can be mathematically described. It was confirmed by our study on spatial succession of both plant and arthropod communities along a linear transect of natural grassland. Both auto-correlation and cross-correlation analyses revealed that the succession of plant and arthropod communities exhibited a significant spatial correlation, and the spatial correlation for plant community succession was stronger than arthropod community succession. Theoretically it should be reasonable to infer a site's community composition from the last site in the linear transect. An artificial neural network for state space modeling (ANNSSM) was developed in present study. An algorithm (i.e., Importance Detection Method (IDM)) for determining the relative importance of input variables was proposed. The relative importance for plant families Gramineae, Compositae and Leguminosae, and arthropod orders Homoptera, Diptera and Orthoptera, were detected and analyzed using IDM. ANNSSM performed better than multivariate linear regression and ordinary differential equation, while ordinary differential equation exhibited the worst performance in the simulation and prediction of spatial succession of biological communities. A state transition probability model (STPM) was proposed to simulate the state transition process of biological communities. STPM performed better than multinomial logistic regression in the state transition modeling. We suggested a novel multi-model framework, i.e., the joint use of ANNSSM and STPM, to predict the spatial succession of biological communities. In this framework, ANNSSM and STPM can be separately used to simulate the continuous and discrete dynamics.

  4. MODELLING OF RADIONUCLIDE MIGRATION IN THE SYSTEM OF NUCLEAR POWER PLANT BIOLOGICAL PONDS

    Directory of Open Access Journals (Sweden)

    Ю. Кутлахмедов

    2011-04-01

    Full Text Available Migration of radionuclide coming from nuclear power plant into the system of biological pondsand then into the water reservoir-cooler is considered in the article. The theme of the work ismodeling of radionuclide migration process in the system of biological ponds on the example of thePivdennoukrainska nuclear power plant using chamber models method. Typical water ecosystemconsisting of three chambers (chamber-water, chamber-biota and chamber-bed silt was the basistaken by the authors. Application of chamber models method allowed authors to develop thedynamic chamber model of radionuclide migration in nuclear power plant biological ponds. Thismodel allows to forecast values and dynamics of radioactive water pollution based on limitedecosystem monitoring data. Thus, parameters of radioactive capacity of nuclear power plantbiological ponds system and water reservoir-cooler were modeled by authors, the estimation andprognosis of radionuclide distribution and accumulation in the system of nuclear power plantbiological ponds were done. Authors also explain the roles of basin water, biomass and bed silt inradionuclide deposition

  5. A Transformative Model for Undergraduate Quantitative Biology Education

    OpenAIRE

    Usher, David C.; Driscoll, Tobin A.; Dhurjati, Prasad; Pelesko, John A.; Rossi, Louis F.; Schleiniger, Gilberto; Pusecker, Kathleen; White, Harold B.

    2010-01-01

    The BIO2010 report recommended that students in the life sciences receive a more rigorous education in mathematics and physical sciences. The University of Delaware approached this problem by (1) developing a bio-calculus section of a standard calculus course, (2) embedding quantitative activities into existing biology courses, and (3) creating a new interdisciplinary major, quantitative biology, designed for students interested in solving complex biological problems using advanced mathematic...

  6. Integrated Ecological River Health Assessments, Based on Water Chemistry, Physical Habitat Quality and Biological Integrity

    Directory of Open Access Journals (Sweden)

    Ji Yoon Kim

    2015-11-01

    Full Text Available This study evaluated integrative river ecosystem health using stressor-based models of physical habitat health, chemical water health, and biological health of fish and identified multiple-stressor indicators influencing the ecosystem health. Integrated health responses (IHRs, based on star-plot approach, were calculated from qualitative habitat evaluation index (QHEI, nutrient pollution index (NPI, and index of biological integrity (IBI in four different longitudinal regions (Groups I–IV. For the calculations of IHRs values, multi-metric QHEI, NPI, and IBI models were developed and their criteria for the diagnosis of the health were determined. The longitudinal patterns of the river were analyzed by a self-organizing map (SOM model and the key major stressors in the river were identified by principal component analysis (PCA. Our model scores of integrated health responses (IHRs suggested that mid-stream and downstream regions were impaired, and the key stressors were closely associated with nutrient enrichment (N and P and organic matter pollutions from domestic wastewater disposal plants and urban sewage. This modeling approach of IHRs may be used as an effective tool for evaluations of integrative ecological river health..

  7. Model-based Software Engineering

    DEFF Research Database (Denmark)

    Kindler, Ekkart

    2010-01-01

    The vision of model-based software engineering is to make models the main focus of software development and to automatically generate software from these models. Part of that idea works already today. But, there are still difficulties when it comes to behaviour. Actually, there is no lack in models...

  8. The AGBNP implicit solvent model: recent advances and applications to biological macromolecules

    Science.gov (United States)

    Gallicchio, Emilio

    2008-03-01

    The Analytical Generalized Born plus Non-Polar (AGBNP) model is an analytical implicit water model suitable for molecular dynamics simulations of small molecules and macromolecules. It is based on an analytical pairwise descreening implementation of the continuum dielectric Generalized Born (GB) model and a non-polar hydration free energy model. AGBNP computes the descreening scaling factors that account for atomic overlaps from the geometry of the solute rather than treating them as geometry-independent parameters fit to numerical or experimental data. The non-polar hydration free energy model is decomposed into a cavity component based on the solute surface area and a solute-solvent van der Waals dispersion energy estimator. The aim of the model is to achieve atomic-resolution accuracy for modelling the many biological systems in which global conformational features are regulated by small and localized control elements. Since its introduction AGBNP has been employed to study a variety of biological problems ranging from peptide conformational propensity and folding, protein allostery, conformational equilibria of protein-ligand complexes, binding affinity prediction, and, more recently, to intrinsically disordered proteins, protein aggregation, the design of virus vaccine carriers, and macromolecular X-ray structure refinement. Recent development work has focused on computational performance enhancements and on improving the accuracy of the model with respect to explicit solvent simulation results. By comparing the details of the solvent potentials of mean force of several peptides calculated with explicit and implicit solvation, we have identified some aspects of the AGBNP model in need of improvement. We are exploring several strategies to address them including the adoption of a molecular surface description of the solute volume, the modelling of high-occupancy hydration sites, and the optimization of the non-polar free energy model.

  9. On the Modelling of Biological Patterns with Mechanochemical Models: Insights from Analysis and Computation

    KAUST Repository

    Moreo, P.

    2009-11-14

    The diversity of biological form is generated by a relatively small number of underlying mechanisms. Consequently, mathematical and computational modelling can, and does, provide insight into how cellular level interactions ultimately give rise to higher level structure. Given cells respond to mechanical stimuli, it is therefore important to consider the effects of these responses within biological self-organisation models. Here, we consider the self-organisation properties of a mechanochemical model previously developed by three of the authors in Acta Biomater. 4, 613-621 (2008), which is capable of reproducing the behaviour of a population of cells cultured on an elastic substrate in response to a variety of stimuli. In particular, we examine the conditions under which stable spatial patterns can emerge with this model, focusing on the influence of mechanical stimuli and the interplay of non-local phenomena. To this end, we have performed a linear stability analysis and numerical simulations based on a mixed finite element formulation, which have allowed us to study the dynamical behaviour of the system in terms of the qualitative shape of the dispersion relation. We show that the consideration of mechanotaxis, namely changes in migration speeds and directions in response to mechanical stimuli alters the conditions for pattern formation in a singular manner. Furthermore without non-local effects, responses to mechanical stimuli are observed to result in dispersion relations with positive growth rates at arbitrarily large wavenumbers, in turn yielding heterogeneity at the cellular level in model predictions. This highlights the sensitivity and necessity of non-local effects in mechanically influenced biological pattern formation models and the ultimate failure of the continuum approximation in their absence. © 2009 Society for Mathematical Biology.

  10. Combining Genetic Circuit and Microbial Growth Kinetic Models: A Challenge for Biological Modelling

    NARCIS (Netherlands)

    Koutinas, M.; Kiparissides, A.; Lam, M.C.; Silva-Rocha, R.; Lorenzo, de V.; Martins Dos Santos, V.A.P.; Pistikopoulos, E.N.; Mantalaris, A.

    2010-01-01

    A modelling framework that consists of model building, validation and analysis, leading to model-based design of experiments and to the application of optimisation-based model-predictive control strategies for the development of optimised bioprocesses is presented. An example of this framework is

  11. Supporting High School Student Accomplishment of Biology Content Using Interactive Computer-Based Curricular Case Studies

    Science.gov (United States)

    Oliver, Joseph Steve; Hodges, Georgia W.; Moore, James N.; Cohen, Allan; Jang, Yoonsun; Brown, Scott A.; Kwon, Kyung A.; Jeong, Sophia; Raven, Sara P.; Jurkiewicz, Melissa; Robertson, Tom P.

    2017-11-01

    Research into the efficacy of modules featuring dynamic visualizations, case studies, and interactive learning environments is reported here. This quasi-experimental 2-year study examined the implementation of three interactive computer-based instructional modules within a curricular unit covering cellular biology concepts in an introductory high school biology course. The modules featured dynamic visualizations and focused on three processes that underlie much of cellular biology: diffusion, osmosis, and filtration. Pre-tests and post-tests were used to assess knowledge growth across the unit. A mixture Rasch model analysis of the post-test data revealed two groups of students. In both years of the study, a large proportion of the students were classified as low-achieving based on their pre-test scores. The use of the modules in the Cell Unit in year 2 was associated with a much larger proportion of the students having transitioned to the high-achieving group than in year 1. In year 2, the same teachers taught the same concepts as year 1 but incorporated the interactive computer-based modules into the cell biology unit of the curriculum. In year 2, 67% of students initially classified as low-achieving were classified as high-achieving at the end of the unit. Examination of responses to assessments embedded within the modules as well as post-test items linked transition to the high-achieving group with correct responses to items that both referenced the visualization and the contextualization of that visualization within the module. This study points to the importance of dynamic visualization within contextualized case studies as a means to support student knowledge acquisition in biology.

  12. Principles of models based engineering

    Energy Technology Data Exchange (ETDEWEB)

    Dolin, R.M.; Hefele, J.

    1996-11-01

    This report describes a Models Based Engineering (MBE) philosophy and implementation strategy that has been developed at Los Alamos National Laboratory`s Center for Advanced Engineering Technology. A major theme in this discussion is that models based engineering is an information management technology enabling the development of information driven engineering. Unlike other information management technologies, models based engineering encompasses the breadth of engineering information, from design intent through product definition to consumer application.

  13. ARM-Cortex M3-Based Two-Wheel Robot for Assessing Grid Cell Model of Medial Entorhinal Cortex: Progress towards Building Robots with Biologically Inspired Navigation-Cognitive Maps

    Directory of Open Access Journals (Sweden)

    J. Cuneo

    2017-01-01

    Full Text Available This article presents the implementation and use of a two-wheel autonomous robot and its effectiveness as a tool for studying the recently discovered use of grid cells as part of mammalian’s brains space-mapping circuitry (specifically the medial entorhinal cortex. A proposed discrete-time algorithm that emulates the medial entorhinal cortex is programed into the robot. The robot freely explores a limited laboratory area in the manner of a rat or mouse and reports information to a PC, thus enabling research without the use of live individuals. Position coordinate neural maps are achieved as mathematically predicted although for a reduced number of implemented neurons (i.e., 200 neurons. However, this type of computational embedded system (robot’s microcontroller is found to be insufficient for simulating huge numbers of neurons in real time (as in the medial entorhinal cortex. It is considered that the results of this work provide an insight into achieving an enhanced embedded systems design for emulating and understanding mathematical neural network models to be used as biologically inspired navigation system for robots.

  14. Predictive Modeling of Influenza Shows the Promise of Applied Evolutionary Biology.

    Science.gov (United States)

    Morris, Dylan H; Gostic, Katelyn M; Pompei, Simone; Bedford, Trevor; Łuksza, Marta; Neher, Richard A; Grenfell, Bryan T; Lässig, Michael; McCauley, John W

    2018-02-01

    Seasonal influenza is controlled through vaccination campaigns. Evolution of influenza virus antigens means that vaccines must be updated to match novel strains, and vaccine effectiveness depends on the ability of scientists to predict nearly a year in advance which influenza variants will dominate in upcoming seasons. In this review, we highlight a promising new surveillance tool: predictive models. Based on data-sharing and close collaboration between the World Health Organization and academic scientists, these models use surveillance data to make quantitative predictions regarding influenza evolution. Predictive models demonstrate the potential of applied evolutionary biology to improve public health and disease control. We review the state of influenza predictive modeling and discuss next steps and recommendations to ensure that these models deliver upon their considerable biomedical promise. Copyright © 2017 Elsevier Ltd. All rights reserved.

  15. Panel 4: Recent Advances in Otitis Media in Molecular Biology, Biochemistry, Genetics, and Animal Models

    Science.gov (United States)

    Li, Jian-Dong; Hermansson, Ann; Ryan, Allen F.; Bakaletz, Lauren O.; Brown, Steve D.; Cheeseman, Michael T.; Juhn, Steven K.; Jung, Timothy T. K.; Lim, David J.; Lim, Jae Hyang; Lin, Jizhen; Moon, Sung-Kyun; Post, J. Christopher

    2014-01-01

    Background Otitis media (OM) is the most common childhood bacterial infection and also the leading cause of conductive hearing loss in children. Currently, there is an urgent need for developing novel therapeutic agents for treating OM based on full understanding of molecular pathogenesis in the areas of molecular biology, biochemistry, genetics, and animal model studies in OM. Objective To provide a state-of-the-art review concerning recent advances in OM in the areas of molecular biology, biochemistry, genetics, and animal model studies and to discuss the future directions of OM studies in these areas. Data Sources and Review Methods A structured search of the current literature (since June 2007). The authors searched PubMed for published literature in the areas of molecular biology, biochemistry, genetics, and animal model studies in OM. Results Over the past 4 years, significant progress has been made in the areas of molecular biology, biochemistry, genetics, and animal model studies in OM. These studies brought new insights into our understanding of the molecular and biochemical mechanisms underlying the molecular pathogenesis of OM and helped identify novel therapeutic targets for OM. Conclusions and Implications for Practice Our understanding of the molecular pathogenesis of OM has been significantly advanced, particularly in the areas of inflammation, innate immunity, mucus overproduction, mucosal hyperplasia, middle ear and inner ear interaction, genetics, genome sequencing, and animal model studies. Although these studies are still in their experimental stages, they help identify new potential therapeutic targets. Future preclinical and clinical studies will help to translate these exciting experimental research findings into clinical applications. PMID:23536532

  16. Sustainable production of biologically active molecules of marine based origin.

    Science.gov (United States)

    Murray, Patrick M; Moane, Siobhan; Collins, Catherine; Beletskaya, Tanya; Thomas, Olivier P; Duarte, Alysson W F; Nobre, Fernando S; Owoyemi, Ifeloju O; Pagnocca, Fernando C; Sette, L D; McHugh, Edward; Causse, Eric; Pérez-López, Paula; Feijoo, Gumersindo; Moreira, Ma T; Rubiolo, Juan; Leirós, Marta; Botana, Luis M; Pinteus, Susete; Alves, Celso; Horta, André; Pedrosa, Rui; Jeffryes, Clayton; Agathos, Spiros N; Allewaert, Celine; Verween, Annick; Vyverman, Wim; Laptev, Ivan; Sineoky, Sergei; Bisio, Angela; Manconi, Renata; Ledda, Fabio; Marchi, Mario; Pronzato, Roberto; Walsh, Daniel J

    2013-09-25

    The marine environment offers both economic and scientific potential which are relatively untapped from a biotechnological point of view. These environments whilst harsh are ironically fragile and dependent on a harmonious life form balance. Exploitation of natural resources by exhaustive wild harvesting has obvious negative environmental consequences. From a European industry perspective marine organisms are a largely underutilised resource. This is not due to lack of interest but due to a lack of choice the industry faces for cost competitive, sustainable and environmentally conscientious product alternatives. Knowledge of the biotechnological potential of marine organisms together with the development of sustainable systems for their cultivation, processing and utilisation are essential. In 2010, the European Commission recognised this need and funded a collaborative RTD/SME project under the Framework 7-Knowledge Based Bio-Economy (KBBE) Theme 2 Programme 'Sustainable culture of marine microorganisms, algae and/or invertebrates for high value added products'. The scope of that project entitled 'Sustainable Production of Biologically Active Molecules of Marine Based Origin' (BAMMBO) is outlined. Although the Union is a global leader in many technologies, it faces increasing competition from traditional rivals and emerging economies alike and must therefore improve its innovation performance. For this reason innovation is placed at the heart of a European Horizon 2020 Strategy wherein the challenge is to connect economic performance to eco performance. This article provides a synopsis of the research activities of the BAMMBO project as they fit within the wider scope of sustainable environmentally conscientious marine resource exploitation for high-value biomolecules. Copyright © 2013 Elsevier B.V. All rights reserved.

  17. Pharmacology and toxicology of diphenyl diselenide in several biological models

    Directory of Open Access Journals (Sweden)

    R.M. Rosa

    2007-10-01

    Full Text Available The pharmacology of synthetic organoselenium compounds indicates that they can be used as antioxidants, enzyme inhibitors, neuroprotectors, anti-tumor and anti-infectious agents, and immunomodulators. In this review, we focus on the effects of diphenyl diselenide (DPDS in various biological model organisms. DPDS possesses antioxidant activity, confirmed in several in vitro and in vivo systems, and thus has a protective effect against hepatic, renal and gastric injuries, in addition to its neuroprotective activity. The activity of the compound on the central nervous system has been studied since DPDS has lipophilic characteristics, increasing adenylyl cyclase activity and inhibiting glutamate and MK-801 binding to rat synaptic membranes. Systemic administration facilitates the formation of long-term object recognition memory in mice and has a protective effect against brain ischemia and on reserpine-induced orofacial dyskinesia in rats. On the other hand, DPDS may be toxic, mainly because of its interaction with thiol groups. In the yeast Saccharomyces cerevisiae, the molecule acts as a pro-oxidant by depleting free glutathione. Administration to mice during cadmium intoxication has the opposite effect, reducing oxidative stress in various tissues. DPDS is a potent inhibitor of d-aminolevulinate dehydratase and chronic exposure to high doses of this compound has central effects on mouse brain, as well as liver and renal toxicity. Genotoxicity of this compound has been assessed in bacteria, haploid and diploid yeast and in a tumor cell line.

  18. METABOLIC MODELLING IN THE DEVELOPMENT OF CELL FACTORIES BY SYNTHETIC BIOLOGY

    Directory of Open Access Journals (Sweden)

    Paula Jouhten

    2012-10-01

    Full Text Available Cell factories are commonly microbial organisms utilized for bioconversion of renewable resources to bulk or high value chemicals. Introduction of novel production pathways in chassis strains is the core of the development of cell factories by synthetic biology. Synthetic biology aims to create novel biological functions and systems not found in nature by combining biology with engineering. The workflow of the development of novel cell factories with synthetic biology is ideally linear which will be attainable with the quantitative engineering approach, high-quality predictive models, and libraries of well-characterized parts. Different types of metabolic models, mathematical representations of metabolism and its components, enzymes and metabolites, are useful in particular phases of the synthetic biology workflow. In this minireview, the role of metabolic modelling in synthetic biology will be discussed with a review of current status of compatible methods and models for the in silico design and quantitative evaluation of a cell factory.

  19. Biology meets Physics: Reductionism and Multi-scale Modeling of Morphogenesis

    DEFF Research Database (Denmark)

    Green, Sara; Batterman, Robert

    2017-01-01

    from philosophers of biology. Specifically, scholars have pointed to the impossibility of deducing biological explanations from physical ones, and to the irreducible nature of distinctively biological processes such as gene regulation and evolution. This paper takes a step back in asking whether bottom......-up modeling is feasible even when modeling simple physical systems across scales. By comparing examples of multi-scale modeling in physics and biology, we argue that the “tyranny of scales” problem present a challenge to reductive explanations in both physics and biology. The problem refers to the scale......-dependency of physical and biological behaviors that forces researchers to combine different models relying on different scale-specific mathematical strategies and boundary conditions. Analyzing the ways in which different models are combined in multi-scale modeling also has implications for the relation between physics...

  20. Organizing Community-Based Data Standards: Lessons from Developing a Successful Open Standard in Systems Biology

    Science.gov (United States)

    Hucka, M.

    2015-09-01

    In common with many fields, including astronomy, a vast number of software tools for computational modeling and simulation are available today in systems biology. This wealth of resources is a boon to researchers, but it also presents interoperability problems. Despite working with different software tools, researchers want to disseminate their work widely as well as reuse and extend the models of other researchers. This situation led in the year 2000 to an effort to create a tool-independent, machine-readable file format for representing models: SBML, the Systems Biology Markup Language. SBML has since become the de facto standard for its purpose. Its success and general approach has inspired and influenced other community-oriented standardization efforts in systems biology. Open standards are essential for the progress of science in all fields, but it is often difficult for academic researchers to organize successful community-based standards. I draw on personal experiences from the development of SBML and summarize some of the lessons learned, in the hope that this may be useful to other groups seeking to develop open standards in a community-oriented fashion.

  1. Integrative biological simulation praxis: Considerations from physics, philosophy, and data/model curation practices

    OpenAIRE

    Sarma, Gopal P.; Faundez, Victor

    2017-01-01

    ABSTRACT Integrative biological simulations have a varied and controversial history in the biological sciences. From computational models of organelles, cells, and simple organisms, to physiological models of tissues, organ systems, and ecosystems, a diverse array of biological systems have been the target of large-scale computational modeling efforts. Nonetheless, these research agendas have yet to prove decisively their value among the broader community of theoretical and experimental biolo...

  2. "Model Your Genes the Mathematical Way"--A Mathematical Biology Workshop for Secondary School Teachers

    Science.gov (United States)

    Martins, Ana Margarida; Vera-Licona, Paola; Laubenbacher, Reinhard

    2008-01-01

    This article describes a mathematical biology workshop given to secondary school teachers of the Danville area in Virginia, USA. The goal of the workshop was to enable teams of teachers with biology and mathematics expertise to incorporate lesson plans in mathematical modelling into the curriculum. The biological focus of the activities is the…

  3. Application of Biologically Based Lumping To Investigate the Toxicokinetic Interactions of a Complex Gasoline Mixture.

    Science.gov (United States)

    Jasper, Micah N; Martin, Sheppard A; Oshiro, Wendy M; Ford, Jermaine; Bushnell, Philip J; El-Masri, Hisham

    2016-03-15

    People are often exposed to complex mixtures of environmental chemicals such as gasoline, tobacco smoke, water contaminants, or food additives. We developed an approach that applies chemical lumping methods to complex mixtures, in this case gasoline, based on biologically relevant parameters used in physiologically based pharmacokinetic (PBPK) modeling. Inhalation exposures were performed with rats to evaluate the performance of our PBPK model and chemical lumping method. There were 109 chemicals identified and quantified in the vapor in the chamber. The time-course toxicokinetic profiles of 10 target chemicals were also determined from blood samples collected during and following the in vivo experiments. A general PBPK model was used to compare the experimental data to the simulated values of blood concentration for 10 target chemicals with various numbers of lumps, iteratively increasing from 0 to 99. Large reductions in simulation error were gained by incorporating enzymatic chemical interactions, in comparison to simulating the individual chemicals separately. The error was further reduced by lumping the 99 nontarget chemicals. The same biologically based lumping approach can be used to simplify any complex mixture with tens, hundreds, or thousands of constituents.

  4. Numerical model for biological fluidized-bed reactor treatment of perchlorate contaminated groundwater.

    Science.gov (United States)

    McCarty, Perry L; Meyer, Travis E

    2005-02-01

    Biological fluidized-bed reactor (BFBR) treatment with 1.3 mm granular activated carbon as support medium is being used for removal of 2.6 mg/L perchlorate from contaminated groundwater in California. The California drinking-water action level of 4 microg/L for perchlorate requires 99.9% perchlorate removal. Sufficient ethanol, the electron donor, is added to remove oxygen and nitrate as well as perchlorate, as all three serve as electron acceptors, but with biological preference for oxygen and nitrate. A numerical BFBR model based upon basic physical, chemical, and biological processes including reaction stoichiometry, biofilm kinetics, and sequential electron acceptor usage was developed and evaluated with the full-scale treatment results. A key fitting parameter was bacterial detachment rate, which impacts reaction stoichiometry. For best model fit this was found to vary between 0.062 and 0.31 d(-1), with an average of 0.22 d(-1). The model indicates that GAC particle size, reactor diameter, and perchlorate concentration affect BFBR performance. While empty-bed detention time might be decreased somewhat below 10 min by an increase in either GAC particle size or reactor diameter, the current design provides a good factor of safety in operation. With a 10 min detention time, the effluent goal of 4 microg/L should be achievable even with influent perchlorate concentration as high as 10 mg/L.

  5. Data to support "Boosted Regression Tree Models to Explain Watershed Nutrient Concentrations & Biological Condition"

    Data.gov (United States)

    U.S. Environmental Protection Agency — Spreadsheets are included here to support the manuscript "Boosted Regression Tree Models to Explain Watershed Nutrient Concentrations and Biological Condition". This...

  6. A Study of the Literature on Lab-Based Instruction in Biology

    Science.gov (United States)

    Puttick, Gillian; Drayton, Brian; Cohen, Eliza

    2015-01-01

    We analyzed the practitioner literature on lab-based instruction in biology in "The American Biology Teacher" between 2007 and 2012. We investigated what laboratory learning looks like in biology classrooms, what topics are addressed, what instructional methods and activities are described, and what is being learned about student…

  7. Challenges and Opportunities for Learning Biology in Distance-Based Settings

    Science.gov (United States)

    Hallyburton, Chad L.; Lunsford, Eddie

    2013-01-01

    The history of learning biology through distance education is documented. A review of terminology and unique problems associated with biology instruction is presented. Using published research and their own teaching experience, the authors present recommendations and best practices for managing biology in distance-based formats. They offer ideas…

  8. Vicus: Exploiting local structures to improve network-based analysis of biological data.

    Directory of Open Access Journals (Sweden)

    Bo Wang

    2017-10-01

    Full Text Available Biological networks entail important topological features and patterns critical to understanding interactions within complicated biological systems. Despite a great progress in understanding their structure, much more can be done to improve our inference and network analysis. Spectral methods play a key role in many network-based applications. Fundamental to spectral methods is the Laplacian, a matrix that captures the global structure of the network. Unfortunately, the Laplacian does not take into account intricacies of the network's local structure and is sensitive to noise in the network. These two properties are fundamental to biological networks and cannot be ignored. We propose an alternative matrix Vicus. The Vicus matrix captures the local neighborhood structure of the network and thus is more effective at modeling biological interactions. We demonstrate the advantages of Vicus in the context of spectral methods by extensive empirical benchmarking on tasks such as single cell dimensionality reduction, protein module discovery and ranking genes for cancer subtyping. Our experiments show that using Vicus, spectral methods result in more accurate and robust performance in all of these tasks.

  9. Vicus: Exploiting local structures to improve network-based analysis of biological data.

    Science.gov (United States)

    Wang, Bo; Huang, Lin; Zhu, Yuke; Kundaje, Anshul; Batzoglou, Serafim; Goldenberg, Anna

    2017-10-01

    Biological networks entail important topological features and patterns critical to understanding interactions within complicated biological systems. Despite a great progress in understanding their structure, much more can be done to improve our inference and network analysis. Spectral methods play a key role in many network-based applications. Fundamental to spectral methods is the Laplacian, a matrix that captures the global structure of the network. Unfortunately, the Laplacian does not take into account intricacies of the network's local structure and is sensitive to noise in the network. These two properties are fundamental to biological networks and cannot be ignored. We propose an alternative matrix Vicus. The Vicus matrix captures the local neighborhood structure of the network and thus is more effective at modeling biological interactions. We demonstrate the advantages of Vicus in the context of spectral methods by extensive empirical benchmarking on tasks such as single cell dimensionality reduction, protein module discovery and ranking genes for cancer subtyping. Our experiments show that using Vicus, spectral methods result in more accurate and robust performance in all of these tasks.

  10. Hidden Markov models and other machine learning approaches in computational molecular biology

    Energy Technology Data Exchange (ETDEWEB)

    Baldi, P. [California Inst. of Tech., Pasadena, CA (United States)

    1995-12-31

    This tutorial was one of eight tutorials selected to be presented at the Third International Conference on Intelligent Systems for Molecular Biology which was held in the United Kingdom from July 16 to 19, 1995. Computational tools are increasingly needed to process the massive amounts of data, to organize and classify sequences, to detect weak similarities, to separate coding from non-coding regions, and reconstruct the underlying evolutionary history. The fundamental problem in machine learning is the same as in scientific reasoning in general, as well as statistical modeling: to come up with a good model for the data. In this tutorial four classes of models are reviewed. They are: Hidden Markov models; artificial Neural Networks; Belief Networks; and Stochastic Grammars. When dealing with DNA and protein primary sequences, Hidden Markov models are one of the most flexible and powerful alignments and data base searches. In this tutorial, attention is focused on the theory of Hidden Markov Models, and how to apply them to problems in molecular biology.

  11. Cluster Based Text Classification Model

    DEFF Research Database (Denmark)

    Nizamani, Sarwat; Memon, Nasrullah; Wiil, Uffe Kock

    2011-01-01

    We propose a cluster based classification model for suspicious email detection and other text classification tasks. The text classification tasks comprise many training examples that require a complex classification model. Using clusters for classification makes the model simpler and increases......, the classifier is trained on each cluster having reduced dimensionality and less number of examples. The experimental results show that the proposed model outperforms the existing classification models for the task of suspicious email detection and topic categorization on the Reuters-21578 and 20 Newsgroups...... datasets. Our model also outperforms A Decision Cluster Classification (ADCC) and the Decision Cluster Forest Classification (DCFC) models on the Reuters-21578 dataset....

  12. Graph Model Based Indoor Tracking

    DEFF Research Database (Denmark)

    Jensen, Christian Søndergaard; Lu, Hua; Yang, Bin

    2009-01-01

    The tracking of the locations of moving objects in large indoor spaces is important, as it enables a range of applications related to, e.g., security and indoor navigation and guidance. This paper presents a graph model based approach to indoor tracking that offers a uniform data management...... infrastructure for different symbolic positioning technologies, e.g., Bluetooth and RFID. More specifically, the paper proposes a model of indoor space that comprises a base graph and mappings that represent the topology of indoor space at different levels. The resulting model can be used for one or several...... indoor positioning technologies. Focusing on RFID-based positioning, an RFID specific reader deployment graph model is built from the base graph model. This model is then used in several algorithms for constructing and refining trajectories from raw RFID readings. Empirical studies with implementations...

  13. Comparison of Model Calculations of Biological Damage from Exposure to Heavy Ions with Measurements

    Science.gov (United States)

    Kim, Myung-Hee Y.; Hada, Megumi; Cucinotta, Francis A.; Wu, Honglu

    2014-01-01

    The space environment consists of a varying field of radiation particles including high-energy ions, with spacecraft shielding material providing the major protection to astronauts from harmful exposure. Unlike low-LET gamma or X rays, the presence of shielding does not always reduce the radiation risks for energetic charged-particle exposure. Dose delivered by the charged particle increases sharply at the Bragg peak. However, the Bragg curve does not necessarily represent the biological damage along the particle path since biological effects are influenced by the track structures of both primary and secondary particles. Therefore, the ''biological Bragg curve'' is dependent on the energy and the type of the primary particle and may vary for different biological end points. Measurements of the induction of micronuclei (MN) have made across the Bragg curve in human fibroblasts exposed to energetic silicon and iron ions in vitro at two different energies, 300 MeV/nucleon and 1 GeV/nucleon. Although the data did not reveal an increased yield of MN at the location of the Bragg peak, the increased inhibition of cell progression, which is related to cell death, was found at the Bragg peak location. These results are compared to the calculations of biological damage using a stochastic Monte-Carlo track structure model, Galactic Cosmic Ray Event-based Risk Model (GERM) code (Cucinotta, et al., 2011). The GERM code estimates the basic physical properties along the passage of heavy ions in tissue and shielding materials, by which the experimental set-up can be interpreted. The code can also be used to describe the biophysical events of interest in radiobiology, cancer therapy, and space exploration. The calculation has shown that the severely damaged cells at the Bragg peak are more likely to go through reproductive death, the so called "overkill".

  14. Reconstructing Anaximander's biological model unveils a theory of evolution akin to Darwin's, though centuries before the birth of science.

    Science.gov (United States)

    Trevisanato, Siro Igino

    2016-08-01

    Anaximander's fragments on biology report a theory of evolution, which, unlike the development of other biological systems in the ancient Aegean, is naturalistic and is not based on metaphysics. According to Anaximander, evolution affected all living beings, including humans. The first biological systems formed in an aquatic environment, and were encased in a rugged and robust envelope. Evolution progressed with modifications that enabled the formation of more dynamic biological systems. For instance, after reaching land, the robust armors around aquatic beings dried up, and became brittle, This led to the loss of the armor and the development of more mobile life forms. Anaximander's theory combines observations of animals with speculations, and as such mirrors the more famous theory of evolution by Charles Darwin expressed 24 centuries later. The poor reception received by Anaximander's model in his time, illustrates a zeitgeist that would explain the contemporary lag phase in the development of biology and, as a result, medicine, in the ancient western world.

  15. Activity-based DEVS modeling

    DEFF Research Database (Denmark)

    Alshareef, Abdurrahman; Sarjoughian, Hessam S.; Zarrin, Bahram

    2018-01-01

    architecture and the UML concepts. In this paper, we further this work by grounding Activity-based DEVS modeling and developing a fully-fledged modeling engine to demonstrate applicability. We also detail the relevant aspects of the created metamodel in terms of modeling and simulation. A significant number...

  16. Modeling Wireless Sensor Networks for Monitoring in Biological Processes

    DEFF Research Database (Denmark)

    Nadimi, Esmaeil

    (MMAE) approach to the data resulted in the highest classification success rate, due to the use of precise forth-order mathematical models which relate the feed offer to the pitch angle of the neck. This thesis shows that wireless sensor networks can be successfully employed to monitor the behavior...... parameters, as the use of wired sensors is impractical. In this thesis, a ZigBee based wireless sensor network was employed and only a part of the herd was monitored, as monitoring each individual animal in a large herd under practical conditions is inefficient. Investigations to show that the monitored...... signal strength). Fusing the two measured behavioral data resulted in an improvement of the classification results regarding the animal behavior mode (activity/inactivity), compared to the results achieved by only monitoring one of the behavioral parameters. Applying a multiple-model adaptive estimation...

  17. Expansion of biological pathways based on evolutionary inference.

    Science.gov (United States)

    Li, Yang; Calvo, Sarah E; Gutman, Roee; Liu, Jun S; Mootha, Vamsi K

    2014-07-03

    The availability of diverse genomes makes it possible to predict gene function based on shared evolutionary history. This approach can be challenging, however, for pathways whose components do not exhibit a shared history but rather consist of distinct "evolutionary modules." We introduce a computational algorithm, clustering by inferred models of evolution (CLIME), which inputs a eukaryotic species tree, homology matrix, and pathway (gene set) of interest. CLIME partitions the gene set into disjoint evolutionary modules, simultaneously learning the number of modules and a tree-based evolutionary history that defines each module. CLIME then expands each module by scanning the genome for new components that likely arose under the inferred evolutionary model. Application of CLIME to ∼1,000 annotated human pathways and to the proteomes of yeast, red algae, and malaria reveals unanticipated evolutionary modularity and coevolving components. CLIME is freely available and should become increasingly powerful with the growing wealth of eukaryotic genomes. Copyright © 2014 Elsevier Inc. All rights reserved.

  18. PeTTSy: a computational tool for perturbation analysis of complex systems biology models.

    Science.gov (United States)

    Domijan, Mirela; Brown, Paul E; Shulgin, Boris V; Rand, David A

    2016-03-10

    Over the last decade sensitivity analysis techniques have been shown to be very useful to analyse complex and high dimensional Systems Biology models. However, many of the currently available toolboxes have either used parameter sampling, been focused on a restricted set of model observables of interest, studied optimisation of a objective function, or have not dealt with multiple simultaneous model parameter changes where the changes can be permanent or temporary. Here we introduce our new, freely downloadable toolbox, PeTTSy (Perturbation Theory Toolbox for Systems). PeTTSy is a package for MATLAB which implements a wide array of techniques for the perturbation theory and sensitivity analysis of large and complex ordinary differential equation (ODE) based models. PeTTSy is a comprehensive modelling framework that introduces a number of new approaches and that fully addresses analysis of oscillatory systems. It examines sensitivity analysis of the models to perturbations of parameters, where the perturbation timing, strength, length and overall shape can be controlled by the user. This can be done in a system-global setting, namely, the user can determine how many parameters to perturb, by how much and for how long. PeTTSy also offers the user the ability to explore the effect of the parameter perturbations on many different types of outputs: period, phase (timing of peak) and model solutions. PeTTSy can be employed on a wide range of mathematical models including free-running and forced oscillators and signalling systems. To enable experimental optimisation using the Fisher Information Matrix it efficiently allows one to combine multiple variants of a model (i.e. a model with multiple experimental conditions) in order to determine the value of new experiments. It is especially useful in the analysis of large and complex models involving many variables and parameters. PeTTSy is a comprehensive tool for analysing large and complex models of regulatory and

  19. PA401, a novel CXCL8-based biologic therapeutic with increased glycosaminoglycan binding, reduces bronchoalveolar lavage neutrophils and systemic inflammatory markers in a murine model of LPS-induced lung inflammation.

    Science.gov (United States)

    Adage, Tiziana; Del Bene, Francesca; Fiorentini, Francesco; Doornbos, Robert P; Zankl, Christina; Bartley, Michael R; Kungl, Andreas J

    2015-12-01

    Neutrophils play a fundamental role in a number of chronic lung diseases. Among the mediators of their recruitment to the lung, CXCL8 (IL-8) is considered to be one of the major players. CXCL8 exerts its chemotactic activity by binding to its GPCR receptors (CXCR1/R2) located on neutrophils, as well as through interactions with glycosaminoglycans (GAGs) on cell surfaces including those of the microvascular endothelium. Binding to GAG co-receptors is required to generate a solid-phase haptotactic gradient and to present IL-8/CXCL8 in a proper conformation to its receptors on circulating neutrophils. We have engineered increased GAG-binding affinity into human CXCL8, thereby obtaining a competitive inhibitor that displaces wild-type IL-8/CXCL8 from GAGs. By additionally knocking-out the GPCR binding domain of the chemokine, we generated a dominant negative protein (dnCXCL8; PA401) with potent anti-inflammatory characteristics proven in vivo in a murine model of LPS-induced lung inflammation (Adage et al., 2015). Here we have further investigated PA401 activity in this pulmonary model by evaluating plasma changes induced by LPS on white blood cells (WBC) and a broad range of inflammatory markers, especially chemokines, by addressing immediate effects of PA401 on these parameters in healthy and LPS exposed mice. Aerosolized LPS induced a significant increase in bronchoalveolar lavage (BAL) neutrophils after 3 and 7h, as well as an increase in total WBC and changes in 21 of the 59 measured plasma markers, mostly belonging to the chemokine family. PA401 treatment in saline exposed mice didn't induce major changes in any of the measured parameters. When administered to LPS aerosolized mice, PA401 caused a significant normalization of KC/mCXCL1 and other inflammatory markers, as well as of blood WBC count. In addition, BAL neutrophils were significantly reduced, confirming the previously observed lung anti-inflammatory activity of PA401 in this experiment. PA401 is a new

  20. Towards the virtual artery: a multiscale model for vascular physiology at the physics-chemistry-biology interface.

    Science.gov (United States)

    Hoekstra, Alfons G; Alowayyed, Saad; Lorenz, Eric; Melnikova, Natalia; Mountrakis, Lampros; van Rooij, Britt; Svitenkov, Andrew; Závodszky, Gábor; Zun, Pavel

    2016-11-13

    This discussion paper introduces the concept of the Virtual Artery as a multiscale model for arterial physiology and pathologies at the physics-chemistry-biology (PCB) interface. The cellular level is identified as the mesoscopic level, and we argue that by coupling cell-based models with other relevant models on the macro- and microscale, a versatile model of arterial health and disease can be composed. We review the necessary ingredients, both models of arteries at many different scales, as well as generic methods to compose multiscale models. Next, we discuss how this can be combined into the virtual artery. Finally, we argue that the concept of models at the PCB interface could or perhaps should become a powerful paradigm, not only as in our case for studying physiology, but also for many other systems that have such PCB interfaces.This article is part of the themed issue 'Multiscale modelling at the physics-chemistry-biology interface'. © 2016 The Authors.

  1. Towards the virtual artery: a multiscale model for vascular physiology at the physics–chemistry–biology interface

    Science.gov (United States)

    Alowayyed, Saad; Lorenz, Eric; Melnikova, Natalia; Mountrakis, Lampros; van Rooij, Britt; Svitenkov, Andrew; Závodszky, Gábor; Zun, Pavel

    2016-01-01

    This discussion paper introduces the concept of the Virtual Artery as a multiscale model for arterial physiology and pathologies at the physics–chemistry–biology (PCB) interface. The cellular level is identified as the mesoscopic level, and we argue that by coupling cell-based models with other relevant models on the macro- and microscale, a versatile model of arterial health and disease can be composed. We review the necessary ingredients, both models of arteries at many different scales, as well as generic methods to compose multiscale models. Next, we discuss how this can be combined into the virtual artery. Finally, we argue that the concept of models at the PCB interface could or perhaps should become a powerful paradigm, not only as in our case for studying physiology, but also for many other systems that have such PCB interfaces. This article is part of the themed issue ‘Multiscale modelling at the physics–chemistry–biology interface’. PMID:27698036

  2. Systematic synergy modeling: understanding drug synergy from a systems biology perspective.

    Science.gov (United States)

    Chen, Di; Liu, Xi; Yang, Yiping; Yang, Hongjun; Lu, Peng

    2015-09-16

    Owing to drug synergy effects, drug combinations have become a new trend in combating complex diseases like cancer, HIV and cardiovascular diseases. However, conventional synergy quantification methods often depend on experimental dose-response data which are quite resource-demanding. In addition, these methods are unable to interpret the explicit synergy mechanism. In this review, we give representative examples of how systems biology modeling offers strategies toward better understanding of drug synergy, including the protein-protein interaction (PPI) network-based methods, pathway dynamic simulations, synergy network motif recognitions, integrative drug feature calculations, and "omic"-supported analyses. Although partially successful in drug synergy exploration and interpretation, more efforts should be put on a holistic understanding of drug-disease interactions, considering integrative pharmacology and toxicology factors. With a comprehensive and deep insight into the mechanism of drug synergy, systems biology opens a novel avenue for rational design of effective drug combinations.

  3. Modelling the Influence of Shielding on Physical and Biological Organ Doses

    CERN Document Server

    Ballarini, Francesca; Ferrari, Alfredo; Ottolenghi, Andrea; Pelliccioni, Maurizio; Scannicchio, Domenico

    2002-01-01

    Distributions of "physical" and "biological" dose in different organs were calculated by coupling the FLUKA MC transport code with a geometrical human phantom inserted into a shielding box of variable shape, thickness and material. While the expression "physical dose" refers to the amount of deposited energy per unit mass (in Gy), "biological dose" was modelled with "Complex Lesions" (CL), clustered DNA strand breaks calculated in a previous work based on "event-by-event" track-structure simulations. The yields of complex lesions per cell and per unit dose were calculated for different radiation types and energies, and integrated into a version of FLUKA modified for this purpose, allowing us to estimate the effects of mixed fields. As an initial test simulation, the phantom was inserted into an aluminium parallelepiped and was isotropically irradiated with 500 MeV protons. Dose distributions were calculated for different values of the shielding thickness. The results were found to be organ-dependent. In most ...

  4. Biological and environmental surface interactions of nanomaterials: characterization, modeling, and prediction.

    Science.gov (United States)

    Chen, Ran; Riviere, Jim E

    2017-05-01

    The understanding of nano-bio interactions is deemed essential in the design, application, and safe handling of nanomaterials. Proper characterization of the intrinsic physicochemical properties, including their size, surface charge, shape, and functionalization, is needed to consider the fate or impact of nanomaterials in biological and environmental systems. The characterizations of their interactions with surrounding chemical species are often hindered by the complexity of biological or environmental systems, and the drastically different surface physicochemical properties among a large population of nanomaterials. The complexity of these interactions is also due to the diverse ligands of different chemical properties present in most biomacromolecules, and multiple conformations they can assume at different conditions to minimize their conformational free energy. Often these interactions are collectively determined by multiple physical or chemical forces, including electrostatic forces, hydrogen bonding, and hydrophobic forces, and calls for multidimensional characterization strategies, both experimentally and computationally. Through these characterizations, the understanding of the roles surface physicochemical properties of nanomaterials and their surface interactions with biomacromolecules can play in their applications in biomedical and environmental fields can be obtained. To quantitatively decipher these physicochemical surface interactions, computational methods, including physical, statistical, and pharmacokinetic models, can be used for either analyses of large amounts of experimental characterization data, or theoretical prediction of the interactions, and consequent biological behavior in the body after administration. These computational methods include molecular dynamics simulation, structure-activity relationship models such as biological surface adsorption index, and physiologically-based pharmacokinetic models. WIREs Nanomed Nanobiotechnol 2017

  5. Quantitative Modeling of Membrane Transport and Anisogamy by Small Groups Within a Large-Enrollment Organismal Biology Course

    Directory of Open Access Journals (Sweden)

    Eric S. Haag

    2016-12-01

    Full Text Available Quantitative modeling is not a standard part of undergraduate biology education, yet is routine in the physical sciences. Because of the obvious biophysical aspects, classes in anatomy and physiology offer an opportunity to introduce modeling approaches to the introductory curriculum. Here, we describe two in-class exercises for small groups working within a large-enrollment introductory course in organismal biology. Both build and derive biological insights from quantitative models, implemented using spreadsheets. One exercise models the evolution of anisogamy (i.e., small sperm and large eggs from an initial state of isogamy. Groups of four students work on Excel spreadsheets (from one to four laptops per group. The other exercise uses an online simulator to generate data related to membrane transport of a solute, and a cloud-based spreadsheet to analyze them. We provide tips for implementing these exercises gleaned from two years of experience.

  6. Chemical kinetic mechanistic models to investigate cancer biology and impact cancer medicine

    International Nuclear Information System (INIS)

    Stites, Edward C

    2013-01-01

    Traditional experimental biology has provided a mechanistic understanding of cancer in which the malignancy develops through the acquisition of mutations that disrupt cellular processes. Several drugs developed to target such mutations have now demonstrated clinical value. These advances are unequivocal testaments to the value of traditional cellular and molecular biology. However, several features of cancer may limit the pace of progress that can be made with established experimental approaches alone. The mutated genes (and resultant mutant proteins) function within large biochemical networks. Biochemical networks typically have a large number of component molecules and are characterized by a large number of quantitative properties. Responses to a stimulus or perturbation are typically nonlinear and can display qualitative changes that depend upon the specific values of variable system properties. Features such as these can complicate the interpretation of experimental data and the formulation of logical hypotheses that drive further research. Mathematical models based upon the molecular reactions that define these networks combined with computational studies have the potential to deal with these obstacles and to enable currently available information to be more completely utilized. Many of the pressing problems in cancer biology and cancer medicine may benefit from a mathematical treatment. As work in this area advances, one can envision a future where such models may meaningfully contribute to the clinical management of cancer patients. (paper)

  7. Realistic modeling of the biological channel for the design of implantable wireless UWB communication systems.

    Science.gov (United States)

    Bahrami, Hadi; Gosselin, Benoit; Rusch, Leslie A

    2012-01-01

    Several emerging medical applications require that a miniature data acquisition device be implanted into the head to extract and wirelessly communicate brain activity to other devices. Designing a reliable communication link for such an application requires a realistic model of the surrounding biological tissues. This paper exploits a realistic model of the biological channel to design a suitable wireless ultra wideband communication link in a brain monitoring application. Two scenarios for positioning the implanted transmitting antenna are considered. The 1(st) scenario places the antenna under the skull, whereas the 2(nd) scenario places the antenna under the skin, above the skull. The propagation characteristics of the signal through the tissues of the human head have been determined with full-wave electromagnetic simulation based on Finite Element Method. The implantable antenna and the external antenna are key components to establish an electromagnetic link between an implanted transmitter and an external receiver. The average specific absorption rate (ASAR) of the implantable antennas are evaluated and compared for the two proposed scenarios. Moreover, the maximum available power from the implanted antenna is evaluated to characterize the performance of the communication link established between the implantable antenna and the external antenna, with respect to spectrum and safety regulations. We show how sensitive the receiver must be in order to implement a reliable telemetry link based on the proposed model of the channel.

  8. Electrical circuit modeling and analysis of microwave acoustic interaction with biological tissues.

    Science.gov (United States)

    Gao, Fei; Zheng, Qian; Zheng, Yuanjin

    2014-05-01

    Numerical study of microwave imaging and microwave-induced thermoacoustic imaging utilizes finite difference time domain (FDTD) analysis for simulation of microwave and acoustic interaction with biological tissues, which is time consuming due to complex grid-segmentation and numerous calculations, not straightforward due to no analytical solution and physical explanation, and incompatible with hardware development requiring circuit simulator such as SPICE. In this paper, instead of conventional FDTD numerical simulation, an equivalent electrical circuit model is proposed to model the microwave acoustic interaction with biological tissues for fast simulation and quantitative analysis in both one and two dimensions (2D). The equivalent circuit of ideal point-like tissue for microwave-acoustic interaction is proposed including transmission line, voltage-controlled current source, envelop detector, and resistor-inductor-capacitor (RLC) network, to model the microwave scattering, thermal expansion, and acoustic generation. Based on which, two-port network of the point-like tissue is built and characterized using pseudo S-parameters and transducer gain. Two dimensional circuit network including acoustic scatterer and acoustic channel is also constructed to model the 2D spatial information and acoustic scattering effect in heterogeneous medium. Both FDTD simulation, circuit simulation, and experimental measurement are performed to compare the results in terms of time domain, frequency domain, and pseudo S-parameters characterization. 2D circuit network simulation is also performed under different scenarios including different sizes of tumors and the effect of acoustic scatterer. The proposed circuit model of microwave acoustic interaction with biological tissue could give good agreement with FDTD simulated and experimental measured results. The pseudo S-parameters and characteristic gain could globally evaluate the performance of tumor detection. The 2D circuit network

  9. Systems Biology based studies on anti-inflammatory compounds

    NARCIS (Netherlands)

    Verhoeckx, Kitty Catharina Maria

    2005-01-01

    The introduction of the ‘omics’ techniques (transcriptomics, proteomics, and metabolomics) and systems biology, has caused fundamental changes in the drug discovery process and many other fields in the life science area. In this thesis we explored the possibilities to apply these holistic

  10. Neural network models: from biology to many - body phenomenology

    International Nuclear Information System (INIS)

    Clark, J.W.

    1993-01-01

    Theoretical work in neural networks has a strange feel for most physicists. In some cases the aspect of design becomes paramount. More comfortable ground at least for many body theorists may be found in realistic biological simulation, although the complexity of most problems is so awesome that incisive results will be hard won. It has also shown the impressive capabilities of artificial networks in pattern recognition and classification may be exploited to solve management problems in experimental physics and for discovery of radically new theoretical description of physical systems. This advance represents an important step towards the ultimate goal of neuro biological paradigm. (A.B.)

  11. Development of biological movement recognition by interaction between active basis model and fuzzy optical flow division.

    Science.gov (United States)

    Yousefi, Bardia; Loo, Chu Kiong

    2014-01-01

    Following the study on computational neuroscience through functional magnetic resonance imaging claimed that human action recognition in the brain of mammalian pursues two separated streams, that is, dorsal and ventral streams. It follows up by two pathways in the bioinspired model, which are specialized for motion and form information analysis (Giese and Poggio 2003). Active basis model is used to form information which is different from orientations and scales of Gabor wavelets to form a dictionary regarding object recognition (human). Also biologically movement optic-flow patterns utilized. As motion information guides share sketch algorithm in form pathway for adjustment plus it helps to prevent wrong recognition. A synergetic neural network is utilized to generate prototype templates, representing general characteristic form of every class. Having predefined templates, classifying performs based on multitemplate matching. As every human action has one action prototype, there are some overlapping and consistency among these templates. Using fuzzy optical flow division scoring can prevent motivation for misrecognition. We successfully apply proposed model on the human action video obtained from KTH human action database. Proposed approach follows the interaction between dorsal and ventral processing streams in the original model of the biological movement recognition. The attained results indicate promising outcome and improvement in robustness using proposed approach.

  12. Biological Surface Adsorption Index of Nanomaterials: Modelling Surface Interactions of Nanomaterials with Biomolecules.

    Science.gov (United States)

    Chen, Ran; Riviere, Jim E

    2017-01-01

    Quantitative analysis of the interactions between nanomaterials and their surrounding environment is crucial for safety evaluation in the application of nanotechnology as well as its development and standardization. In this chapter, we demonstrate the importance of the adsorption of surrounding molecules onto the surface of nanomaterials by forming biocorona and thus impact the bio-identity and fate of those materials. We illustrate the key factors including various physical forces in determining the interaction happening at bio-nano interfaces. We further discuss the mathematical endeavors in explaining and predicting the adsorption phenomena, and propose a new statistics-based surface adsorption model, the Biological Surface Adsorption Index (BSAI), to quantitatively analyze the interaction profile of surface adsorption of a large group of small organic molecules onto nanomaterials with varying surface physicochemical properties, first employing five descriptors representing the surface energy profile of the nanomaterials, then further incorporating traditional semi-empirical adsorption models to address concentration effects of solutes. These Advancements in surface adsorption modelling showed a promising development in the application of quantitative predictive models in biological applications, nanomedicine, and environmental safety assessment of nanomaterials.

  13. Event-Based Conceptual Modeling

    DEFF Research Database (Denmark)

    Bækgaard, Lars

    2009-01-01

    The purpose of the paper is to obtain insight into and provide practical advice for event-based conceptual modeling. We analyze a set of event concepts and use the results to formulate a conceptual event model that is used to identify guidelines for creation of dynamic process models and static...... information models. We characterize events as short-duration processes that have participants, consequences, and properties, and that may be modeled in terms of information structures. The conceptual event model is used to characterize a variety of event concepts and it is used to illustrate how events can...... be used to integrate dynamic modeling of processes and static modeling of information structures. The results are unique in the sense that no other general event concept has been used to unify a similar broad variety of seemingly incompatible event concepts. The general event concept can be used...

  14. Comparison of Model Calculations of Biological Damage from Exposure to Heavy Ions with Measurements

    Science.gov (United States)

    Kim, Myung-Hee Y.; Wu, Honglu; Hada, Megumi; Cucinotta, Francis

    The space environment consists of a varying field of radiation particles including high-energy ions, with spacecraft shielding material providing the major protection to astronauts from harmful exposure. Unlike low-LET g or X rays, the presence of shielding does not always reduce the radiation risks for energetic charged-particle exposure. Dose delivered by the charged particle increases sharply at the Bragg peak. However, the Bragg curve does not necessarily represent the biological damage along the particle path since biological effects are influenced by the track structures of both primary and secondary particles. Therefore, the ‘‘biological Bragg curve’’ is dependent on the energy and the type of the primary particle and may vary for different biological end points. Measurements of the induction of micronuclei (MN) have made across the Bragg curve in human fibroblasts exposed to energetic silicon and iron ions in vitro at two different energies, 300 MeV/nucleon and 1 GeV/nucleon. Although the data did not reveal an increased yield of MN at the location of the Bragg peak, the increased inhibition of cell progression, which is related to cell death, was found at the Bragg peak location. These results are compared to the calculations of biological damage using a stochastic Monte-Carlo track structure model, Galactic Cosmic Ray Event-based Risk Model (GERM) code (Cucinotta et al., 2011). The GERM code estimates the basic physical properties along the passage of heavy ions in tissue and shielding materials, by which the experimental set-up can be interpreted. The code can also be used to describe the biophysical events of interest in radiobiology, cancer therapy, and space exploration. The calculation has shown that the severely damaged cells at the Bragg peak are more likely to go through reproductive death, the so called “overkill”. F. A. Cucinotta, I. Plante, A. L. Ponomarev, and M. Y. Kim, Nuclear Interactions in Heavy Ion Transport and Event-based

  15. Development of a kinetic model for biological sulphate reduction ...

    African Journals Online (AJOL)

    The Rhodes BioSUREÆÊ Process is a low-cost active treatment system for acid mine drainage (AMD) waters. Central to this process is biological sulphate reduction (BSR) using primary sewage sludge (PSS) as the electron donor and organic carbon source, with the concomitant reduction of sulphate to sulphide and ...

  16. ANIMO: a tool for modeling biological pathway dynamics

    NARCIS (Netherlands)

    Schivo, Stefano; Scholma, Jetse; Karperien, Hermanus Bernardus Johannes; Langerak, Romanus; van de Pol, Jan Cornelis; Post, Janine Nicole

    2014-01-01

    Introduction Computational methods are applied with increasing success to the analysis of complex biological systems. However, their adoption is sometimes made difficult by requiring prior knowledge about the foundations of such methods, which often come from a different branch of science. The

  17. A Transformative Model for Undergraduate Quantitative Biology Education

    Science.gov (United States)

    Usher, David C.; Driscoll, Tobin A.; Dhurjati, Prasad; Pelesko, John A.; Rossi, Louis F.; Schleiniger, Gilberto; Pusecker, Kathleen; White, Harold B.

    2010-01-01

    The "BIO2010" report recommended that students in the life sciences receive a more rigorous education in mathematics and physical sciences. The University of Delaware approached this problem by (1) developing a bio-calculus section of a standard calculus course, (2) embedding quantitative activities into existing biology courses, and (3)…

  18. Atomic force microscopy on domains in biological model membranes

    NARCIS (Netherlands)

    Rinia, H.A.

    2001-01-01

    This thesis describes the preparation and imaging of supported lipid bilayers, which can be regarded as biological modelmembranes, in the light of the formation of domains. The bilayers were prepared with either the Langmuir-Blodgett method, or with vesicle fusion. They were imaged with Atomic Force

  19. Event-Based Activity Modeling

    DEFF Research Database (Denmark)

    Bækgaard, Lars

    2004-01-01

    We present and discuss a modeling approach that supports event-based modeling of information and activity in information systems. Interacting human actors and IT-actors may carry out such activity. We use events to create meaningful relations between information structures and the related...

  20. Zirconia based ceramics, some clinical and biological aspects: Review

    Directory of Open Access Journals (Sweden)

    Ossama Saleh Abd El-Ghany

    2016-12-01

    Full Text Available Improved material strength, enhanced esthethic and high biocompatibility give Zirconia ceramic a great possibility to be used for a wide range of promising clinical applications. This review presents the different types of zirconia materials available for dental application, the effect of machining procedures on these materials, the esthetic of zirconia ceramics and bonding of the veneering ceramics in addition to the biologic properties of these new materials.

  1. Statistical Modeling of Radiative Transfer and Transient Characteristics for Multilayer Biological Tissue

    Directory of Open Access Journals (Sweden)

    S. Yu. Makarov

    2014-01-01

    and scattering medium. The main absorbers in visible and near-IR spectral range in this case are melanin (contains in pigmented epidermis and blood hemoglobin. Scattering is defined both by the fibrous structure of skin, and by the cell organellеs. The optical characteristics, absorbing and scattering properties of skin, and subcutaneous tissues are rather well studied [6][7][8].The aim of modelling was to have both the stationary distribution of light radiation in multilayer biological tissue and the transitional characteristics corresponding to such biological tissue structure. These characteristics may appear when a biological tissue is subjected to short laser pulses. Discovering of such characteristics and their analysis allows us to formulate a criterion for the validity of stationary models of radiation transfer in multilayer biological tissue. As to transitional characteristics (i.e. time-allowed absorption coefficients in layers, the standard algorithm of the Monte-Carlo method [9][10] was modified to take into consideration a final speed value of light distribution in layers. In such a way, in particular, it was found that time about 60 Ps (for radiation with the wavelength of 633 nm is necessary to obtain the steady-state (stationary values of the absorbed power in skin and subcutaneous tissues. The entire modelling process (based on the i7 processor took about 30 minutes, thus the number of the traceable photons made 100 million.The results obtained for a beam of infinitesimal diameter allowed us to find the solution on distribution of light energy in biological tissue for a laser beam of a final width with a Gaussian profile of intensity. For this purpose, was used the mathematical apparatus of Green function. Its digital representation in this case is a modelling result for a beam of infinitesimal diameter. Since indexes of refraction of the adjacent layers in model were specified to be equal, the received function of integrated intensity for a Gaussian

  2. Introducing Systems Biology to Bioscience students through mathematical modelling. A practical module

    Directory of Open Access Journals (Sweden)

    Néstor V. Torres Darias

    2013-11-01

    Full Text Available Systems Biology, one of the current approaches to the understanding of living things, aims to understand the behaviour of living systems through the creation of mathematical models that integrate the available knowledge of the system’s component parts and the relations among them. Accordingly, model building should play a central part in any biology degree program. One difficulty that we face when confronted with this task, however, is that the mathematical background of undergraduate students is very often deficient in essential concepts required for dynamic mathematical modelling. In this practical module, students are introduced to the basic techniques of mathematical modelling and computer simulation from a Systems Biology perspective.

  3. Experiment design through dynamical characterisation of non-linear systems biology models utilising sparse grids.

    Science.gov (United States)

    Donahue, M M; Buzzard, G T; Rundell, A E

    2010-07-01

    The sparse grid-based experiment design algorithm sequentially selects an experimental design point to discriminate between hypotheses for given experimental conditions. Sparse grids efficiently screen the global uncertain parameter space to identify acceptable parameter subspaces. Clustering the located acceptable parameter vectors by the similarity of the simulated model trajectories characterises the data-compatible model dynamics. The experiment design algorithm capitalizes on the diversity of the experimentally distinguishable system output dynamics to select the design point that best discerns between competing model-structure and parameter-encoded hypotheses. As opposed to designing the experiments to explicitly reduce uncertainty in the model parameters, this approach selects design points to differentiate between dynamical behaviours. This approach further differs from other experimental design methods in that it simultaneously addresses both parameter- and structural-based uncertainty that is applicable to some ill-posed problems where the number of uncertain parameters exceeds the amount of data, places very few requirements on the model type, available data and a priori parameter estimates, and is performed over the global uncertain parameter space. The experiment design algorithm is demonstrated on a mitogen-activated protein kinase cascade model. The results show that system dynamics are highly uncertain with limited experimental data. Nevertheless, the algorithm requires only three additional experimental data points to simultaneously discriminate between possible model structures and acceptable parameter values. This sparse grid-based experiment design process provides a systematic and computationally efficient exploration over the entire uncertain parameter space of potential model structures to resolve the uncertainty in the non-linear systems biology model dynamics.

  4. Societal Risk Evaluation Scheme (SRES: Scenario-Based Multi-Criteria Evaluation of Synthetic Biology Applications.

    Directory of Open Access Journals (Sweden)

    Christopher L Cummings

    Full Text Available Synthetic biology (SB applies engineering principles to biology for the construction of novel biological systems designed for useful purposes. From an oversight perspective, SB products come with significant uncertainty. Yet there is a need to anticipate and prepare for SB applications before deployment. This study develops a Societal Risk Evaluation Scheme (SRES in order to advance methods for anticipatory governance of emerging technologies such as SB. The SRES is based upon societal risk factors that were identified as important through a policy Delphi study. These factors range from those associated with traditional risk assessment, such as health and environmental consequences, to broader features of risk such as those associated with reversibility, manageability, anticipated levels of public concern, and uncertainty. A multi-disciplinary panel with diverse perspectives and affiliations assessed four case studies of SB using the SRES. Rankings of the SRES components are compared within and across the case studies. From these comparisons, we found levels of controllability and familiarity associated with the cases to be important for overall SRES rankings. From a theoretical standpoint, this study illustrates the applicability of the psychometric paradigm to evaluating SB cases. In addition, our paper describes how the SRES can be incorporated into anticipatory governance models as a screening tool to prioritize research, information collection, and dialogue in the face of the limited capacity of governance systems. To our knowledge, this is the first study to elicit data on specific cases of SB with the goal of developing theory and tools for risk governance.

  5. Model-based biosignal interpretation.

    Science.gov (United States)

    Andreassen, S

    1994-03-01

    Two relatively new approaches to model-based biosignal interpretation, qualitative simulation and modelling by causal probabilistic networks, are compared to modelling by differential equations. A major problem in applying a model to an individual patient is the estimation of the parameters. The available observations are unlikely to allow a proper estimation of the parameters, and even if they do, the task appears to have exponential computational complexity if the model is non-linear. Causal probabilistic networks have both differential equation models and qualitative simulation as special cases, and they can provide both Bayesian and maximum-likelihood parameter estimates, in most cases in much less than exponential time. In addition, they can calculate the probabilities required for a decision-theoretical approach to medical decision support. The practical applicability of causal probabilistic networks to real medical problems is illustrated by a model of glucose metabolism which is used to adjust insulin therapy in type I diabetic patients.

  6. Indoor Air Nuclear, Biological, and Chemical Health Modeling and Assessment System

    Energy Technology Data Exchange (ETDEWEB)

    Stenner, Robert D.; Hadley, Donald L.; Armstrong, Peter R.; Buck, John W.; Hoopes, Bonnie L.; Janus, Michael C.

    2001-03-01

    Indoor air quality effects on human health are of increasing concern to public health agencies and building owners. The prevention and treatment of 'sick building' syndrome and the spread of air-borne diseases in hospitals, for example, are well known priorities. However, increasing attention is being directed to the vulnerability of our public buildings/places, public security and national defense facilities to terrorist attack or the accidental release of air-borne biological pathogens, harmful chemicals, or radioactive contaminants. The Indoor Air Nuclear, Biological, and Chemical Health Modeling and Assessment System (IA-NBC-HMAS) was developed to serve as a health impact analysis tool for use in addressing these concerns. The overall goal was to develop a user-friendly fully functional prototype Health Modeling and Assessment system, which will operate under the PNNL FRAMES system for ease of use and to maximize its integration with other modeling and assessment capabilities accessible within the FRAMES system (e.g., ambient air fate and transport models, water borne fate and transport models, Physiologically Based Pharmacokinetic models, etc.). The prototype IA-NBC-HMAS is designed to serve as a functional Health Modeling and Assessment system that can be easily tailored to meet specific building analysis needs of a customer. The prototype system was developed and tested using an actual building (i.e., the Churchville Building located at the Aberdeen Proving Ground) and release scenario (i.e., the release and measurement of tracer materials within the building) to ensure realism and practicality in the design and development of the prototype system. A user-friendly "demo" accompanies this report to allow the reader the opportunity for a "hands on" review of the prototype system's capability.

  7. Model-based machine learning.

    Science.gov (United States)

    Bishop, Christopher M

    2013-02-13

    Several decades of research in the field of machine learning have resulted in a multitude of different algorithms for solving a broad range of problems. To tackle a new application, a researcher typically tries to map their problem onto one of these existing methods, often influenced by their familiarity with specific algorithms and by the availability of corresponding software implementations. In this study, we describe an alternative methodology for applying machine learning, in which a bespoke solution is formulated for each new application. The solution is expressed through a compact modelling language, and the corresponding custom machine learning code is then generated automatically. This model-based approach offers several major advantages, including the opportunity to create highly tailored models for specific scenarios, as well as rapid prototyping and comparison of a range of alternative models. Furthermore, newcomers to the field of machine learning do not have to learn about the huge range of traditional methods, but instead can focus their attention on understanding a single modelling environment. In this study, we show how probabilistic graphical models, coupled with efficient inference algorithms, provide a very flexible foundation for model-based machine learning, and we outline a large-scale commercial application of this framework involving tens of millions of users. We also describe the concept of probabilistic programming as a powerful software environment for model-based machine learning, and we discuss a specific probabilistic programming language called Infer.NET, which has been widely used in practical applications.

  8. Multivariate statistical modelling based on generalized linear models

    CERN Document Server

    Fahrmeir, Ludwig

    1994-01-01

    This book is concerned with the use of generalized linear models for univariate and multivariate regression analysis. Its emphasis is to provide a detailed introductory survey of the subject based on the analysis of real data drawn from a variety of subjects including the biological sciences, economics, and the social sciences. Where possible, technical details and proofs are deferred to an appendix in order to provide an accessible account for non-experts. Topics covered include: models for multi-categorical responses, model checking, time series and longitudinal data, random effects models, and state-space models. Throughout, the authors have taken great pains to discuss the underlying theoretical ideas in ways that relate well to the data at hand. As a result, numerous researchers whose work relies on the use of these models will find this an invaluable account to have on their desks. "The basic aim of the authors is to bring together and review a large part of recent advances in statistical modelling of m...

  9. Bayesian model accounting for within-class biological variability in Serial Analysis of Gene Expression (SAGE

    Directory of Open Access Journals (Sweden)

    Brentani Helena

    2004-08-01

    Full Text Available Abstract Background An important challenge for transcript counting methods such as Serial Analysis of Gene Expression (SAGE, "Digital Northern" or Massively Parallel Signature Sequencing (MPSS, is to carry out statistical analyses that account for the within-class variability, i.e., variability due to the intrinsic biological differences among sampled individuals of the same class, and not only variability due to technical sampling error. Results We introduce a Bayesian model that accounts for the within-class variability by means of mixture distribution. We show that the previously available approaches of aggregation in pools ("pseudo-libraries" and the Beta-Binomial model, are particular cases of the mixture model. We illustrate our method with a brain tumor vs. normal comparison using SAGE data from public databases. We show examples of tags regarded as differentially expressed with high significance if the within-class variability is ignored, but clearly not so significant if one accounts for it. Conclusion Using available information about biological replicates, one can transform a list of candidate transcripts showing differential expression to a more reliable one. Our method is freely available, under GPL/GNU copyleft, through a user friendly web-based on-line tool or as R language scripts at supplemental web-site.

  10. Bayesian model accounting for within-class biological variability in Serial Analysis of Gene Expression (SAGE).

    Science.gov (United States)

    Vêncio, Ricardo Z N; Brentani, Helena; Patrão, Diogo F C; Pereira, Carlos A B

    2004-08-31

    An important challenge for transcript counting methods such as Serial Analysis of Gene Expression (SAGE), "Digital Northern" or Massively Parallel Signature Sequencing (MPSS), is to carry out statistical analyses that account for the within-class variability, i.e., variability due to the intrinsic biological differences among sampled individuals of the same class, and not only variability due to technical sampling error. We introduce a Bayesian model that accounts for the within-class variability by means of mixture distribution. We show that the previously available approaches of aggregation in pools ("pseudo-libraries") and the Beta-Binomial model, are particular cases of the mixture model. We illustrate our method with a brain tumor vs. normal comparison using SAGE data from public databases. We show examples of tags regarded as differentially expressed with high significance if the within-class variability is ignored, but clearly not so significant if one accounts for it. Using available information about biological replicates, one can transform a list of candidate transcripts showing differential expression to a more reliable one. Our method is freely available, under GPL/GNU copyleft, through a user friendly web-based on-line tool or as R language scripts at supplemental web-site.

  11. Modelling effective dielectric properties of materials containing diverse types of biological cells

    International Nuclear Information System (INIS)

    Huclova, Sonja; Froehlich, Juerg; Erni, Daniel

    2010-01-01

    An efficient and versatile numerical method for the generation of different realistically shaped biological cells is developed. This framework is used to calculate the dielectric spectra of materials containing specific types of biological cells. For the generation of the numerical models of the cells a flexible parametrization method based on the so-called superformula is applied including the option of obtaining non-axisymmetric shapes such as box-shaped cells and even shapes corresponding to echinocytes. The dielectric spectra of effective media containing various cell morphologies are calculated focusing on the dependence of the spectral features on the cell shape. The numerical method is validated by comparing a model of spherical inclusions at a low volume fraction with the analytical solution obtained by the Maxwell-Garnett mixing formula, resulting in good agreement. Our simulation data for different cell shapes suggest that around 1MHz the effective dielectric properties of different cell shapes at different volume fractions significantly deviate from the spherical case. The most pronounced change exhibits ε eff between 0.1 and 1 MHz with a deviation of up to 35% for a box-shaped cell and 15% for an echinocyte compared with the sphere at a volume fraction of 0.4. This hampers the unique interpretation of changes in cellular features measured by dielectric spectroscopy when simplified material models are used.

  12. Perceptron-like computation based on biologically-inspired neurons with heterosynaptic mechanisms

    Science.gov (United States)

    Kaluza, Pablo; Urdapilleta, Eugenio

    2014-10-01

    Perceptrons are one of the fundamental paradigms in artificial neural networks and a key processing scheme in supervised classification tasks. However, the algorithm they provide is given in terms of unrealistically simple processing units and connections and therefore, its implementation in real neural networks is hard to be fulfilled. In this work, we present a neural circuit able to perform perceptron's computation based on realistic models of neurons and synapses. The model uses Wang-Buzsáki neurons with coupling provided by axodendritic and axoaxonic synapses (heterosynapsis). The main characteristics of the feedforward perceptron operation are conserved, which allows to combine both approaches: whereas the classical artificial system can be used to learn a particular problem, its solution can be directly implemented in this neural circuit. As a result, we propose a biologically-inspired system able to work appropriately in a wide range of frequencies and system parameters, while keeping robust to noise and error.

  13. Energy-based control for a biologically inspired hexapod robot with rolling locomotion

    Directory of Open Access Journals (Sweden)

    Takuma Nemoto

    2015-04-01

    Full Text Available This paper presents an approach to control rolling locomotion on the level ground with a biologically inspired hexapod robot. For controlling rolling locomotion, a controller which can compensate energy loss with rolling locomotion of the hexapod robot is designed based on its dynamic model. The dynamic model describes the rolling locomotion which is limited to planar one by an assumption that the hexapod robot does not fall down while rolling and influences due to collision and contact with the ground, and it is applied for computing the mechanical energy of the hexapod robot and a plant for a numerical simulation. The numerical simulation of the rolling locomotion on the level ground verifies the effectiveness of the proposed controller. The simulation results show that the hexapod robot can perform the rolling locomotion with the proposed controller. In conclusion, it is shown that the proposed control approach is effective in achieving the rolling locomotion on the level ground.

  14. The Development of Environment based Textbook in Biology Course at Tribhuwana Tunggadewi University

    Directory of Open Access Journals (Sweden)

    Nugroho Aji Prasetiyo

    2017-03-01

    Full Text Available Environmental issues are rooted in human behavior is often found in everyday life, one contributing factor was not maximal the environment learning outcomes in the education. The purpose of this study is to develop environment based textbook in Biology course suited to the needs and character of college students. The development model used in this research and development are modified Thiagarajan et al model consists of three stages: define, design, and develop. The technique of collecting data using questionnaires validation for experts, and small-scale trials. The result of the development of textbooks showing the average results of the validation and testing is in the category with a good fit for use in accordance with the table eligibility criteria and product revision level.

  15. Semantic Models of Sentences with Verbs of Motion in Standard Language and in Scientific Language Used in Biology

    Directory of Open Access Journals (Sweden)

    Vita Banionytė

    2016-06-01

    Full Text Available The semantic models of sentences with verbs of motion in German standard language and in scientific language used in biology are analyzed in the article. In its theoretic part it is affirmed that the article is based on the semantic theory of the sentence. This theory, in its turn, is grounded on the correlation of semantic predicative classes and semantic roles. The combination of semantic predicative classes and semantic roles is expressed by the main semantic formula – proposition. In its practical part the differences between the semantic models of standard and scientific language used in biology are explained. While modelling sentences with verbs of motion, two groups of semantic models of sentences are singled out: that of action (Handlung and process (Vorgang. The analysis shows that the semantic models of sentences with semantic action predicatives dominate in the text of standard language while the semantic models of sentences with semantic process predicatives dominate in the texts of scientific language used in biology. The differences how the doer and direction are expressed in standard and in scientific language are clearly seen and the semantic cases (Agens, Patiens, Direktiv1 help to determine that. It is observed that in scientific texts of high level of specialization (biology science in contrast to popular scientific literature models of sentences with moving verbs are usually seldom found. They are substituted by denominative constructions. In conclusions it is shown that this analysis can be important in methodics, especially planning material for teaching professional-scientific language.

  16. Computational systems biology and dose-response modeling in relation to new directions in toxicity testing.

    Science.gov (United States)

    Zhang, Qiang; Bhattacharya, Sudin; Andersen, Melvin E; Conolly, Rory B

    2010-02-01

    The new paradigm envisioned for toxicity testing in the 21st century advocates shifting from the current animal-based testing process to a combination of in vitro cell-based studies, high-throughput techniques, and in silico modeling. A strategic component of the vision is the adoption of the systems biology approach to acquire, analyze, and interpret toxicity pathway data. As key toxicity pathways are identified and their wiring details elucidated using traditional and high-throughput techniques, there is a pressing need to understand their qualitative and quantitative behaviors in response to perturbation by both physiological signals and exogenous stressors. The complexity of these molecular networks makes the task of understanding cellular responses merely by human intuition challenging, if not impossible. This process can be aided by mathematical modeling and computer simulation of the networks and their dynamic behaviors. A number of theoretical frameworks were developed in the last century for understanding dynamical systems in science and engineering disciplines. These frameworks, which include metabolic control analysis, biochemical systems theory, nonlinear dynamics, and control theory, can greatly facilitate the process of organizing, analyzing, and understanding toxicity pathways. Such analysis will require a comprehensive examination of the dynamic properties of "network motifs"--the basic building blocks of molecular circuits. Network motifs like feedback and feedforward loops appear repeatedly in various molecular circuits across cell types and enable vital cellular functions like homeostasis, all-or-none response, memory, and biological rhythm. These functional motifs and associated qualitative and quantitative properties are the predominant source of nonlinearities observed in cellular dose response data. Complex response behaviors can arise from toxicity pathways built upon combinations of network motifs. While the field of computational cell

  17. Diploid biological evolution models with general smooth fitness landscapes and recombination.

    Science.gov (United States)

    Saakian, David B; Kirakosyan, Zara; Hu, Chin-Kun

    2008-06-01

    Using a Hamilton-Jacobi equation approach, we obtain analytic equations for steady-state population distributions and mean fitness functions for Crow-Kimura and Eigen-type diploid biological evolution models with general smooth hypergeometric fitness landscapes. Our numerical solutions of diploid biological evolution models confirm the analytic equations obtained. We also study the parallel diploid model for the simple case of recombination and calculate the variance of distribution, which is consistent with numerical results.

  18. Fuzzy method of recognition of high molecular substances in evidence-based biology

    Science.gov (United States)

    Olevskyi, V. I.; Smetanin, V. T.; Olevska, Yu. B.

    2017-10-01

    Nowadays modern requirements to achieving reliable results along with high quality of researches put mathematical analysis methods of results at the forefront. Because of this, evidence-based methods of processing experimental data have become increasingly popular in the biological sciences and medicine. Their basis is meta-analysis, a method of quantitative generalization of a large number of randomized trails contributing to a same special problem, which are often contradictory and performed by different authors. It allows identifying the most important trends and quantitative indicators of the data, verification of advanced hypotheses and discovering new effects in the population genotype. The existing methods of recognizing high molecular substances by gel electrophoresis of proteins under denaturing conditions are based on approximate methods for comparing the contrast of electrophoregrams with a standard solution of known substances. We propose a fuzzy method for modeling experimental data to increase the accuracy and validity of the findings of the detection of new proteins.

  19. Multiscale models in mechano and tumor biology modeling, homogenization, and applications

    CERN Document Server

    Penta, Raimondo; Lang, Jens

    2017-01-01

    This book presents and discusses the state of the art and future perspectives in mathematical modeling and homogenization techniques with the focus on addressing key physiological issues in the context of multiphase healthy and malignant biological materials. The highly interdisciplinary content brings together contributions from scientists with complementary areas of expertise, such as pure and applied mathematicians, engineers, and biophysicists. The book also features the lecture notes from a half-day introductory course on asymptotic homogenization. These notes are suitable for undergraduate mathematics or physics students, while the other chapters are aimed at graduate students and researchers.

  20. Biologically constrained optimization based cell membrane segmentation in C. elegans embryos.

    Science.gov (United States)

    Azuma, Yusuke; Onami, Shuichi

    2017-06-19

    Recent advances in bioimaging and automated analysis methods have enabled the large-scale systematic analysis of cellular dynamics during the embryonic development of Caenorhabditis elegans. Most of these analyses have focused on cell lineage tracing rather than cell shape dynamics. Cell shape analysis requires cell membrane segmentation, which is challenging because of insufficient resolution and image quality. This problem is currently solved by complicated segmentation methods requiring laborious and time consuming parameter adjustments. Our new framework BCOMS (Biologically Constrained Optimization based cell Membrane Segmentation) automates the extraction of the cell shape of C. elegans embryos. Both the segmentation and evaluation processes are automated. To automate the evaluation, we solve an optimization problem under biological constraints. The performance of BCOMS was validated against a manually created ground truth of the 24-cell stage embryo. The average deviation of 25 cell shape features was 5.6%. The deviation was mainly caused by membranes parallel to the focal planes, which either contact the surfaces of adjacent cells or make no contact with other cells. Because segmentation of these membranes was difficult even by manual inspection, the automated segmentation was sufficiently accurate for cell shape analysis. As the number of manually created ground truths is necessarily limited, we compared the segmentation results between two adjacent time points. Across all cells and all cell cycles, the average deviation of the 25 cell shape features was 4.3%, smaller than that between the automated segmentation result and ground truth. BCOMS automated the accurate extraction of cell shapes in developing C. elegans embryos. By replacing image processing parameters with easily adjustable biological constraints, BCOMS provides a user-friendly framework. The framework is also applicable to other model organisms. Creating the biological constraints is a

  1. Event-based text mining for biology and functional genomics.

    Science.gov (United States)

    Ananiadou, Sophia; Thompson, Paul; Nawaz, Raheel; McNaught, John; Kell, Douglas B

    2015-05-01

    The assessment of genome function requires a mapping between genome-derived entities and biochemical reactions, and the biomedical literature represents a rich source of information about reactions between biological components. However, the increasingly rapid growth in the volume of literature provides both a challenge and an opportunity for researchers to isolate information about reactions of interest in a timely and efficient manner. In response, recent text mining research in the biology domain has been largely focused on the identification and extraction of 'events', i.e. categorised, structured representations of relationships between biochemical entities, from the literature. Functional genomics analyses necessarily encompass events as so defined. Automatic event extraction systems facilitate the development of sophisticated semantic search applications, allowing researchers to formulate structured queries over extracted events, so as to specify the exact types of reactions to be retrieved. This article provides an overview of recent research into event extraction. We cover annotated corpora on which systems are trained, systems that achieve state-of-the-art performance and details of the community shared tasks that have been instrumental in increasing the quality, coverage and scalability of recent systems. Finally, several concrete applications of event extraction are covered, together with emerging directions of research. © The Author 2014. Published by Oxford University Press.

  2. Event-based text mining for biology and functional genomics

    Science.gov (United States)

    Thompson, Paul; Nawaz, Raheel; McNaught, John; Kell, Douglas B.

    2015-01-01

    The assessment of genome function requires a mapping between genome-derived entities and biochemical reactions, and the biomedical literature represents a rich source of information about reactions between biological components. However, the increasingly rapid growth in the volume of literature provides both a challenge and an opportunity for researchers to isolate information about reactions of interest in a timely and efficient manner. In response, recent text mining research in the biology domain has been largely focused on the identification and extraction of ‘events’, i.e. categorised, structured representations of relationships between biochemical entities, from the literature. Functional genomics analyses necessarily encompass events as so defined. Automatic event extraction systems facilitate the development of sophisticated semantic search applications, allowing researchers to formulate structured queries over extracted events, so as to specify the exact types of reactions to be retrieved. This article provides an overview of recent research into event extraction. We cover annotated corpora on which systems are trained, systems that achieve state-of-the-art performance and details of the community shared tasks that have been instrumental in increasing the quality, coverage and scalability of recent systems. Finally, several concrete applications of event extraction are covered, together with emerging directions of research. PMID:24907365

  3. Formal modeling and analysis of ER-α associated Biological Regulatory Network in breast cancer

    Directory of Open Access Journals (Sweden)

    Samra Khalid

    2016-10-01

    Full Text Available Background Breast cancer (BC is one of the leading cause of death among females worldwide. The increasing incidence of BC is due to various genetic and environmental changes which lead to the disruption of cellular signaling network(s. It is a complex disease in which several interlinking signaling cascades play a crucial role in establishing a complex regulatory network. The logical modeling approach of René Thomas has been applied to analyze the behavior of estrogen receptor-alpha (ER-α associated Biological Regulatory Network (BRN for a small part of complex events that leads to BC metastasis. Methods A discrete model was constructed using the kinetic logic formalism and its set of logical parameters were obtained using the model checking technique implemented in the SMBioNet software which is consistent with biological observations. The discrete model was further enriched with continuous dynamics by converting it into an equivalent Petri Net (PN to analyze the logical parameters of the involved entities. Results In-silico based discrete and continuous modeling of ER-α associated signaling network involved in BC provides information about behaviors and gene-gene interaction in detail. The dynamics of discrete model revealed, imperative behaviors represented as cyclic paths and trajectories leading to pathogenic states such as metastasis. Results suggest that the increased expressions of receptors ER-α, IGF-1R and EGFR slow down the activity of tumor suppressor genes (TSGs such as BRCA1, p53 and Mdm2 which can lead to metastasis. Therefore, IGF-1R and EGFR are considered as important inhibitory targets to control the metastasis in BC. Conclusion The in-silico approaches allow us to increase our understanding of the functional properties of living organisms. It opens new avenues of investigations of multiple inhibitory targets (ER-α, IGF-1R and EGFR for wet lab experiments as well as provided valuable insights in the treatment of cancers

  4. Systems Modelling and the Development of Coherent Understanding of Cell Biology

    Science.gov (United States)

    Verhoeff, Roald P.; Waarlo, Arend Jan; Boersma, Kerst Th.

    2008-01-01

    This article reports on educational design research concerning a learning and teaching strategy for cell biology in upper-secondary education introducing "systems modelling" as a key competence. The strategy consists of four modelling phases in which students subsequently develop models of free-living cells, a general two-dimensional model of…

  5. Using multi-criteria analysis of simulation models to understand complex biological systems

    Science.gov (United States)

    Maureen C. Kennedy; E. David. Ford

    2011-01-01

    Scientists frequently use computer-simulation models to help solve complex biological problems. Typically, such models are highly integrated, they produce multiple outputs, and standard methods of model analysis are ill suited for evaluating them. We show how multi-criteria optimization with Pareto optimality allows for model outputs to be compared to multiple system...

  6. Efficient Estimation of the Robustness Region of Biological Models with Oscillatory Behavior

    NARCIS (Netherlands)

    Apri, M.; Molenaar, J.; Gee, de M.; Voorn, van G.A.K.

    2010-01-01

    Robustness is an essential feature of biological systems, and any mathematical model that describes such a system should reflect this feature. Especially, persistence of oscillatory behavior is an important issue. A benchmark model for this phenomenon is the Laub-Loomis model, a nonlinear model for

  7. Teaching Real Data Interpretation with Models (TRIM): Analysis of Student Dialogue in a Large-Enrollment Cell and Developmental Biology Course

    Science.gov (United States)

    Zagallo, Patricia; Meddleton, Shanice; Bolger, Molly S.

    2016-01-01

    We present our design for a cell biology course to integrate content with scientific practices, specifically data interpretation and model-based reasoning. A 2-year research project within this course allowed us to understand how students interpret authentic biological data in this setting. Through analysis of written work, we measured the extent…

  8. Not just a theory--the utility of mathematical models in evolutionary biology.

    Science.gov (United States)

    Servedio, Maria R; Brandvain, Yaniv; Dhole, Sumit; Fitzpatrick, Courtney L; Goldberg, Emma E; Stern, Caitlin A; Van Cleve, Jeremy; Yeh, D Justin

    2014-12-01

    Progress in science often begins with verbal hypotheses meant to explain why certain biological phenomena exist. An important purpose of mathematical models in evolutionary research, as in many other fields, is to act as “proof-of-concept” tests of the logic in verbal explanations, paralleling the way in which empirical data are used to test hypotheses. Because not all subfields of biology use mathematics for this purpose, misunderstandings of the function of proof-of-concept modeling are common. In the hope of facilitating communication, we discuss the role of proof-of-concept modeling in evolutionary biology.

  9. Not just a theory--the utility of mathematical models in evolutionary biology.

    Directory of Open Access Journals (Sweden)

    Maria R Servedio

    2014-12-01

    Full Text Available Progress in science often begins with verbal hypotheses meant to explain why certain biological phenomena exist. An important purpose of mathematical models in evolutionary research, as in many other fields, is to act as “proof-of-concept” tests of the logic in verbal explanations, paralleling the way in which empirical data are used to test hypotheses. Because not all subfields of biology use mathematics for this purpose, misunderstandings of the function of proof-of-concept modeling are common. In the hope of facilitating communication, we discuss the role of proof-of-concept modeling in evolutionary biology.

  10. How to Build a Course in Mathematical-Biological Modeling: Content and Processes for Knowledge and Skill

    Science.gov (United States)

    Hoskinson, Anne-Marie

    2010-01-01

    Biological problems in the twenty-first century are complex and require mathematical insight, often resulting in mathematical models of biological systems. Building mathematical-biological models requires cooperation among biologists and mathematicians, and mastery of building models. A new course in mathematical modeling presented the opportunity…

  11. The development of peptide-based interfacial biomaterials for generating biological functionality on the surface of bioinert materials.

    Science.gov (United States)

    Meyers, Steven R; Khoo, Xiaojuan; Huang, Xin; Walsh, Elisabeth B; Grinstaff, Mark W; Kenan, Daniel J

    2009-01-01

    Biomaterials used in implants have traditionally been selected based on their mechanical properties, chemical stability, and biocompatibility. However, the durability and clinical efficacy of implantable biomedical devices remain limited in part due to the absence of appropriate biological interactions at the implant interface and the lack of integration into adjacent tissues. Herein, we describe a robust peptide-based coating technology capable of modifying the surface of existing biomaterials and medical devices through the non-covalent binding of modular biofunctional peptides. These peptides contain at least one material binding sequence and at least one biologically active sequence and thus are termed, "Interfacial Biomaterials" (IFBMs). IFBMs can simultaneously bind the biomaterial surface while endowing it with desired biological functionalities at the interface between the material and biological realms. We demonstrate the capabilities of model IFBMs to convert native polystyrene, a bioinert surface, into a bioactive surface that can support a range of cell activities. We further distinguish between simple cell attachment with insufficient integrin interactions, which in some cases can adversely impact downstream biology, versus biologically appropriate adhesion, cell spreading, and cell survival mediated by IFBMs. Moreover, we show that we can use the coating technology to create spatially resolved patterns of fluorophores and cells on substrates and that these patterns retain their borders in culture.

  12. Methods of Model Reduction for Large-Scale Biological Systems: A Survey of Current Methods and Trends.

    Science.gov (United States)

    Snowden, Thomas J; van der Graaf, Piet H; Tindall, Marcus J

    2017-07-01

    Complex models of biochemical reaction systems have become increasingly common in the systems biology literature. The complexity of such models can present a number of obstacles for their practical use, often making problems difficult to intuit or computationally intractable. Methods of model reduction can be employed to alleviate the issue of complexity by seeking to eliminate those portions of a reaction network that have little or no effect upon the outcomes of interest, hence yielding simplified systems that retain an accurate predictive capacity. This review paper seeks to provide a brief overview of a range of such methods and their application in the context of biochemical reaction network models. To achieve this, we provide a brief mathematical account of the main methods including timescale exploitation approaches, reduction via sensitivity analysis, optimisation methods, lumping, and singular value decomposition-based approaches. Methods are reviewed in the context of large-scale systems biology type models, and future areas of research are briefly discussed.

  13. Caenorhabditis elegans - A model system for space biology studies

    Science.gov (United States)

    Johnson, Thomas E.; Nelson, Gregory A.

    1991-01-01

    The utility of the nematode Caenorhabditis elegans in studies spanning aspects of development, aging, and radiobiology is reviewed. These topics are interrelated via cellular and DNA repair processes especially in the context of oxidative stress and free-radical metabolism. The relevance of these research topics to problems in space biology is discussed and properties of the space environment are outlined. Exposure to the space-flight environment can induce rapid changes in living systems that are similar to changes occurring during aging; manipulation of these environmental parameters may represent an experimental strategy for studies of development and senescence. The current and future opportunities for such space-flight experimentation are presented.

  14. Computer-Based Modeling Environments

    Science.gov (United States)

    1989-01-01

    1988). "An introduction to graph-based modeling Rich. E. (1983). Artificial Inteligence , McGraw-Hill, New York. systems", Working Paper 88-10-2...Hall, J., S. Lippman, and J. McCall. "Expected Utility Maximizing Job Search," Chapter 7 of Studies in the Economics of Search, 1979, North-Holland. WMSI...The same shape has been used theory, as knowledge representation in artificial for data sources and analytical models because, at intelligence, and as

  15. Digital learning material for experimental design and model building in molecular biology

    NARCIS (Netherlands)

    Aegerter-Wilmsen, T.

    2005-01-01

    Designing experimental approaches is a major cognitive skill in molecular biology research, and building models, including quantitative ones, is a cognitive skill which is rapidly gaining importance. Since molecular biology education at university level is aimed at educating future researchers, we

  16. Using probabilistic graphical models to reconstruct biological networks and linkage maps

    NARCIS (Netherlands)

    Wang, Huange

    2017-01-01

    Probabilistic graphical models (PGMs) offer a conceptual architecture where biological and mathematical objects can be expressed with a common, intuitive formalism. This facilitates the joint development of statistical and computational tools for quantitative analysis of biological data. Over the

  17. An Introduction to Biological Modeling Using Coin Flips to Predict the Outcome of a Diffusion Activity

    Science.gov (United States)

    Butcher, Greg Q.; Rodriguez, Juan; Chirhart, Scott; Messina, Troy C.

    2016-01-01

    In order to increase students' awareness for and comfort with mathematical modeling of biological processes, and increase their understanding of diffusion, the following lab was developed for use in 100-level, majors/non-majors biology and neuroscience courses. The activity begins with generation of a data set that uses coin-flips to replicate…

  18. Converting biomolecular modelling data based on an XML representation.

    Science.gov (United States)

    Sun, Yudong; McKeever, Steve

    2008-08-25

    Biomolecular modelling has provided computational simulation based methods for investigating biological processes from quantum chemical to cellular levels. Modelling such microscopic processes requires atomic description of a biological system and conducts in fine timesteps. Consequently the simulations are extremely computationally demanding. To tackle this limitation, different biomolecular models have to be integrated in order to achieve high-performance simulations. The integration of diverse biomolecular models needs to convert molecular data between different data representations of different models. This data conversion is often non-trivial, requires extensive human input and is inevitably error prone. In this paper we present an automated data conversion method for biomolecular simulations between molecular dynamics and quantum mechanics/molecular mechanics models. Our approach is developed around an XML data representation called BioSimML (Biomolecular Simulation Markup Language). BioSimML provides a domain specific data representation for biomolecular modelling which can effciently support data interoperability between different biomolecular simulation models and data formats.

  19. Fluid models and simulations of biological cell phenomena

    Science.gov (United States)

    Greenspan, H. P.

    1982-01-01

    The dynamics of coated droplets are examined within the context of biofluids. Of specific interest is the manner in which the shape of a droplet, the motion within it as well as that of aggregates of droplets can be controlled by the modulation of surface properties and the extent to which such fluid phenomena are an intrinsic part of cellular processes. From the standpoint of biology, an objective is to elucidate some of the general dynamical features that affect the disposition of an entire cell, cell colonies and tissues. Conventionally averaged field variables of continuum mechanics are used to describe the overall global effects which result from the myriad of small scale molecular interactions. An attempt is made to establish cause and effect relationships from correct dynamical laws of motion rather than by what may have been unnecessary invocation of metabolic or life processes. Several topics are discussed where there are strong analogies droplets and cells including: encapsulated droplets/cell membranes; droplet shape/cell shape; adhesion and spread of a droplet/cell motility and adhesion; and oams and multiphase flows/cell aggregates and tissues. Evidence is presented to show that certain concepts of continuum theory such as suface tension, surface free energy, contact angle, bending moments, etc. are relevant and applicable to the study of cell biology.

  20. Aspergilli: Models for systems biology in filamentous fungi

    DEFF Research Database (Denmark)

    Brandl, Julian; Andersen, Mikael Rørdam

    2017-01-01

    Aspergillus is a diverse genus of filamentous fungi including common house hold mold as well as human pathogens. More than 350 species are currently part of this genus and all their genomes are soon to be sequenced. The availability of this vast amount of data will allow for more in-depth underst......Aspergillus is a diverse genus of filamentous fungi including common house hold mold as well as human pathogens. More than 350 species are currently part of this genus and all their genomes are soon to be sequenced. The availability of this vast amount of data will allow for more in......-depth understanding of genetic traits governing desirable properties like enzyme production as well as the pathogenic potency of the organisms. In this review we give an overview of the systems biology research conducted in Aspergilli. This research has covered omics technologies like genomics, transcriptomics...... and proteomics where outstanding contributions are highlighted. From past developments it becomes apparent that CRISPR technology will speed up genetic research in the Aspergillus field. This speed up will allow for an increase in systems biology targeted research by accelerating data generation. The increase...

  1. Biologically-based signal processing system applied to noise removal for signal extraction

    Science.gov (United States)

    Fu, Chi Yung; Petrich, Loren I.

    2004-07-13

    The method and system described herein use a biologically-based signal processing system for noise removal for signal extraction. A wavelet transform may be used in conjunction with a neural network to imitate a biological system. The neural network may be trained using ideal data derived from physical principles or noiseless signals to determine to remove noise from the signal.

  2. Lack of Evolution Acceptance Inhibits Students' Negotiation of Biology-Based Socioscientific Issues

    Science.gov (United States)

    Fowler, S. R.; Zeidler, D. L.

    2016-01-01

    The purpose of this study was to explore science content used during college students' negotiation of biology-based socioscientific issues (SSI) and examine how it related to students' conceptual understanding and acceptance of biological evolution. The Socioscientific Issues Questionnaire (SSI-Q) was developed to measure depth of evolutionary…

  3. Comparison of hybridization-based and sequencing-based gene expression technologies on biological replicates.

    Science.gov (United States)

    Liu, Fang; Jenssen, Tor-Kristian; Trimarchi, Jeff; Punzo, Claudio; Cepko, Connie L; Ohno-Machado, Lucila; Hovig, Eivind; Kuo, Winston Patrick

    2007-06-07

    High-throughput systems for gene expression profiling have been developed and have matured rapidly through the past decade. Broadly, these can be divided into two categories: hybridization-based and sequencing-based approaches. With data from different technologies being accumulated, concerns and challenges are raised about the level of agreement across technologies. As part of an ongoing large-scale cross-platform data comparison framework, we report here a comparison based on identical samples between one-dye DNA microarray platforms and MPSS (Massively Parallel Signature Sequencing). The DNA microarray platforms generally provided highly correlated data, while moderate correlations between microarrays and MPSS were obtained. Disagreements between the two types of technologies can be attributed to limitations inherent to both technologies. The variation found between pooled biological replicates underlines the importance of exercising caution in identification of differential expression, especially for the purposes of biomarker discovery. Based on different principles, hybridization-based and sequencing-based technologies should be considered complementary to each other, rather than competitive alternatives for measuring gene expression, and currently, both are important tools for transcriptome profiling.

  4. Comparison of hybridization-based and sequencing-based gene expression technologies on biological replicates

    Directory of Open Access Journals (Sweden)

    Cepko Connie L

    2007-06-01

    Full Text Available Abstract Background High-throughput systems for gene expression profiling have been developed and have matured rapidly through the past decade. Broadly, these can be divided into two categories: hybridization-based and sequencing-based approaches. With data from different technologies being accumulated, concerns and challenges are raised about the level of agreement across technologies. As part of an ongoing large-scale cross-platform data comparison framework, we report here a comparison based on identical samples between one-dye DNA microarray platforms and MPSS (Massively Parallel Signature Sequencing. Results The DNA microarray platforms generally provided highly correlated data, while moderate correlations between microarrays and MPSS were obtained. Disagreements between the two types of technologies can be attributed to limitations inherent to both technologies. The variation found between pooled biological replicates underlines the importance of exercising caution in identification of differential expression, especially for the purposes of biomarker discovery. Conclusion Based on different principles, hybridization-based and sequencing-based technologies should be considered complementary to each other, rather than competitive alternatives for measuring gene expression, and currently, both are important tools for transcriptome profiling.

  5. Biological Characterization of an Improved Pyrrole-Based Colchicine Site Agent Identified through Structure-Based Design.

    Science.gov (United States)

    Rohena, Cristina C; Telang, Nakul S; Da, Chenxiao; Risinger, April L; Sikorski, James A; Kellogg, Glen E; Gupton, John T; Mooberry, Susan L

    2016-02-01

    A refined model of the colchicine site on tubulin was used to design an improved analog of the pyrrole parent compound, JG-03-14. The optimized compound, NT-7-16, was evaluated in biological assays that confirm that it has potent activities as a new colchicine site microtubule depolymerizer. NT-7-16 exhibits antiproliferative and cytotoxic activities against multiple cancer cell lines, with IC(50) values of 10-16 nM, and it is able to overcome drug resistance mediated by the expression of P-glycoprotein and the βIII isotype of tubulin. NT-7-16 initiated the concentration-dependent loss of cellular microtubules and caused the formation of abnormal mitotic spindles, leading to mitotic accumulation. The direct interaction of NT-7-16 with purified tubulin was confirmed, and it was more potent than combretastatin A-4 in these assays. Binding studies verified that NT-7-16 binds to tubulin within the colchicine site. The antitumor effects of NT-7-16 were evaluated in an MDA-MB-435 xenograft model and it had excellent activity at concentrations that were not toxic. A second compound, NT-9-21, which contains dichloro moieties in place of the 3,5-dibromo substituents of NT-7-16, had a poorer fit within the colchicine site as predicted by modeling and the Hydropathic INTeractions score. Biological evaluations showed that NT-9-21 has 10-fold lower potency than NT-7-16, confirming the modeling predictions. These studies highlight the value of the refined colchicine-site model and identify a new pyrrole-based colchicine-site agent with potent in vitro activities and promising in vivo antitumor actions. Copyright © 2016 by The American Society for Pharmacology and Experimental Therapeutics.

  6. Automated Bayesian model development for frequency detection in biological time series

    Directory of Open Access Journals (Sweden)

    Oldroyd Giles ED

    2011-06-01

    the requirement for uniformly sampled data. Biological time series often deviate significantly from the requirements of optimality for Fourier transformation. In this paper we present an alternative approach based on Bayesian inference. We show the value of placing spectral analysis in the framework of Bayesian inference and demonstrate how model comparison can automate this procedure.

  7. Cost-effectiveness simulation model of biologic strategies for treating to target rheumatoid arthritis in Germany.

    Science.gov (United States)

    Beresniak, Ariel; Baerwald, Christoph; Zeidler, Henning; Krüger, Klaus; Neubauer, Aljoscha S; Dupont, Danielle; Merkesdal, Sonja

    2013-01-01

    The treatment of active rheumatoid arthritis (RA) usually requires different therapeutic options used sequentially in case of an insufficient response (IR) to previous agents. Since there is a lack of clinical trials comparing biologic treatment sequences, simulation models might add to the understanding of optimal treatment sequences and their cost-effectiveness. The objective of this study was to assess the cost-effectiveness of different biologic treatment strategies in patients with an IR to anti-TNF agents, based on levels of disease activity from the German public payer's perspective. A cost-effectiveness sequential model was developed in accordance with local RA treatment strategies, using DAS28 scores as dichotomous effectiveness endpoints: achieving remission/no remission (RS/no RS) or a state of low disease activity (LDAS/no LDAS). Costs were estimated using resource utilisation data obtained from a large observational German cohort. Advanced simulations were conducted to assess the cost-effectiveness over 2 years of four sequential biologic strategies composed of up to 3 biologic agents, namely anti-TNF agents, abatacept or rituximab, in patients with moderate-to-severe active RA and an IR to at least one anti-TNF agent. Over two years, the biological sequence including abatacept after an IR to one anti-TNF agent appeared the most effective and cost-effective versus (vs.) use after two anti-TNF agents (€633 vs. €1,067/day in LDAS and €1,222 vs. €3,592/day in remission), and vs a similar sequence using rituximab (€633 vs. €728/day in LDAS and €1,222 vs. €1,812/day in remission). The sequence using a 3rd anti-TNF agent was less effective and cost-effective than the same sequence using abatacept (€2,000 vs. €1,067/day in LDAS and €6,623 vs. €3,592/day in remission). All differences were statistically significant (pcost-effective than similar sequences including rituximab or only cycled anti-TNF agents.

  8. Biological nitrogen and phosphorus removal in membrane bioreactors: model development and parameter estimation.

    Science.gov (United States)

    Cosenza, Alida; Mannina, Giorgio; Neumann, Marc B; Viviani, Gaspare; Vanrolleghem, Peter A

    2013-04-01

    Membrane bioreactors (MBR) are being increasingly used for wastewater treatment. Mathematical modeling of MBR systems plays a key role in order to better explain their characteristics. Several MBR models have been presented in the literature focusing on different aspects: biological models, models which include soluble microbial products (SMP), physical models able to describe the membrane fouling and integrated models which couple the SMP models with the physical models. However, only a few integrated models have been developed which take into account the relationships between membrane fouling and biological processes. With respect to biological phosphorus removal in MBR systems, due to the complexity of the process, practical use of the models is still limited. There is a vast knowledge (and consequently vast amount of data) on nutrient removal for conventional-activated sludge systems but only limited information on phosphorus removal for MBRs. Calibration of these complex integrated models still remains the main bottleneck to their employment. The paper presents an integrated mathematical model able to simultaneously describe biological phosphorus removal, SMP formation/degradation and physical processes which also include the removal of organic matter. The model has been calibrated with data collected in a UCT-MBR pilot plant, located at the Palermo wastewater treatment plant, applying a modified version of a recently developed calibration protocol. The calibrated model provides acceptable correspondence with experimental data and can be considered a useful tool for MBR design and operation.

  9. Benchmarking biological nutrient removal in wastewater treatment plants: influence of mathematical model assumptions.

    Science.gov (United States)

    Flores-Alsina, Xavier; Gernaey, Krist V; Jeppsson, Ulf

    2012-01-01

    This paper examines the effect of different model assumptions when describing biological nutrient removal (BNR) by the activated sludge models (ASM) 1, 2d & 3. The performance of a nitrogen removal (WWTP1) and a combined nitrogen and phosphorus removal (WWTP2) benchmark wastewater treatment plant was compared for a series of model assumptions. Three different model approaches describing BNR are considered. In the reference case, the original model implementations are used to simulate WWTP1 (ASM1 & 3) and WWTP2 (ASM2d). The second set of models includes a reactive settler, which extends the description of the non-reactive TSS sedimentation and transport in the reference case with the full set of ASM processes. Finally, the third set of models is based on including electron acceptor dependency of biomass decay rates for ASM1 (WWTP1) and ASM2d (WWTP2). The results show that incorporation of a reactive settler: (1) increases the hydrolysis of particulates; (2) increases the overall plant's denitrification efficiency by reducing the S(NOx) concentration at the bottom of the clarifier; (3) increases the oxidation of COD compounds; (4) increases X(OHO) and X(ANO) decay; and, finally, (5) increases the growth of X(PAO) and formation of X(PHA,Stor) for ASM2d, which has a major impact on the whole P removal system. Introduction of electron acceptor dependent decay leads to a substantial increase of the concentration of X(ANO), X(OHO) and X(PAO) in the bottom of the clarifier. The paper ends with a critical discussion of the influence of the different model assumptions, and emphasizes the need for a model user to understand the significant differences in simulation results that are obtained when applying different combinations of 'standard' models.

  10. Advantages and challenges of using physics curricula as a model for reforming an undergraduate biology course.

    Science.gov (United States)

    Donovan, D A; Atkins, L J; Salter, I Y; Gallagher, D J; Kratz, R F; Rousseau, J V; Nelson, G D

    2013-06-01

    We report on the development of a life sciences curriculum, targeted to undergraduate students, which was modeled after a commercially available physics curriculum and based on aspects of how people learn. Our paper describes the collaborative development process and necessary modifications required to apply a physics pedagogical model in a life sciences context. While some approaches were easily adapted, others provided significant challenges. Among these challenges were: representations of energy, introducing definitions, the placement of Scientists' Ideas, and the replicability of data. In modifying the curriculum to address these challenges, we have come to see them as speaking to deeper differences between the disciplines, namely that introductory physics--for example, Newton's laws, magnetism, light--is a science of pairwise interaction, while introductory biology--for example, photosynthesis, evolution, cycling of matter in ecosystems--is a science of linked processes, and we suggest that this is how the two disciplines are presented in introductory classes. We illustrate this tension through an analysis of our adaptations of the physics curriculum for instruction on the cycling of matter and energy; we show that modifications of the physics curriculum to address the biological framework promotes strong gains in student understanding of these topics, as evidenced by analysis of student work.

  11. Modeling LIDAR Detection of Biological Aerosols to Determine Optimum Implementation Strategy

    Energy Technology Data Exchange (ETDEWEB)

    Sheen, David M.; Aker, Pam M.

    2007-09-19

    This report summarizes work performed for a larger multi-laboratory project named the Background Interferent Measurement and Standards project. While originally tasked to develop algorithms to optimize biological warfare agent detection using UV fluorescence LIDAR, the current uncertainties in the reported fluorescence profiles and cross sections the development of any meaningful models. It was decided that a better approach would be to model the wavelength-dependent elastic backscattering from a number of ambient background aerosol types, and compare this with that generated from representative sporulated and vegetative bacterial systems. Calculations in this report show that a 266, 355, 532 and 1064 nm elastic backscatter LIDAR experiment will allow an operator to immediately recognize when sulfate, VOC-based or road dust (silicate) aerosols are approaching, independent of humidity changes. It will be more difficult to distinguish soot aerosols from biological aerosols, or vegetative bacteria from sporulated bacteria. In these latter cases, the elastic scattering data will most likely have to be combined with UV fluorescence data to enable a more robust categorization.

  12. Biologically-directed modeling reflects cytolytic clearance of SIV-infected cells in vivo in macaques.

    Directory of Open Access Journals (Sweden)

    W David Wick

    Full Text Available The disappointing outcomes of cellular immune-based vaccines against HIV-1 despite strong evidence for the protective role of CD8⁺ T lymphocytes (CTLs has prompted revisiting the mechanisms of cellular immunity. Prior data from experiments examining the kinetics of Simian Immunodeficiency Virus (SIV clearance in infected macaques with or without in vivo CD8 depletion were interpreted as refuting the concept that CTLs suppress SIV/HIV by direct killing of infected cells. Here we briefly review the biological evidence for CTL cytolytic activity in viral infections, and utilize biologically-directed modeling to assess the possibility of a killing mechanism for the antiviral effect of CTLs, taking into account the generation, proliferation, and survival of activated CD4⁺ and CD8⁺ T lymphocytes, as well as the life cycle of the virus. Our analyses of the published macaque data using these models support a killing mechanism, when one considers T lymphocyte and HIV-1 lifecycles, and factors such as the eclipse period before release of virions by infected cells, an exponential pattern of virion production by infected cells, and a variable lifespan for acutely infected cells. We conclude that for SIV/HIV pathogenesis, CTLs deserve their reputation as being cytolytic.

  13. Design, synthesis and biological evaluation of Arylpiperazine-based ...

    Indian Academy of Sciences (India)

    years, several piperazine-based molecules have been reported to possess strong apoptotic activity on cancer- ous cells.21 28 Piperazine based small amides such as. AK301 (I), have been stated to induce mitotic arrest and to increase ligand-dependent apoptosis in HT29 human colon cancer cells (ED50: 115nM).21 Also,.

  14. Use of genome-scale metabolic models in evolutionary systems biology.

    Science.gov (United States)

    Papp, Balázs; Szappanos, Balázs; Notebaart, Richard A

    2011-01-01

    One of the major aims of the nascent field of evolutionary systems biology is to test evolutionary hypotheses that are not only realistic from a population genetic point of view but also detailed in terms of molecular biology mechanisms. By providing a mapping between genotype and phenotype for hundreds of genes, genome-scale systems biology models of metabolic networks have already provided valuable insights into the evolution of metabolic gene contents and phenotypes of yeast and other microbial species. Here we review the recent use of these computational models to predict the fitness effect of mutations, genetic interactions, evolutionary outcomes, and to decipher the mechanisms of mutational robustness. While these studies have demonstrated that even simplified models of biochemical reaction networks can be highly informative for evolutionary analyses, they have also revealed the weakness of this modeling framework to quantitatively predict mutational effects, a challenge that needs to be addressed for future progress in evolutionary systems biology.

  15. Stochastic processes, multiscale modeling, and numerical methods for computational cellular biology

    CERN Document Server

    2017-01-01

    This book focuses on the modeling and mathematical analysis of stochastic dynamical systems along with their simulations. The collected chapters will review fundamental and current topics and approaches to dynamical systems in cellular biology. This text aims to develop improved mathematical and computational methods with which to study biological processes. At the scale of a single cell, stochasticity becomes important due to low copy numbers of biological molecules, such as mRNA and proteins that take part in biochemical reactions driving cellular processes. When trying to describe such biological processes, the traditional deterministic models are often inadequate, precisely because of these low copy numbers. This book presents stochastic models, which are necessary to account for small particle numbers and extrinsic noise sources. The complexity of these models depend upon whether the biochemical reactions are diffusion-limited or reaction-limited. In the former case, one needs to adopt the framework of s...

  16. A GEO-VISUAL ANALYTICS APPROACH TO BIOLOGICAL SHEPHERDING: MODELLING ANIMAL MOVEMENTS AND IMPACTS

    Directory of Open Access Journals (Sweden)

    K. K. Benke

    2012-07-01

    Full Text Available The lamb industry in Victoria is a significant component of the state economy with annual exports in the vicinity of $1 billion. GPS and visualisation tools can be used to monitor grazing animal movements at the farm scale and observe interactions with the environment. Modelling the spatial-temporal movements of grazing animals in response to environmental conditions provides input for the design of paddocks with the aim of improving management procedures, animal performance and animal welfare. The term "biological shepherding" is associated with the re-design of environmental conditions and the analysis of responses from grazing animals. The combination of biological shepherding with geo-visual analytics (geo-spatial data analysis with visualisation provides a framework for improving landscape design and supports research in grazing behaviour in variable landscapes, heat stress avoidance behaviour during summer months, and modelling excreta distributions (with respect to nitrogen emissions and nitrogen return for fertilising the paddock. Nitrogen losses due to excreta are mainly in the form of gaseous emissions to the atmosphere and leaching into the groundwater. In this study, background and context are provided in the case of biological shepherding and tracking animal movements. Examples are provided of recent applications in regional Australia and New Zealand. Based on experimental data and computer simulation, and using data visualisation and feature extraction, it was demonstrated that livestock excreta are not always randomly located, but concentrated around localised gathering points, sometimes separated by the nature of the excretion. Farmers require information on the nitrogen losses in order to reduce emissions to meet local and international nitrogen leaching and greenhouse gas targets and to improve the efficiency of nutrient management.

  17. MODEL PENULISAN BUKU AJAR BIOLOGI SMA BERWAWASAN EKOLOGI DAN LOKAL UNTUK MENINGKATKAN KEPEDULIAN SISWA TERHADAP LINGKUNGAN

    Directory of Open Access Journals (Sweden)

    Achyani Achyani

    2010-05-01

    Full Text Available A study using Research and Development design was conducted to produce a model of Biology hand book writing which is ecology and local oriented as an effort to increase students’ care toward environment. The background of this research is the reality which is  still going on untill now that the awareness and care of the school graduatee toward the environement safety is still low. Besides, hard science instructional at school could not affect or intervene the graduatee’s characteristics, for instance in keeping the environment awareness. Meanwhile, there are many concepts of environment which had been taught through hard science especially biology, so in the researcher’s point of view, biology subject has strategic role to prevent or mitigate the environment disaster caused by human activities. The model was validated at beach  ecosystem. The analysis of the research result includes three aspects, namely: 1 text comprehension, 2 environment care attitude, and 3 handbook readibility. Based on the result of beach ecosystem data analysis, it was found that (1 there was a significant difference between experimental class and control class in the beach ecosystem which is shown by tcalculation > ttable (7.429 > 2.00; (2 there was strong correlation between students’ comprehension and attitude which is shown by coeficient correlation (r 0.634. While the text readability test (Cloze test shown  the readability of beach ecosystem text is 57,57% (moderate. Therefore, it can be concluded that all of the texts in the developed book are fit and proper for SMA students of grade X.   Kata kunci:  Penulisan buku ajar, orientasi ekologi dan lokal, kepedulian terhadap  lingkungan.

  18. The role of mathematical models in understanding pattern formation in developmental biology.

    Science.gov (United States)

    Umulis, David M; Othmer, Hans G

    2015-05-01

    In a Wall Street Journal article published on April 5, 2013, E. O. Wilson attempted to make the case that biologists do not really need to learn any mathematics-whenever they run into difficulty with numerical issues, they can find a technician (aka mathematician) to help them out of their difficulty. He formalizes this in Wilsons Principle No. 1: "It is far easier for scientists to acquire needed collaboration from mathematicians and statisticians than it is for mathematicians and statisticians to find scientists able to make use of their equations." This reflects a complete misunderstanding of the role of mathematics in all sciences throughout history. To Wilson, mathematics is mere number crunching, but as Galileo said long ago, "The laws of Nature are written in the language of mathematics[Formula: see text] the symbols are triangles, circles and other geometrical figures, without whose help it is impossible to comprehend a single word." Mathematics has moved beyond the geometry-based model of Galileo's time, and in a rebuttal to Wilson, E. Frenkel has pointed out the role of mathematics in synthesizing the general principles in science (Both point and counter-point are available in Wilson and Frenkel in Notices Am Math Soc 60(7):837-838, 2013). We will take this a step further and show how mathematics has been used to make new and experimentally verified discoveries in developmental biology and how mathematics is essential for understanding a problem that has puzzled experimentalists for decades-that of how organisms can scale in size. Mathematical analysis alone cannot "solve" these problems since the validation lies at the molecular level, but conversely, a growing number of questions in biology cannot be solved without mathematical analysis and modeling. Herein, we discuss a few examples of the productive intercourse between mathematics and biology.

  19. Essential Oils from Thyme (Thymus vulgaris): Chemical Composition and Biological Effects in Mouse Model.

    Science.gov (United States)

    Vetvicka, Vaclav; Vetvickova, Jana

    2016-12-01

    Thymus species are popular spices and contain volatile oils as main chemical constituents. Recently, plant-derived essential oils are gaining significant attention due to their significant biological activities. Seven different thymus-derived essential oils were compared in our study. First, we focused on their chemical composition, which was followed up by testing their effects on phagocytosis, cytokine production, chemotaxis, edema inhibition, and liver protection. We found limited biological activities among tested oils, with no correlation between composition and biological effects. Similarly, no oils were effective in every reaction. Based on our data, the tested biological use of these essential oils is questionable.

  20. Social and Behavioral Science: Monitoring Social Foraging Behavior in a Biological Model System

    Science.gov (United States)

    2016-10-12

    stratification (i.e., caste system ) that characterizes both and leads to some actors in the groups being more susceptible to disease and other risks. The RFID...Social Foraging Behavior in a Biological Model System " The views, opinions and/or findings contained in this report are those of the author(s) and...reviewed journals: Final Report: "Social and Behavioral Science: Monitoring Social Foraging Behavior in a Biological Model System " Report Title The

  1. Biological effectiveness and application of heavy ions in radiation therapy described by a physical and biological model

    International Nuclear Information System (INIS)

    Olsen, K.J.; Hansen, J.W.

    1982-12-01

    A description is given of the physical basis for applying track structure theory in the determination of the effectiveness of heavy-ion irradiation of single- and multi-hit target systems. It will be shown that for applying the theory to biological systems the effectiveness of heavy-ion irradiation is inadequately described by an RBE-factor, whereas the complete formulation of the probability of survival must be used, as survival depends on both radiation quality and dose. The theoretical model of track structure can be used in dose-effect calculations for neutron-, high-LET, and low-LET radiation applied simultaneously in therapy. (author)

  2. Predicting Biological Information Flow in a Model Oxygen Minimum Zone

    Science.gov (United States)

    Louca, S.; Hawley, A. K.; Katsev, S.; Beltran, M. T.; Bhatia, M. P.; Michiels, C.; Capelle, D.; Lavik, G.; Doebeli, M.; Crowe, S.; Hallam, S. J.

    2016-02-01

    Microbial activity drives marine biochemical fluxes and nutrient cycling at global scales. Geochemical measurements as well as molecular techniques such as metagenomics, metatranscriptomics and metaproteomics provide great insight into microbial activity. However, an integration of molecular and geochemical data into mechanistic biogeochemical models is still lacking. Recent work suggests that microbial metabolic pathways are, at the ecosystem level, strongly shaped by stoichiometric and energetic constraints. Hence, models rooted in fluxes of matter and energy may yield a holistic understanding of biogeochemistry. Furthermore, such pathway-centric models would allow a direct consolidation with meta'omic data. Here we present a pathway-centric biogeochemical model for the seasonal oxygen minimum zone in Saanich Inlet, a fjord off the coast of Vancouver Island. The model considers key dissimilatory nitrogen and sulfur fluxes, as well as the population dynamics of the genes that mediate them. By assuming a direct translation of biocatalyzed energy fluxes to biosynthesis rates, we make predictions about the distribution and activity of the corresponding genes. A comparison of the model to molecular measurements indicates that the model explains observed DNA, RNA, protein and cell depth profiles. This suggests that microbial activity in marine ecosystems such as oxygen minimum zones is well described by DNA abundance, which, in conjunction with geochemical constraints, determines pathway expression and process rates. Our work further demonstrates how meta'omic data can be mechanistically linked to environmental redox conditions and biogeochemical processes.

  3. Antiproliferative Pt(IV) complexes: synthesis, biological activity, and quantitative structure-activity relationship modeling.

    Science.gov (United States)

    Gramatica, Paola; Papa, Ester; Luini, Mara; Monti, Elena; Gariboldi, Marzia B; Ravera, Mauro; Gabano, Elisabetta; Gaviglio, Luca; Osella, Domenico

    2010-09-01

    Several Pt(IV) complexes of the general formula [Pt(L)2(L')2(L'')2] [axial ligands L are Cl-, RCOO-, or OH-; equatorial ligands L' are two am(m)ine or one diamine; and equatorial ligands L'' are Cl- or glycolato] were rationally designed and synthesized in the attempt to develop a predictive quantitative structure-activity relationship (QSAR) model. Numerous theoretical molecular descriptors were used alongside physicochemical data (i.e., reduction peak potential, Ep, and partition coefficient, log Po/w) to obtain a validated QSAR between in vitro cytotoxicity (half maximal inhibitory concentrations, IC50, on A2780 ovarian and HCT116 colon carcinoma cell lines) and some features of Pt(IV) complexes. In the resulting best models, a lipophilic descriptor (log Po/w or the number of secondary sp3 carbon atoms) plus an electronic descriptor (Ep, the number of oxygen atoms, or the topological polar surface area expressed as the N,O polar contribution) is necessary for modeling, supporting the general finding that the biological behavior of Pt(IV) complexes can be rationalized on the basis of their cellular uptake, the Pt(IV)-->Pt(II) reduction, and the structure of the corresponding Pt(II) metabolites. Novel compounds were synthesized on the basis of their predicted cytotoxicity in the preliminary QSAR model, and were experimentally tested. A final QSAR model, based solely on theoretical molecular descriptors to ensure its general applicability, is proposed.

  4. Biological evaluation of silver nanoparticles incorporated into chitosan-based membranes

    NARCIS (Netherlands)

    Shao, J.; Yu, N.; Kolwijck, E.; Wang, B.; Tan, K.W.; Jansen, J.A.; Walboomers, X.F.; Yang, F.

    2017-01-01

    AIM: To evaluate the antibacterial potential and biological performance of silver nanoparticles in chitosan-based membranes. MATERIALS & METHODS: Electrospun chitosan/poly(ethylene oxide) membranes with different amounts of silver nanoparticles were evaluated for antibacterial properties and

  5. Robotic, MEMS-based Multi Utility Sample Preparation Instrument for ISS Biological Workstation, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — This project will develop a multi-functional, automated sample preparation instrument for biological wet-lab workstations on the ISS. The instrument is based on a...

  6. Modelling, abstraction, and computation in systems biology: A view from computer science.

    Science.gov (United States)

    Melham, Tom

    2013-04-01

    Systems biology is centrally engaged with computational modelling across multiple scales and at many levels of abstraction. Formal modelling, precise and formalised abstraction relationships, and computation also lie at the heart of computer science--and over the past decade a growing number of computer scientists have been bringing their discipline's core intellectual and computational tools to bear on biology in fascinating new ways. This paper explores some of the apparent points of contact between the two fields, in the context of a multi-disciplinary discussion on conceptual foundations of systems biology. Copyright © 2012 Elsevier Ltd. All rights reserved.

  7. Model based management of a reservoir system

    Energy Technology Data Exchange (ETDEWEB)

    Scharaw, B.; Westerhoff, T. [Fraunhofer IITB, Ilmenau (Germany). Anwendungszentrum Systemtechnik; Puta, H.; Wernstedt, J. [Technische Univ. Ilmenau (Germany)

    2000-07-01

    The main goals of reservoir management systems consist of prevention against flood water damages, the catchment of raw water and keeping all of the quality parameters within their limits besides controlling the water flows. In consideration of these goals a system model of the complete reservoir system Ohra-Schmalwasser-Tambach Dietharz was developed. This model has been used to develop optimized strategies for minimization of raw water production cost, for maximization of electrical energy production and to cover flood situations, as well. Therefore a proper forecast of the inflow to the reservoir from the catchment areas (especially flooding rivers) and the biological processes in the reservoir is important. The forecast model for the inflow to the reservoir is based on the catchment area model of Lorent and Gevers. It uses area precipitation, water supply from the snow cover, evapotranspiration and soil wetness data to calculate the amount of flow in rivers. The other aim of the project is to ensure the raw water quality using quality models, as well. Then a quality driven raw water supply will be possible. (orig.)

  8. Development of a GCR Event-based Risk Model

    Science.gov (United States)

    Cucinotta, Francis A.; Ponomarev, Artem L.; Plante, Ianik; Carra, Claudio; Kim, Myung-Hee

    2009-01-01

    A goal at NASA is to develop event-based systems biology models of space radiation risks that will replace the current dose-based empirical models. Complex and varied biochemical signaling processes transmit the initial DNA and oxidative damage from space radiation into cellular and tissue responses. Mis-repaired damage or aberrant signals can lead to genomic instability, persistent oxidative stress or inflammation, which are causative of cancer and CNS risks. Protective signaling through adaptive responses or cell repopulation is also possible. We are developing a computational simulation approach to galactic cosmic ray (GCR) effects that is based on biological events rather than average quantities such as dose, fluence, or dose equivalent. The goal of the GCR Event-based Risk Model (GERMcode) is to provide a simulation tool to describe and integrate physical and biological events into stochastic models of space radiation risks. We used the quantum multiple scattering model of heavy ion fragmentation (QMSFRG) and well known energy loss processes to develop a stochastic Monte-Carlo based model of GCR transport in spacecraft shielding and tissue. We validated the accuracy of the model by comparing to physical data from the NASA Space Radiation Laboratory (NSRL). Our simulation approach allows us to time-tag each GCR proton or heavy ion interaction in tissue including correlated secondary ions often of high multiplicity. Conventional space radiation risk assessment employs average quantities, and assumes linearity and additivity of responses over the complete range of GCR charge and energies. To investigate possible deviations from these assumptions, we studied several biological response pathway models of varying induction and relaxation times including the ATM, TGF -Smad, and WNT signaling pathways. We then considered small volumes of interacting cells and the time-dependent biophysical events that the GCR would produce within these tissue volumes to estimate how

  9. Digital Learning Material for Student-Directed Model Building in Molecular Biology

    Science.gov (United States)

    Aegerter-Wilmsen, Tinri; Coppens, Marjolijn; Janssen, Fred; Hartog, Rob; Bisseling, Ton

    2005-01-01

    The building of models to explain data and make predictions constitutes an important goal in molecular biology research. To give students the opportunity to practice such model building, two digital cases had previously been developed in which students are guided to build a model step by step. In this article, the development and initial…

  10. Tangible Models and Haptic Representations Aid Learning of Molecular Biology Concepts

    Science.gov (United States)

    Johannes, Kristen; Powers, Jacklyn; Couper, Lisa; Silberglitt, Matt; Davenport, Jodi

    2016-01-01

    Can novel 3D models help students develop a deeper understanding of core concepts in molecular biology? We adapted 3D molecular models, developed by scientists, for use in high school science classrooms. The models accurately represent the structural and functional properties of complex DNA and Virus molecules, and provide visual and haptic…

  11. A Novel Method to Verify Multilevel Computational Models of Biological Systems Using Multiscale Spatio-Temporal Meta Model Checking

    Science.gov (United States)

    Gilbert, David

    2016-01-01

    Insights gained from multilevel computational models of biological systems can be translated into real-life applications only if the model correctness has been verified first. One of the most frequently employed in silico techniques for computational model verification is model checking. Traditional model checking approaches only consider the evolution of numeric values, such as concentrations, over time and are appropriate for computational models of small scale systems (e.g. intracellular networks). However for gaining a systems level understanding of how biological organisms function it is essential to consider more complex large scale biological systems (e.g. organs). Verifying computational models of such systems requires capturing both how numeric values and properties of (emergent) spatial structures (e.g. area of multicellular population) change over time and across multiple levels of organization, which are not considered by existing model checking approaches. To address this limitation we have developed a novel approximate probabilistic multiscale spatio-temporal meta model checking methodology for verifying multilevel computational models relative to specifications describing the desired/expected system behaviour. The methodology is generic and supports computational models encoded using various high-level modelling formalisms because it is defined relative to time series data and not the models used to generate it. In addition, the methodology can be automatically adapted to case study specific types of spatial structures and properties using the spatio-temporal