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.

Notions of similarity for computational biology models

KAUST Repository

Waltemath, Dagmar; Henkel, Ron; Hoehndorf, Robert; Kacprowski, Tim; Knuepfer, Christian; Liebermeister, Wolfram

2016-01-01

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.

Transcription control engineering and applications in synthetic biology

Directory of Open Access Journals (Sweden)

Michael D. Engstrom

2017-09-01

Full Text Available In synthetic biology, researchers assemble biological components in new ways to produce systems with practical applications. One of these practical applications is control of the flow of genetic information (from nucleic acid to protein, a.k.a. gene regulation. Regulation is critical for optimizing protein (and therefore activity levels and the subsequent levels of metabolites and other cellular properties. The central dogma of molecular biology posits that information flow commences with transcription, and accordingly, regulatory tools targeting transcription have received the most attention in synthetic biology. In this mini-review, we highlight many past successes and summarize the lessons learned in developing tools for controlling transcription. In particular, we focus on engineering studies where promoters and transcription terminators (cis-factors were directly engineered and/or isolated from DNA libraries. We also review several well-characterized transcription regulators (trans-factors, giving examples of how cis- and trans-acting factors have been combined to create digital and analogue switches for regulating transcription in response to various signals. Last, we provide examples of how engineered transcription control systems have been used in metabolic engineering and more complicated genetic circuits. While most of our mini-review focuses on the well-characterized bacterium Escherichia coli, we also provide several examples of the use of transcription control engineering in non-model organisms. Similar approaches have been applied outside the bacterial kingdom indicating that the lessons learned from bacterial studies may be generalized for other organisms.

Transcription control engineering and applications in synthetic biology.

Science.gov (United States)

Engstrom, Michael D; Pfleger, Brian F

2017-09-01

In synthetic biology, researchers assemble biological components in new ways to produce systems with practical applications. One of these practical applications is control of the flow of genetic information (from nucleic acid to protein), a.k.a. gene regulation. Regulation is critical for optimizing protein (and therefore activity) levels and the subsequent levels of metabolites and other cellular properties. The central dogma of molecular biology posits that information flow commences with transcription, and accordingly, regulatory tools targeting transcription have received the most attention in synthetic biology. In this mini-review, we highlight many past successes and summarize the lessons learned in developing tools for controlling transcription. In particular, we focus on engineering studies where promoters and transcription terminators ( cis -factors) were directly engineered and/or isolated from DNA libraries. We also review several well-characterized transcription regulators ( trans- factors), giving examples of how cis- and trans -acting factors have been combined to create digital and analogue switches for regulating transcription in response to various signals. Last, we provide examples of how engineered transcription control systems have been used in metabolic engineering and more complicated genetic circuits. While most of our mini-review focuses on the well-characterized bacterium Escherichia coli , we also provide several examples of the use of transcription control engineering in non-model organisms. Similar approaches have been applied outside the bacterial kingdom indicating that the lessons learned from bacterial studies may be generalized for other organisms.

Use of nuclear techniques in biological control

International Nuclear Information System (INIS)

Greany, Patrick D.; Carpenter, James E.

2000-01-01

As pointed out by Benbrook (1996), pest management is at a crossroads, and there is a great need for new, biointensive pest management strategies. Among these approaches, biological control is a keystone. However, because of increasing concerns about the introduction of exotic natural enemies of insect pests and weeds (Howarth 1991, Delfosse 1997), the overall thrust of biological control has moved toward augmentative biological control, involving releases of established natural enemy species (Knipling 1992). This in turn has created a need to develop more cost-effective mass rearing technologies for beneficial insects. Nuclear techniques could play an especially important role in augmentative biological control, not only in facilitating mass rearing, but in several other ways, as indicated below. Recognising the potential value for use of nuclear techniques in biological control, the Insect and Pest Control Section of the Joint FAO/IAEA Division of Nuclear Techniques in Food and Agriculture, International Atomic Energy Agency, sponsored a Consultants' Group Meeting on this subject in April 1997. The Group produced a document entitled Use of Nuclear Techniques in Biological Control: Managing Pests, Facilitating Trade and Protecting the Environment. The consultants included the authors of this paper as well as Ernest Delfosse (at that time, with the USDA-APHIS National Biological Control Institute), Garry Hill (Intl. Institute for Biological Control), Sinthya Penn (Beneficial Insectary), and Felipe Jeronimo (USDA-APHIS PPQ, Guatemala). The remarks presented in this paper reflect the thoughts presented by these consultants and other participants at the IAEA-sponsored meeting. Several potential uses for nuclear techniques were identified by the Consultants' Group, including: 1) improvements in rearing media (either artificial diets or natural hosts/prey), 2) provision of sterilised natural prey to be used as food during shipment, to ameliorate concerns relating to the

Local and global control of ecological and biological networks

OpenAIRE

Alessandro Ferrarini

2014-01-01

Recently, I introduced a methodological framework so that ecological and biological networks can be controlled both from inside and outside by coupling network dynamics and evolutionary modelling. The endogenous control requires the network to be optimized at the beginning of its dynamics (by acting upon nodes, edges or both) so that it will then go inertially to the desired state. Instead, the exogenous control requires that exogenous controllers act upon the network at each time step. By th...

Conserving and enhancing biological control of nematodes.

Science.gov (United States)

Timper, Patricia

2014-06-01

Conservation biological control is the modification of the environment or existing practices to protect and enhance antagonistic organisms to reduce damage from pests. This approach to biological control has received insufficient attention compared with inundative applications of microbial antagonists to control nematodes. This review provides examples of how production practices can enhance or diminish biological control of plant-parasitic nematodes and other soilborne pests. Antagonists of nematodes can be enhanced by providing supplementary food sources such as occurs when organic amendments are applied to soil. However, some organic amendments (e.g., manures and plants containing allelopathic compounds) can also be detrimental to nematode antagonists. Plant species and genotype can strongly influence the outcome of biological control. For instance, the susceptibility of the plant to the nematode can determine the effectiveness of control; good hosts will require greater levels of suppression than poor hosts. Plant genotype can also influence the degree of rhizosphere colonization and antibiotic production by antagonists, as well the expression of induced resistance by plants. Production practices such as crop rotation, fallow periods, tillage, and pesticide applications can directly disrupt populations of antagonistic organisms. These practices can also indirectly affect antagonists by reducing their primary nematode host. One of the challenges of conservation biological control is that practices intended to protect or enhance suppression of nematodes may not be effective in all field sites because they are dependent on indigenous antagonists. Ultimately, indicators will need to be identified, such as the presence of particular antagonists, which can guide decisions on where it is practical to use conservation biological control. Antagonists can also be applied to field sites in conjunction with conservation practices to improve the consistency, efficacy, and

Engineering challenges of BioNEMS: the integration of microfluidics, micro- and nanodevices, models and external control for systems biology.

Science.gov (United States)

Wikswo, J P; Prokop, A; Baudenbacher, F; Cliffel, D; Csukas, B; Velkovsky, M

2006-08-01

Systems biology, i.e. quantitative, postgenomic, postproteomic, dynamic, multiscale physiology, addresses in an integrative, quantitative manner the shockwave of genetic and proteomic information using computer models that may eventually have 10(6) dynamic variables with non-linear interactions. Historically, single biological measurements are made over minutes, suggesting the challenge of specifying 10(6) model parameters. Except for fluorescence and micro-electrode recordings, most cellular measurements have inadequate bandwidth to discern the time course of critical intracellular biochemical events. Micro-array expression profiles of thousands of genes cannot determine quantitative dynamic cellular signalling and metabolic variables. Major gaps must be bridged between the computational vision and experimental reality. The analysis of cellular signalling dynamics and control requires, first, micro- and nano-instruments that measure simultaneously multiple extracellular and intracellular variables with sufficient bandwidth; secondly, the ability to open existing internal control and signalling loops; thirdly, external BioMEMS micro-actuators that provide high bandwidth feedback and externally addressable intracellular nano-actuators; and, fourthly, real-time, closed-loop, single-cell control algorithms. The unravelling of the nested and coupled nature of cellular control loops requires simultaneous recording of multiple single-cell signatures. Externally controlled nano-actuators, needed to effect changes in the biochemical, mechanical and electrical environment both outside and inside the cell, will provide a major impetus for nanoscience.

Biological Control of Plant Disease Caused by Bacteria

Directory of Open Access Journals (Sweden)

Triwidodo Arwiyanto

2014-07-01

Full Text Available Bacterial diseases in plants are difficult to control. The emphasis is on preventing the spread of the bacteria rather than curing the diseased plant. Integrated management measures for bacterial plant pathogens should be applied for successfull control. Biological control is one of the control measures viz. through the use of microorganisms to suppress the growth and development of bacterial plant pathogen and ultimately reduce the possibility of disease onset. The study of biological control of bacterial plant pathogen was just began compared with of fungal plant pathogen. The ecological nature of diverse bacterial plant pathogens has led scientists to apply different approach in the investigation of its biological control. The complex process of entrance to its host plant for certain soil-borne bacterial plant pathogens need special techniques and combination of more than one biological control agent. Problem and progress in controlling bacterial plant pathogens biologically will be discussed in more detail in the paper and some commercial products of biological control agents (biopesticides will be introduced.     Penyakit tumbuhan karena bakteri sulit dikendalikan. Penekanan pengendalian adalah pada pencegahan penyebaran bakteri patogen dan bukan pada penyembuhan tanaman yang sudah sakit. Untuk suksesnya pengendalian bakteri patogen tumbuhan diperlukan cara pengelolaan yang terpadu. Pengendalian secara biologi merupakan salah satu cara pengendalian dengan menggunakan mikroorganisme untuk menekan pertumbuhan dan perkembangan bakteri patogen tumbuhan dengan tujuan akhir menurunkan kemungkinan timbulnya penyakit. Sifat ekologi bakteri patogen tumbuhan yang berbeda-beda mengharuskan pendekatan yang berbeda pula dalam pengendaliannya secara biologi. Masalah dan perkembangan dalam pengendalian bakteri patogen tumbuhan secara biologi didiskusikan secara detail dalam makalah ini.

Notions of similarity for systems biology models.

Science.gov (United States)

Henkel, Ron; Hoehndorf, Robert; Kacprowski, Tim; Knüpfer, Christian; Liebermeister, Wolfram; Waltemath, Dagmar

2018-01-01

Systems biology models are rapidly increasing in complexity, size and numbers. When building large models, researchers rely on software tools for the retrieval, comparison, combination and merging of models, as well as for 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 survey existing methods for the comparison of models, introduce quantitative measures for model similarity, and discuss potential applications of combined similarity measures. To frame model comparison as a general problem, we describe a theoretical approach to defining and computing similarities based on a combination of different model aspects. The six aspects that we define as potentially relevant for similarity are underlying encoding, references to biological entities, quantitative behaviour, qualitative behaviour, mathematical equations and parameters and network structure. We argue that future similarity measures will benefit from combining these model aspects in flexible, problem-specific ways to mimic users' intuition about model similarity, and to support complex model searches in databases. © The Author 2016. Published by Oxford University Press.

BIOLOGICAL CONTROL OF WEEDS BY MEANS OF PLANT PATHOGENS

OpenAIRE

Marija Ravlić; Renata Baličević

2014-01-01

Biological control is the use of live beneficial organisms and products of their metabolism in the pests control. Plant pathogens can be used for weed control in three different ways: as classical, conservation and augmentative (inoculative and inundated) biological control. Inundated biological control involves the use of bioherbicides (mycoherbicides) or artificial breeding of pathogens and application in specific stages of crops and weeds. Biological control of weeds can be used where chem...

Echinococcus as a model system: biology and epidemiology.

Science.gov (United States)

Thompson, R C A; Jenkins, D J

2014-10-15

The introduction of Echinococcus to Australia over 200 years ago and its establishment in sheep rearing areas of the country inflicted a serious medical and economic burden on the country. This resulted in an investment in both basic and applied research aimed at learning more about the biology and life cycle of Echinococcus. This research served to illustrate the uniqueness of the parasite in terms of developmental biology and ecology, and the value of Echinococcus as a model system in a broad range of research, from fundamental biology to theoretical control systems. These studies formed the foundation for an international, diverse and ongoing research effort on the hydatid organisms encompassing stem cell biology, gene regulation, strain variation, wildlife diseases and models of transmission dynamics. We describe the development, nature and diversity of this research, and how it was initiated in Australia but subsequently has stimulated much international and collaborative research on Echinococcus. Copyright © 2014 Australian Society for Parasitology Inc. Published by Elsevier Ltd. All rights reserved.

Biological Systems Thinking for Control Engineering Design

Directory of Open Access Journals (Sweden)

D. J. Murray-Smith

2004-01-01

Full Text Available Artificial neural networks and genetic algorithms are often quoted in discussions about the contribution of biological systems thinking to engineering design. This paper reviews work on the neuromuscular system, a field in which biological systems thinking could make specific contributions to the development and design of automatic control systems for mechatronics and robotics applications. The paper suggests some specific areas in which a better understanding of this biological control system could be expected to contribute to control engineering design methods in the future. Particular emphasis is given to the nonlinear nature of elements within the neuromuscular system and to processes of neural signal processing, sensing and system adaptivity. Aspects of the biological system that are of particular significance for engineering control systems include sensor fusion, sensor redundancy and parallelism, together with advanced forms of signal processing for adaptive and learning control. 

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.

From Biology to Mathematical Models and Back: Teaching Modeling to Biology Students, and Biology to Math and Engineering Students

Science.gov (United States)

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. PMID:20810957

Biological control of toxic cyanobacteria

CSIR Research Space (South Africa)

Ndlela, L

2016-04-01

Full Text Available harmful algal blooms and their impacts in over 30 countries. Biological control is a method of introducing natural enemies to control an organism and has been more successful using microorganisms....

An online model composition tool for system biology models.

Science.gov (United States)

Coskun, Sarp A; Cicek, A Ercument; Lai, Nicola; Dash, Ranjan K; Ozsoyoglu, Z Meral; Ozsoyoglu, Gultekin

2013-09-05

There are multiple representation formats for Systems Biology computational models, and the Systems Biology Markup Language (SBML) is one of the most widely used. SBML is used to capture, store, and distribute computational models by Systems Biology data sources (e.g., the BioModels Database) and researchers. Therefore, there is a need for all-in-one web-based solutions that support advance SBML functionalities such as uploading, editing, composing, visualizing, simulating, querying, and browsing computational models. We present the design and implementation of the Model Composition Tool (Interface) within the PathCase-SB (PathCase Systems Biology) web portal. The tool helps users compose systems biology models to facilitate the complex process of merging systems biology models. We also present three tools that support the model composition tool, namely, (1) Model Simulation Interface that generates a visual plot of the simulation according to user's input, (2) iModel Tool as a platform for users to upload their own models to compose, and (3) SimCom Tool that provides a side by side comparison of models being composed in the same pathway. Finally, we provide a web site that hosts BioModels Database models and a separate web site that hosts SBML Test Suite models. Model composition tool (and the other three tools) can be used with little or no knowledge of the SBML document structure. For this reason, students or anyone who wants to learn about systems biology will benefit from the described functionalities. SBML Test Suite models will be a nice starting point for beginners. And, for more advanced purposes, users will able to access and employ models of the BioModels Database as well.

SEEK: a systems biology data and model management platform.

Science.gov (United States)

Wolstencroft, Katherine; Owen, Stuart; Krebs, Olga; Nguyen, Quyen; Stanford, Natalie J; Golebiewski, Martin; Weidemann, Andreas; Bittkowski, Meik; An, Lihua; Shockley, David; Snoep, Jacky L; Mueller, Wolfgang; Goble, Carole

2015-07-11

Systems biology research typically involves the integration and analysis of heterogeneous data types in order to model and predict biological processes. Researchers therefore require tools and resources to facilitate the sharing and integration of data, and for linking of data to systems biology models. There are a large number of public repositories for storing biological data of a particular type, for example transcriptomics or proteomics, and there are several model repositories. However, this silo-type storage of data and models is not conducive to systems biology investigations. Interdependencies between multiple omics datasets and between datasets and models are essential. Researchers require an environment that will allow the management and sharing of heterogeneous data and models in the context of the experiments which created them. The SEEK is a suite of tools to support the management, sharing and exploration of data and models in systems biology. The SEEK platform provides an access-controlled, web-based environment for scientists to share and exchange data and models for day-to-day collaboration and for public dissemination. A plug-in architecture allows the linking of experiments, their protocols, data, models and results in a configurable system that is available 'off the shelf'. Tools to run model simulations, plot experimental data and assist with data annotation and standardisation combine to produce a collection of resources that support analysis as well as sharing. Underlying semantic web resources additionally extract and serve SEEK metadata in RDF (Resource Description Format). SEEK RDF enables rich semantic queries, both within SEEK and between related resources in the web of Linked Open Data. The SEEK platform has been adopted by many systems biology consortia across Europe. It is a data management environment that has a low barrier of uptake and provides rich resources for collaboration. This paper provides an update on the functions and

The effect of initial density and parasitoid intergenerational survival rate on classical biological control

International Nuclear Information System (INIS)

Xiao Yanni; Tang Sanyi

2008-01-01

Models of biological control have a long history of theoretical development that have focused on the interaction of a parasitoid and its host. The host-parasitoid systems have identified several important and general factors affecting the long-term dynamics of interacting populations. However, much less is known about how the initial densities of host-parasitoid populations affect the biological control as well as the stability of host-parasitoid systems. To do this, the classical Nicholson-Bailey model with host self-regulation and parasitoid intergenerational survival rate is used to uncover the effect of initial densities on the successful biological control. The results indicate that the simplest Nicholson-Bailey model has various coexistence with a wide range of parameters, including boundary attractors where the parasitoid population is absent and interior attractors where host-parasitoid coexists. The final stable states of host-parasitoid populations depend on their initial densities as well as their ratios, and those results are confirmed by basins of attraction of initial densities. The results also indicate that the parasitoid intergenerational survival rate increases the stability of the host-parasitoid systems. Therefore, the present research can help us to further understand the dynamical behavior of host-parasitoid interactions, to improve the classical biological control and to make management decisions

Insecticides and Biological Control

Science.gov (United States)

Furness, G. O.

1972-01-01

Use of insecticides has been questioned due to their harmful effects on edible items. Biological control of insects along with other effective practices for checking spread of parasites on crops are discussed. (PS)

Biological Control Strategies for Mosquito Vectors of Arboviruses.

Science.gov (United States)

Huang, Yan-Jang S; Higgs, Stephen; Vanlandingham, Dana L

2017-02-10

Historically, biological control utilizes predatory species and pathogenic microorganisms to reduce the population of mosquitoes as disease vectors. This is particularly important for the control of mosquito-borne arboviruses, which normally do not have specific antiviral therapies available. Although development of resistance is likely, the advantages of biological control are that the resources used are typically biodegradable and ecologically friendly. Over the past decade, the advancement of molecular biology has enabled optimization by the manipulation of genetic materials associated with biological control agents. Two significant advancements are the discovery of cytoplasmic incompatibility induced by Wolbachia bacteria, which has enhanced replacement programs, and the introduction of dominant lethal genes into local mosquito populations through the release of genetically modified mosquitoes. As various arboviruses continue to be significant public health threats, biological control strategies have evolved to be more diverse and become critical tools to reduce the disease burden of arboviruses.

Will the Convention on Biological Diversity put an end to biological control?

NARCIS (Netherlands)

Lenteren, van J.C.; Cock, M.J.W.; Brodeur, J.; Barratt, B.I.P.; Bigler, F.; Bolckmans, K.; Haas, F.; Mason, P.G.; Parra, J.R.P.

2011-01-01

Will the Convention on Biological Diversity put an end to biological control? Under the Convention on Biological Diversity countries have sovereign rights over their genetic resources. Agreements governing the access to these resources and the sharing of the benefits arising from their use need to

Integrating systems biology models and biomedical ontologies.

Science.gov (United States)

Hoehndorf, Robert; Dumontier, Michel; Gennari, John H; Wimalaratne, Sarala; de Bono, Bernard; Cook, Daniel L; Gkoutos, Georgios V

2011-08-11

Systems biology is an approach to biology that emphasizes the structure and dynamic behavior of biological systems and the interactions that occur within them. To succeed, systems biology crucially depends on the accessibility and integration of data across domains and levels of granularity. Biomedical ontologies were developed to facilitate such an integration of data and are often used to annotate biosimulation models in systems biology. We provide a framework to integrate representations of in silico systems biology with those of in vivo biology as described by biomedical ontologies and demonstrate this framework using the Systems Biology Markup Language. We developed the SBML Harvester software that automatically converts annotated SBML models into OWL and we apply our software to those biosimulation models that are contained in the BioModels Database. We utilize the resulting knowledge base for complex biological queries that can bridge levels of granularity, verify models based on the biological phenomenon they represent and provide a means to establish a basic qualitative layer on which to express the semantics of biosimulation models. We establish an information flow between biomedical ontologies and biosimulation models and we demonstrate that the integration of annotated biosimulation models and biomedical ontologies enables the verification of models as well as expressive queries. Establishing a bi-directional information flow between systems biology and biomedical ontologies has the potential to enable large-scale analyses of biological systems that span levels of granularity from molecules to organisms.

The semiotics of control and modeling relations in complex systems.

Science.gov (United States)

Joslyn, C

2001-01-01

We provide a conceptual analysis of ideas and principles from the systems theory discourse which underlie Pattee's semantic or semiotic closure, which is itself foundational for a school of theoretical biology derived from systems theory and cybernetics, and is now being related to biological semiotics and explicated in the relational biological school of Rashevsky and Rosen. Atomic control systems and models are described as the canonical forms of semiotic organization, sharing measurement relations, but differing topologically in that control systems are circularly and models linearly related to their environments. Computation in control systems is introduced, motivating hierarchical decomposition, hybrid modeling and control systems, and anticipatory or model-based control. The semiotic relations in complex control systems are described in terms of relational constraints, and rules and laws are distinguished as contingent and necessary functional entailments, respectively. Finally, selection as a meta-level of constraint is introduced as the necessary condition for semantic relations in control systems and models.

Workshop Introduction: Systems Biology and Biological Models

Science.gov (United States)

As we consider the future of toxicity testing, the importance of applying biological models to this problem is clear. Modeling efforts exist along a continuum with respect to the level of organization (e.g. cell, tissue, organism) linked to the resolution of the model. Generally,...

Holarchical Systems and Emotional Holons : Biologically-Inspired System Designs for Control of Autonomous Aerial Vehicles

Science.gov (United States)

Ippolito, Corey; Plice, Laura; Pisanich, Greg

2003-01-01

The BEES (Bio-inspired Engineering for Exploration Systems) for Mars project at NASA Ames Research Center has the goal of developing bio-inspired flight control strategies to enable aerial explorers for Mars scientific investigations. This paper presents a summary of our ongoing research into biologically inspired system designs for control of unmanned autonomous aerial vehicle communities for Mars exploration. First, we present cooperative design considerations for robotic explorers based on the holarchical nature of biological systems and communities. Second, an outline of an architecture for cognitive decision making and control of individual robotic explorers is presented, modeled after the emotional nervous system of cognitive biological systems. Keywords: Holarchy, Biologically Inspired, Emotional UAV Flight Control

Biological Control Strategies for Mosquito Vectors of Arboviruses

Directory of Open Access Journals (Sweden)

Yan-Jang S. Huang

2017-02-01

Full Text Available Historically, biological control utilizes predatory species and pathogenic microorganisms to reduce the population of mosquitoes as disease vectors. This is particularly important for the control of mosquito-borne arboviruses, which normally do not have specific antiviral therapies available. Although development of resistance is likely, the advantages of biological control are that the resources used are typically biodegradable and ecologically friendly. Over the past decade, the advancement of molecular biology has enabled optimization by the manipulation of genetic materials associated with biological control agents. Two significant advancements are the discovery of cytoplasmic incompatibility induced by Wolbachia bacteria, which has enhanced replacement programs, and the introduction of dominant lethal genes into local mosquito populations through the release of genetically modified mosquitoes. As various arboviruses continue to be significant public health threats, biological control strategies have evolved to be more diverse and become critical tools to reduce the disease burden of arboviruses.

Biomolecular Modeling in a Process Dynamics and Control Course

Science.gov (United States)

Gray, Jeffrey J.

2006-01-01

I present modifications to the traditional course entitled, "Process dynamics and control," which I renamed "Modeling, dynamics, and control of chemical and biological processes." Additions include the central dogma of biology, pharmacokinetic systems, population balances, control of gene transcription, and large­-scale…

Aspects of modelling and control of bioprocesses

Energy Technology Data Exchange (ETDEWEB)

Zhang, Xiachang

1995-12-31

The modelling and control of bioprocesses are the main subjects in this thesis. Different modelling approaches are proposed for different purposes in various bioprocesses. A conventional global model was constructed for a very complex mammalian cell culture process. A new concept of functional state and a multiple model (local models) approach were used for modelling the fed-batch baker`s yeast process for monitoring and control purposes. Finally, a combination of conventional electrical and biological models was used to simulate and to control a microbial fuel cell process. In the thesis, a yeast growth process was taken as an example to demonstrate the usefulness of the functional state concept and local models. The functional states were first defined according to the yeast metabolism. The process was then described by a set of simple local models. In different functional states, different local models were used. On the other hand, the on-line estimation of functional state and biomass of the process was discussed for process control purpose. As a consequence, both the functional state concept and the multiple model approach were applied for fuzzy logic control of yeast growth process. A fuzzy factor was calculated on the basis of a knowledge-based expert system and fuzzy logic rules. The factor was used to correct an ideal substrate feed rate. In the last part of the thesis, microbial fuel cell processes were studied. A microbial fuel cell is a device for direct conversion of chemical energy to electrical energy by using micro-organisms as catalysts. A combined model including conventional electrical and biological models was constructed for the process based on the biological and electrochemical phenomena

Aspects of modelling and control of bioprocesses

Energy Technology Data Exchange (ETDEWEB)

Zhang, Xiachang

1996-12-31

The modelling and control of bioprocesses are the main subjects in this thesis. Different modelling approaches are proposed for different purposes in various bioprocesses. A conventional global model was constructed for a very complex mammalian cell culture process. A new concept of functional state and a multiple model (local models) approach were used for modelling the fed-batch baker`s yeast process for monitoring and control purposes. Finally, a combination of conventional electrical and biological models was used to simulate and to control a microbial fuel cell process. In the thesis, a yeast growth process was taken as an example to demonstrate the usefulness of the functional state concept and local models. The functional states were first defined according to the yeast metabolism. The process was then described by a set of simple local models. In different functional states, different local models were used. On the other hand, the on-line estimation of functional state and biomass of the process was discussed for process control purpose. As a consequence, both the functional state concept and the multiple model approach were applied for fuzzy logic control of yeast growth process. A fuzzy factor was calculated on the basis of a knowledge-based expert system and fuzzy logic rules. The factor was used to correct an ideal substrate feed rate. In the last part of the thesis, microbial fuel cell processes were studied. A microbial fuel cell is a device for direct conversion of chemical energy to electrical energy by using micro-organisms as catalysts. A combined model including conventional electrical and biological models was constructed for the process based on the biological and electrochemical phenomena

Toward synthesizing executable models in biology.

Science.gov (United States)

Fisher, Jasmin; Piterman, Nir; Bodik, Rastislav

2014-01-01

Over the last decade, executable models of biological behaviors have repeatedly provided new scientific discoveries, uncovered novel insights, and directed new experimental avenues. These models are computer programs whose execution mechanistically simulates aspects of the cell's behaviors. If the observed behavior of the program agrees with the observed biological behavior, then the program explains the phenomena. This approach has proven beneficial for gaining new biological insights and directing new experimental avenues. One advantage of this approach is that techniques for analysis of computer programs can be applied to the analysis of executable models. For example, one can confirm that a model agrees with experiments for all possible executions of the model (corresponding to all environmental conditions), even if there are a huge number of executions. Various formal methods have been adapted for this context, for example, model checking or symbolic analysis of state spaces. To avoid manual construction of executable models, one can apply synthesis, a method to produce programs automatically from high-level specifications. In the context of biological modeling, synthesis would correspond to extracting executable models from experimental data. We survey recent results about the usage of the techniques underlying synthesis of computer programs for the inference of biological models from experimental data. We describe synthesis of biological models from curated mutation experiment data, inferring network connectivity models from phosphoproteomic data, and synthesis of Boolean networks from gene expression data. While much work has been done on automated analysis of similar datasets using machine learning and artificial intelligence, using synthesis techniques provides new opportunities such as efficient computation of disambiguating experiments, as well as the ability to produce different kinds of models automatically from biological data.

BIOLOGICAL CONTROL OF WEEDS BY MEANS OF PLANT PATHOGENS

Directory of Open Access Journals (Sweden)

Marija Ravlić

2014-06-01

Full Text Available Biological control is the use of live beneficial organisms and products of their metabolism in the pests control. Plant pathogens can be used for weed control in three different ways: as classical, conservation and augmentative (inoculative and inundated biological control. Inundated biological control involves the use of bioherbicides (mycoherbicides or artificial breeding of pathogens and application in specific stages of crops and weeds. Biological control of weeds can be used where chemical herbicides are not allowed, if resistant weed species are present or in the integrated pest management against weeds with reduced herbicides doses and other non-chemical measures, but it has certain limitations and disadvantages.

Control theory meets synthetic biology.

Science.gov (United States)

Del Vecchio, Domitilla; Dy, Aaron J; Qian, Yili

2016-07-01

The past several years have witnessed an increased presence of control theoretic concepts in synthetic biology. This review presents an organized summary of how these control design concepts have been applied to tackle a variety of problems faced when building synthetic biomolecular circuits in living cells. In particular, we describe success stories that demonstrate how simple or more elaborate control design methods can be used to make the behaviour of synthetic genetic circuits within a single cell or across a cell population more reliable, predictable and robust to perturbations. The description especially highlights technical challenges that uniquely arise from the need to implement control designs within a new hardware setting, along with implemented or proposed solutions. Some engineering solutions employing complex feedback control schemes are also described, which, however, still require a deeper theoretical analysis of stability, performance and robustness properties. Overall, this paper should help synthetic biologists become familiar with feedback control concepts as they can be used in their application area. At the same time, it should provide some domain knowledge to control theorists who wish to enter the rising and exciting field of synthetic biology. © 2016 The Author(s).

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...

Towards Synthesizing Executable Models in Biology

Directory of Open Access Journals (Sweden)

Jasmin eFisher

2014-12-01

Full Text Available Over the last decade, executable models of biological behaviors have repeatedly provided new scientific discoveries, uncovered novel insights, and directed new experimental avenues. These models are computer programs whose execution mechanistically simulates aspects of the cell’s behaviors. If the observed behavior of the program agrees with the observed biological behavior, then the program explains the phenomena. This approach has proven beneficial for gaining new biological insights and directing new experimental avenues. One advantage of this approach is that techniques for analysis of computer programs can be applied to the analysis of executable models. For example, one can confirm that a model agrees with experiments for all possible executions of the model (corresponding to all environmental conditions, even if there are a huge number of executions. Various formal methods have been adapted for this context, for example, model checking or symbolic analysis of state spaces. To avoid manual construction of executable models, one can apply synthesis, a method to produce programs automatically from high-level specifications. In the context of biological modelling, synthesis would correspond to extracting executable models from experimental data. We survey recent results about the usage of the techniques underlying synthesis of computer programs for the inference of biological models from experimental data. We describe synthesis of biological models from curated mutation experiment data, inferring network connectivity models from phosphoproteomic data, and synthesis of Boolean networks from gene expression data. While much work has been done on automated analysis of similar datasets using machine learning and artificial intelligence, using synthesis techniques provides new opportunities such as efficient computation of disambiguating experiments, as well as the ability to produce different kinds of models automatically from biological data.

Biological Control of Bacterial Wilt in South East Asia

Directory of Open Access Journals (Sweden)

Triwidodo Arwiyanto

2014-12-01

Full Text Available Bacterial wilt disease caused by Ralstonia solanacearum destroys many crops of different plant families in South East Asia despite many researches about the disease, and the availability of developed control method in other parts of the world. There is no chemical available for the bacterial wilt pathogen and biological control is then chosen as an alternative to save the crops. Most of the biological control studies were based on antagonism between biological control agent and the pathogen. The biological control agents were intended to reduce the initial inoculum of the pathogen. The effort to minimize the initial inoculum of the pathogen by baiting with the use of hypersensitive host-plant was only reliable when conducted in the greenhouse experiments. Various microorganisms have been searched as possible biological control agents, for instance avirulent form of the pathogen, soil or rhizosphere bacteria (Bacillus spp. and fluorescent pseudomonads, actinomycetes (Streptomyces spp., yeast (Pichia uillermondii, Candida ethanolica, and a consortium of microorganisms known as effective microorganisms (EM. None of these biological control agents has been used in field application and they need further investigation in order to effectively control bacterial wilt. Opportunities and challenges in developing biological control to combat bacterial wilt are discussed in the paper. Penyakit layu bakteri yang disebabkan oleh Ralstonia solanacearum menghancurkan banyak tanaman dalam famili yang berbeda di Asia Tenggara meskipun telah banyak penelitian tentang metode pengendaliannya. Penyakit ini sulit dikendalikan karena banyaknya variabilitas patogen dan belum tersedianya sumber ketahanan yang mapan. Di samping itu, sampai saat ini belum ada bahan kimia yang tersedia untuk patogen layu bakteri ini sehingga pengendalian biologi kemudian dipilih sebagai cara alternatif untuk menyelamatkan tanaman. Sebagian besar penelitian pengendalian biologi didasarkan

Models for synthetic biology.

Science.gov (United States)

Kaznessis, Yiannis N

2007-11-06

Synthetic biological engineering is emerging from biology as a distinct discipline based on quantification. The technologies propelling synthetic biology are not new, nor is the concept of designing novel biological molecules. What is new is the emphasis on system behavior. The objective is the design and construction of new biological devices and systems to deliver useful applications. Numerous synthetic gene circuits have been created in the past decade, including bistable switches, oscillators, and logic gates, and possible applications abound, including biofuels, detectors for biochemical and chemical weapons, disease diagnosis, and gene therapies. More than fifty years after the discovery of the molecular structure of DNA, molecular biology is mature enough for real quantification that is useful for biological engineering applications, similar to the revolution in modeling in chemistry in the 1950s. With the excitement that synthetic biology is generating, the engineering and biological science communities appear remarkably willing to cross disciplinary boundaries toward a common goal.

Biological Control of Bacterial Wilt in South East Asia

OpenAIRE

Arwiyanto, Triwidodo

2014-01-01

Bacterial wilt disease caused by Ralstonia solanacearum destroys many crops of different plant families in South East Asia despite many researches about the disease, and the availability of developed control method in other parts of the world. There is no chemical available for the bacterial wilt pathogen and biological control is then chosen as an alternative to save the crops. Most of the biological control studies were based on antagonism between biological control agent and the pathogen. ...

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).

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...

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

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.

Biological control component [Management of water hyacinth

International Nuclear Information System (INIS)

Harley, K.L.S.

1981-01-01

Both chemical and biological control have been used with limited success for the management of water hyacinth in Fiji. In some cases heavy application of chemicals have been successful in completely killing limited areas of water hyacinth, but have resulted in the destruction of biological agents introduced to control the water hyacinth and high contamination of natural water supplies. It is proposed that under the direction of Mr S R Singh, the Senior Research Scientist (Entomology) of the Koronivia Research Station, Suva, Fiji, a collaborative programme with Dr Harley of Australia on chemical and biological control of water hyacinth be initiated. This programme would be fundamentally short-term with the prime objective being an investigation of levels of insect population following varying levels of application of chemical sprays. By comparison with control areas, observations would be made of both chemical damage and insect damage within the limited time span of the period

Laboratory of Biological Modeling

Data.gov (United States)

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...

Effectiveness of a biological control agent Palexorista gilvoides in ...

African Journals Online (AJOL)

ACSS

Effectiveness of a biological control agent Palexorista gilvoides in controlling Gonometa podorcarpi in conifer ... gilvoides as a potential biological control agent for G. podocarpi. Field and laboratory studies further established that P. .... version for windows (SPSS, 2002). Results. Gonometa podocarpi was present in.

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...

Biological transportation networks: Modeling and simulation

KAUST Repository

Albi, Giacomo; Artina, Marco; Foransier, Massimo; Markowich, Peter A.

2015-01-01

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

Consistent robustness analysis (CRA) identifies biologically relevant properties of regulatory network models.

Science.gov (United States)

Saithong, Treenut; Painter, Kevin J; Millar, Andrew J

2010-12-16

A number of studies have previously demonstrated that "goodness of fit" is insufficient in reliably classifying the credibility of a biological model. Robustness and/or sensitivity analysis is commonly employed as a secondary method for evaluating the suitability of a particular model. The results of such analyses invariably depend on the particular parameter set tested, yet many parameter values for biological models are uncertain. Here, we propose a novel robustness analysis that aims to determine the "common robustness" of the model with multiple, biologically plausible parameter sets, rather than the local robustness for a particular parameter set. Our method is applied to two published models of the Arabidopsis circadian clock (the one-loop [1] and two-loop [2] models). The results reinforce current findings suggesting the greater reliability of the two-loop model and pinpoint the crucial role of TOC1 in the circadian network. Consistent Robustness Analysis can indicate both the relative plausibility of different models and also the critical components and processes controlling each model.

Biological control agents elevate hantavirus by subsidizing deer mouse populations

Science.gov (United States)

Dean E. Pearson; Ragan M. Callaway

2006-01-01

Biological control of exotic invasive plants using exotic insects is practiced under the assumption that biological control agents are safe if they do not directly attack non-target species. We tested this assumption by evaluating the potential for two host-specific biological control agents (Urophora spp.), widely established in North America for spotted...

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...

Functional model of biological neural networks.

Science.gov (United States)

Lo, James Ting-Ho

2010-12-01

A functional model of biological neural networks, called temporal hierarchical probabilistic associative memory (THPAM), is proposed in this paper. THPAM comprises functional models of dendritic trees for encoding inputs to neurons, a first type of neuron for generating spike trains, a second type of neuron for generating graded signals to modulate neurons of the first type, supervised and unsupervised Hebbian learning mechanisms for easy learning and retrieving, an arrangement of dendritic trees for maximizing generalization, hardwiring for rotation-translation-scaling invariance, and feedback connections with different delay durations for neurons to make full use of present and past informations generated by neurons in the same and higher layers. These functional models and their processing operations have many functions of biological neural networks that have not been achieved by other models in the open literature and provide logically coherent answers to many long-standing neuroscientific questions. However, biological justifications of these functional models and their processing operations are required for THPAM to qualify as a macroscopic model (or low-order approximate) of biological neural networks.

Status of biological control in vegetation management in forestry

Science.gov (United States)

George P. Markin; Donald E. Gardner

1993-01-01

Biological control traditionally depends upon importing the natural enemies of introduced weeds. Since vegetation management in forestry has primarily been aimed at protecting economic species of trees from competition from other native plants, biological control has been of little use in forestry. An alternative approach to controlling unwanted native plants,...

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.

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.

A stress driven growth model for soft tissue considering biological availability

International Nuclear Information System (INIS)

Oller, S; Bellomo, F J; Nallim, L G; Armero, F

2010-01-01

Some of the key factors that regulate growth and remodeling of tissues are fundamentally mechanical. However, it is important to take into account the role of bioavailability together with the stresses and strains in the processes of normal or pathological growth. In this sense, the model presented in this work is oriented to describe the growth of soft biological tissue under 'stress driven growth' and depending on the biological availability of the organism. The general theoretical framework is given by a kinematic formulation in large strain combined with the thermodynamic basis of open systems. The formulation uses a multiplicative decomposition of deformation gradient, splitting it in a growth part and visco-elastic part. The strains due to growth are incompatible and are controlled by an unbalanced stresses related to a homeostatic state. Growth implies a volume change with an increase of mass maintaining constant the density. One of the most interesting features of the proposed model is the generation of new tissue taking into account the contribution of mass to the system controlled through biological availability. Because soft biological tissues in general have a hierarchical structure with several components (usually a soft matrix reinforced with collagen fibers), the developed growth model is suitable for the characterization of the growth of each component. This allows considering a different behavior for each of them in the context of a generalized theory of mixtures. Finally, we illustrate the response of the model in case of growth and atrophy with an application example.

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.

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.

[Cybernetics and biology].

Science.gov (United States)

Vasil'ev, G F

2013-01-01

Owing to methodical disadvantages, the theory of control still lacks the potential for the analysis of biological systems. To get the full benefit of the method in addition to the algorithmic model of control (as of today the only used model in the theory of control) a parametric model of control is offered to employ. The reasoning for it is explained. The approach suggested provides the possibility to use all potential of the modern theory of control for the analysis of biological systems. The cybernetic approach is shown taking a system of the rise of glucose concentration in blood as an example.

Ranked retrieval of Computational Biology models.

Science.gov (United States)

Henkel, Ron; Endler, Lukas; Peters, Andre; Le Novère, Nicolas; Waltemath, Dagmar

2010-08-11

The study of biological systems demands computational support. If targeting a biological problem, the reuse of existing computational models can save time and effort. Deciding for potentially suitable models, however, becomes more challenging with the increasing number of computational models available, and even more when considering the models' growing complexity. Firstly, among a set of potential model candidates it is difficult to decide for the model that best suits ones needs. Secondly, it is hard to grasp the nature of an unknown model listed in a search result set, and to judge how well it fits for the particular problem one has in mind. Here we present an improved search approach for computational models of biological processes. It is based on existing retrieval and ranking methods from Information Retrieval. The approach incorporates annotations suggested by MIRIAM, and additional meta-information. It is now part of the search engine of BioModels Database, a standard repository for computational models. The introduced concept and implementation are, to our knowledge, the first application of Information Retrieval techniques on model search in Computational Systems Biology. Using the example of BioModels Database, it was shown that the approach is feasible and extends the current possibilities to search for relevant models. The advantages of our system over existing solutions are that we incorporate a rich set of meta-information, and that we provide the user with a relevance ranking of the models found for a query. Better search capabilities in model databases are expected to have a positive effect on the reuse of existing models.

Social and economic factors for the adoption of biological control of ...

African Journals Online (AJOL)

The results also showed that the decision on the application of biological control is determined by the educational level, income, mechanization level, extension activities, biological control awareness, social participation, attitude toward biological control and access to information sources which have significant influence.

Control of the cassava mealybug in Africa: lessons from a biological ...

African Journals Online (AJOL)

Control of the cassava mealybug in Africa: lessons from a biological control project. ... Such studies are needed in order to attribute the observed effects to various causes and to advance the science of biological control. ( 4) It is concluded that biological control is the basis ofiPM but cannot usually be manipulated by the ...

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…

Self-Organized Biological Dynamics and Nonlinear Control

Science.gov (United States)

Walleczek, Jan

2006-04-01

The frontiers and challenges of biodynamics research Jan Walleczek; Part I. Nonlinear Dynamics in Biology and Response to Stimuli: 1. External signals and internal oscillation dynamics - principal aspects and response of stimulated rhythmic processes Friedemann Kaiser; 2. Nonlinear dynamics in biochemical and biophysical systems: from enzyme kinetics to epilepsy Raima Larter, Robert Worth and Brent Speelman; 3. Fractal mechanisms in neural control: human heartbeat and gait dynamics in health and disease Chung-Kang Peng, Jeffrey M. Hausdorff and Ary L. Goldberger; 4. Self-organising dynamics in human coordination and perception Mingzhou Ding, Yanqing Chen, J. A. Scott Kelso and Betty Tuller; 5. Signal processing in biochemical reaction networks Adam P. Arkin; Part II. Nonlinear Sensitivity of Biological Systems to Electromagnetic Stimuli: 6. Electrical signal detection and noise in systems with long-range coherence Paul C. Gailey; 7. Oscillatory signals in migrating neutrophils: effects of time-varying chemical and electrical fields Howard R. Petty; 8. Enzyme kinetics and nonlinear biochemical amplification in response to static and oscillating magnetic fields Jan Walleczek and Clemens F. Eichwald; 9. Magnetic field sensitivity in the hippocampus Stefan Engström, Suzanne Bawin and W. Ross Adey; Part III. Stochastic Noise-Induced Dynamics and Transport in Biological Systems: 10. Stochastic resonance: looking forward Frank Moss; 11. Stochastic resonance and small-amplitude signal transduction in voltage-gated ion channels Sergey M. Bezrukov and Igor Vodyanoy; 12. Ratchets, rectifiers and demons: the constructive role of noise in free energy and signal transduction R. Dean Astumian; 13. Cellular transduction of periodic and stochastic energy signals by electroconformational coupling Tian Y. Tsong; Part IV. Nonlinear Control of Biological and Other Excitable Systems: 14. Controlling chaos in dynamical systems Kenneth Showalter; 15. Electromagnetic fields and biological

Spatial Modeling Tools for Cell Biology

National Research Council Canada - National Science Library

Przekwas, Andrzej; Friend, Tom; Teixeira, Rodrigo; Chen, Z. J; Wilkerson, Patrick

2006-01-01

.... Scientific potentials and military relevance of computational biology and bioinformatics have inspired DARPA/IPTO's visionary BioSPICE project to develop computational framework and modeling tools for cell biology...

Optimization and Control of Agent-Based Models in Biology: A Perspective.

Science.gov (United States)

An, G; Fitzpatrick, B G; Christley, S; Federico, P; Kanarek, A; Neilan, R Miller; Oremland, M; Salinas, R; Laubenbacher, R; Lenhart, S

2017-01-01

Agent-based models (ABMs) have become an increasingly important mode of inquiry for the life sciences. They are particularly valuable for systems that are not understood well enough to build an equation-based model. These advantages, however, are counterbalanced by the difficulty of analyzing and using ABMs, due to the lack of the type of mathematical tools available for more traditional models, which leaves simulation as the primary approach. As models become large, simulation becomes challenging. This paper proposes a novel approach to two mathematical aspects of ABMs, optimization and control, and it presents a few first steps outlining how one might carry out this approach. Rather than viewing the ABM as a model, it is to be viewed as a surrogate for the actual system. For a given optimization or control problem (which may change over time), the surrogate system is modeled instead, using data from the ABM and a modeling framework for which ready-made mathematical tools exist, such as differential equations, or for which control strategies can explored more easily. Once the optimization problem is solved for the model of the surrogate, it is then lifted to the surrogate and tested. The final step is to lift the optimization solution from the surrogate system to the actual system. This program is illustrated with published work, using two relatively simple ABMs as a demonstration, Sugarscape and a consumer-resource ABM. Specific techniques discussed include dimension reduction and approximation of an ABM by difference equations as well systems of PDEs, related to certain specific control objectives. This demonstration illustrates the very challenging mathematical problems that need to be solved before this approach can be realistically applied to complex and large ABMs, current and future. The paper outlines a research program to address them.

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.

Unified Deep Learning Architecture for Modeling Biology Sequence.

Science.gov (United States)

Wu, Hongjie; Cao, Chengyuan; Xia, Xiaoyan; Lu, Qiang

2017-10-09

Prediction of the spatial structure or function of biological macromolecules based on their sequence remains an important challenge in bioinformatics. When modeling biological sequences using traditional sequencing models, characteristics, such as long-range interactions between basic units, the complicated and variable output of labeled structures, and the variable length of biological sequences, usually lead to different solutions on a case-by-case basis. This study proposed the use of bidirectional recurrent neural networks based on long short-term memory or a gated recurrent unit to capture long-range interactions by designing the optional reshape operator to adapt to the diversity of the output labels and implementing a training algorithm to support the training of sequence models capable of processing variable-length sequences. Additionally, the merge and pooling operators enhanced the ability to capture short-range interactions between basic units of biological sequences. The proposed deep-learning model and its training algorithm might be capable of solving currently known biological sequence-modeling problems through the use of a unified framework. We validated our model on one of the most difficult biological sequence-modeling problems currently known, with our results indicating the ability of the model to obtain predictions of protein residue interactions that exceeded the accuracy of current popular approaches by 10% based on multiple benchmarks.

Model checking biological systems described using ambient calculus

DEFF Research Database (Denmark)

Mardare, Radu Iulian; Priami, Corrado; Qualia, Paola

2005-01-01

Model checking biological systems described using ambient calculus. In Proc. of the second International Workshop on Computational Methods in Systems Biology (CMSB04), Lecture Notes in Bioinformatics 3082:85-103, Springer, 2005.......Model checking biological systems described using ambient calculus. In Proc. of the second International Workshop on Computational Methods in Systems Biology (CMSB04), Lecture Notes in Bioinformatics 3082:85-103, Springer, 2005....

Economic Benefit for Cuban Laurel Thrips Biological Control.

Science.gov (United States)

Shogren, C; Paine, T D

2016-02-01

The Cuban laurel thrips, Gynaikothrips ficorum Marchal (Thysanoptera: Phlaeothripidae), is a critical insect pest of Ficus microcarpa in California urban landscapes and production nurseries. Female thrips feed and oviposit on young Ficus leaves, causing the expanding leaves to fold or curl into a discolored leaf gall. There have been attempts to establish specialist predator natural enemies of the thrips, but no success has been reported. We resampled the same areas in 2013-2014 where we had released Montandoniola confusa (= morguesi) Streito and Matocq (Hemiptera: Anthocoridae) in southern California in 1995 but had been unable to recover individuals in 1997-1998. Thrips galls were significantly reduced in all three of the locations in the recent samples compared with the earlier samples. M. confusa was present in all locations and appears to be providing successful biological control. The value of the biological control, the difference between street trees in good foliage condition and trees with poor foliage, was $58,766,166. If thrips damage reduced the foliage to very poor condition, the value of biological control was $73,402,683. Total cost for the project was $61,830. The benefit accrued for every dollar spent on the biological control of the thrips ranged from $950, if the foliage was in poor condition, to $1,187, if the foliage was in very poor condition. The value of urban forest is often underappreciated. Economic analyses that clearly demonstrate the very substantial rates of return on investment in successful biological control in urban forests provide compelling arguments for supporting future efforts. © The Authors 2015. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

The markup is the model: reasoning about systems biology models in the Semantic Web era.

Science.gov (United States)

Kell, Douglas B; Mendes, Pedro

2008-06-07

Metabolic control analysis, co-invented by Reinhart Heinrich, is a formalism for the analysis of biochemical networks, and is a highly important intellectual forerunner of modern systems biology. Exchanging ideas and exchanging models are part of the international activities of science and scientists, and the Systems Biology Markup Language (SBML) allows one to perform the latter with great facility. Encoding such models in SBML allows their distributed analysis using loosely coupled workflows, and with the advent of the Internet the various software modules that one might use to analyze biochemical models can reside on entirely different computers and even on different continents. Optimization is at the core of many scientific and biotechnological activities, and Reinhart made many major contributions in this area, stimulating our own activities in the use of the methods of evolutionary computing for optimization.

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.

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.

Biological control of Mycosphaerella fragariae in strawberry culture

Directory of Open Access Journals (Sweden)

Anderson Luis Heling

2015-12-01

Full Text Available The Mycosphaerella spot is one of the main foliar diseases of strawberry, degrating great leaf regions and reducing the photosynthetic area. Its control is mainly by the use of chemical fungicides, but, due the increasing demand for food free of pesticide, alternative control methods have been researched, such as biological control. This work aimed to evaluate the effect on strawberry plants, treated with the biological control agents Bacillus cereus, Saccharomyces boulardii and Saccharomyces cerevisiae, in the severity of Mycosphaerella fragariae, productivity and in the activity of β-1.3 glucanases, peroxidases and chitinases enzymes. It was verified that S. cerevisiae and B. cereus treatments were similar to fungicide for disease control. However, even reducing the severity of the disease, there was no increase in productivity, and the different control agents do not cause changes in the evaluated defense mechanisms.

A biological compression model and its applications.

Science.gov (United States)

Cao, Minh Duc; Dix, Trevor I; Allison, Lloyd

2011-01-01

A biological compression model, expert model, is presented which is superior to existing compression algorithms in both compression performance and speed. The model is able to compress whole eukaryotic genomes. Most importantly, the model provides a framework for knowledge discovery from biological data. It can be used for repeat element discovery, sequence alignment and phylogenetic analysis. We demonstrate that the model can handle statistically biased sequences and distantly related sequences where conventional knowledge discovery tools often fail.

A Biomechanical Comparison of Proportional Electromyography Control to Biological Torque Control Using a Powered Hip Exoskeleton

Directory of Open Access Journals (Sweden)

Aaron J. Young

2017-06-01

Full Text Available BackgroundDespite a large increase in robotic exoskeleton research, there are few studies that have examined human performance with different control strategies on the same exoskeleton device. Direct comparison studies are needed to determine how users respond to different types of control. The purpose of this study was to compare user performance using a robotic hip exoskeleton with two different controllers: a controller that targeted a biological hip torque profile and a proportional myoelectric controller.MethodsWe tested both control approaches on 10 able-bodied subjects using a pneumatically powered hip exoskeleton. The state machine controller targeted a biological hip torque profile. The myoelectric controller used electromyography (EMG of lower limb muscles to produce a proportional control signal for the hip exoskeleton. Each subject performed two 30-min exoskeleton walking trials (1.0 m/s using each controller and a 10-min trial with the exoskeleton unpowered. During each trial, we measured subjects’ metabolic cost of walking, lower limb EMG profiles, and joint kinematics and kinetics (torques and powers using a force treadmill and motion capture.ResultsCompared to unassisted walking in the exoskeleton, myoelectric control significantly reduced metabolic cost by 13% (p = 0.005 and biological hip torque control reduced metabolic cost by 7% (p = 0.261. Subjects reduced muscle activity relative to the unpowered condition for a greater number of lower limb muscles using myoelectric control compared to the biological hip torque control. More subjects subjectively preferred the myoelectric controller to the biological hip torque control.ConclusionMyoelectric control had more advantages (metabolic cost and muscle activity reduction compared to a controller that targeted a biological torque profile for walking with a robotic hip exoskeleton. However, these results were obtained with a single exoskeleton device with specific

A Biomechanical Comparison of Proportional Electromyography Control to Biological Torque Control Using a Powered Hip Exoskeleton.

Science.gov (United States)

Young, Aaron J; Gannon, Hannah; Ferris, Daniel P

2017-01-01

Despite a large increase in robotic exoskeleton research, there are few studies that have examined human performance with different control strategies on the same exoskeleton device. Direct comparison studies are needed to determine how users respond to different types of control. The purpose of this study was to compare user performance using a robotic hip exoskeleton with two different controllers: a controller that targeted a biological hip torque profile and a proportional myoelectric controller. We tested both control approaches on 10 able-bodied subjects using a pneumatically powered hip exoskeleton. The state machine controller targeted a biological hip torque profile. The myoelectric controller used electromyography (EMG) of lower limb muscles to produce a proportional control signal for the hip exoskeleton. Each subject performed two 30-min exoskeleton walking trials (1.0 m/s) using each controller and a 10-min trial with the exoskeleton unpowered. During each trial, we measured subjects' metabolic cost of walking, lower limb EMG profiles, and joint kinematics and kinetics (torques and powers) using a force treadmill and motion capture. Compared to unassisted walking in the exoskeleton, myoelectric control significantly reduced metabolic cost by 13% ( p  = 0.005) and biological hip torque control reduced metabolic cost by 7% ( p  = 0.261). Subjects reduced muscle activity relative to the unpowered condition for a greater number of lower limb muscles using myoelectric control compared to the biological hip torque control. More subjects subjectively preferred the myoelectric controller to the biological hip torque control. Myoelectric control had more advantages (metabolic cost and muscle activity reduction) compared to a controller that targeted a biological torque profile for walking with a robotic hip exoskeleton. However, these results were obtained with a single exoskeleton device with specific control configurations while level walking at a

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...

Mathematical manipulative models: in defense of "beanbag biology".

Science.gov (United States)

Jungck, John R; Gaff, Holly; Weisstein, Anton E

2010-01-01

Mathematical manipulative models have had a long history of influence in biological research and in secondary school education, but they are frequently neglected in undergraduate biology education. By linking mathematical manipulative models in a four-step process-1) use of physical manipulatives, 2) interactive exploration of computer simulations, 3) derivation of mathematical relationships from core principles, and 4) analysis of real data sets-we demonstrate a process that we have shared in biological faculty development workshops led by staff from the BioQUEST Curriculum Consortium over the past 24 yr. We built this approach based upon a broad survey of literature in mathematical educational research that has convincingly demonstrated the utility of multiple models that involve physical, kinesthetic learning to actual data and interactive simulations. Two projects that use this approach are introduced: The Biological Excel Simulations and Tools in Exploratory, Experiential Mathematics (ESTEEM) Project (http://bioquest.org/esteem) and Numerical Undergraduate Mathematical Biology Education (NUMB3R5 COUNT; http://bioquest.org/numberscount). Examples here emphasize genetics, ecology, population biology, photosynthesis, cancer, and epidemiology. Mathematical manipulative models help learners break through prior fears to develop an appreciation for how mathematical reasoning informs problem solving, inference, and precise communication in biology and enhance the diversity of quantitative biology education.

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)

Dose prescription complexity versus tumor control probability in biologically conformal radiotherapy

International Nuclear Information System (INIS)

South, C. P.; Evans, P. M.; Partridge, M.

2009-01-01

The technical feasibility and potential benefits of voxel-based nonuniform dose prescriptions for biologically heterogeneous tumors have been widely demonstrated. In some cases, an ''ideal'' dose prescription has been generated by individualizing the dose to every voxel within the target, but often this voxel-based prescription has been discretized into a small number of compartments. The number of dose levels utilized and the methods used for prescribing doses and assigning tumor voxels to different dose compartments have varied significantly. The authors present an investigation into the relationship between the complexity of the dose prescription and the tumor control probability (TCP) for a number of these methods. The linear quadratic model of cell killing was used in conjunction with a number of modeled tumors heterogeneous in clonogen density, oxygenation, or proliferation. Models based on simple mathematical functions, published biological data, and biological image data were investigated. Target voxels were assigned to dose compartments using (i) simple rules based on the initial biological distribution, (ii) iterative methods designed to maximize the achievable TCP, or (iii) methods based on an ideal dose prescription. The relative performance of the simple rules was found to depend on the form of heterogeneity of the tumor, while the iterative and ideal dose methods performed comparably for all models investigated. In all cases the maximum achievable TCP was approached within the first few (typically two to five) compartments. Results suggest that irrespective of the pattern of heterogeneity, the optimal dose prescription can be well approximated using only a few dose levels but only if both the compartment boundaries and prescribed dose levels are well chosen.

Automated parameter estimation for biological models using Bayesian statistical model checking.

Science.gov (United States)

Hussain, Faraz; Langmead, Christopher J; Mi, Qi; Dutta-Moscato, Joyeeta; Vodovotz, Yoram; Jha, Sumit K

2015-01-01

Probabilistic models have gained widespread acceptance in the systems biology community as a useful way to represent complex biological systems. Such models are developed using existing knowledge of the structure and dynamics of the system, experimental observations, and inferences drawn from statistical analysis of empirical data. A key bottleneck in building such models is that some system variables cannot be measured experimentally. These variables are incorporated into the model as numerical parameters. Determining values of these parameters that justify existing experiments and provide reliable predictions when model simulations are performed is a key research problem. Using an agent-based model of the dynamics of acute inflammation, we demonstrate a novel parameter estimation algorithm by discovering the amount and schedule of doses of bacterial lipopolysaccharide that guarantee a set of observed clinical outcomes with high probability. We synthesized values of twenty-eight unknown parameters such that the parameterized model instantiated with these parameter values satisfies four specifications describing the dynamic behavior of the model. We have developed a new algorithmic technique for discovering parameters in complex stochastic models of biological systems given behavioral specifications written in a formal mathematical logic. Our algorithm uses Bayesian model checking, sequential hypothesis testing, and stochastic optimization to automatically synthesize parameters of probabilistic biological models.

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.

Economic value of biological control in integrated pest management of managed plant systems.

Science.gov (United States)

Naranjo, Steven E; Ellsworth, Peter C; Frisvold, George B

2015-01-07

Biological control is an underlying pillar of integrated pest management, yet little focus has been placed on assigning economic value to this key ecosystem service. Setting biological control on a firm economic foundation would help to broaden its utility and adoption for sustainable crop protection. Here we discuss approaches and methods available for valuation of biological control of arthropod pests by arthropod natural enemies and summarize economic evaluations in classical, augmentative, and conservation biological control. Emphasis is placed on valuation of conservation biological control, which has received little attention. We identify some of the challenges of and opportunities for applying economics to biological control to advance integrated pest management. Interaction among diverse scientists and stakeholders will be required to measure the direct and indirect costs and benefits of biological control that will allow farmers and others to internalize the benefits that incentivize and accelerate adoption for private and public good.

Efficiency of using green algae as biological controllers against toxic ...

African Journals Online (AJOL)

Efficiency of using green algae as biological controllers against toxic algal taxa in cultured ... of two green algal species as biological control of the growth of toxic blue-green algae. ... African Journal of Aquatic Science 2014, 39(4): 443–450 ...

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.

Assessing Probabilistic Risk Assessment Approaches for Insect Biological Control Introductions.

Science.gov (United States)

Kaufman, Leyla V; Wright, Mark G

2017-07-07

The introduction of biological control agents to new environments requires host specificity tests to estimate potential non-target impacts of a prospective agent. Currently, the approach is conservative, and is based on physiological host ranges determined under captive rearing conditions, without consideration for ecological factors that may influence realized host range. We use historical data and current field data from introduced parasitoids that attack an endemic Lepidoptera species in Hawaii to validate a probabilistic risk assessment (PRA) procedure for non-target impacts. We use data on known host range and habitat use in the place of origin of the parasitoids to determine whether contemporary levels of non-target parasitism could have been predicted using PRA. Our results show that reasonable predictions of potential non-target impacts may be made if comprehensive data are available from places of origin of biological control agents, but scant data produce poor predictions. Using apparent mortality data rather than marginal attack rate estimates in PRA resulted in over-estimates of predicted non-target impact. Incorporating ecological data into PRA models improved the predictive power of the risk assessments.

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.

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.

Arms Control: US and International efforts to ban biological weapons

Energy Technology Data Exchange (ETDEWEB)

1992-12-01

The Bacteriological (Biological) and Toxin Weapons Convention, the treaty that bans the development, production, and stockpiling and acquisition of biological weapons was opened for signature in 1972 and came into force in 1975 after being ratified by 22 governments, including the depository nations of the USA, the United Kingdom, and the former Soviet Union. In support of the Convention, the USA later established export controls on items used to make biological weapons. Further, in accordance with the 1990 President`s Enhanced Proliferation Control Initiative, actions were taken to redefine and expand US export controls, as well as to encourage multilateral controls through the Australia Group. Thus far, the Convention has not been effective in stopping the development of biological weapons. The principal findings as to the reasons of the failures of the Convention are found to be: the Convention lacks universality, compliance measures are effective, advantage of verification may outweigh disadvantages. Recommendations for mitigating these failures are outlined in this report.

Characterization and control of biological microrobots

NARCIS (Netherlands)

Khalil, I.S.M.; Pichel, Marc Philippe; Zondervan, L.; Abelmann, Leon; Misra, Sarthak; Desai, Jaydev P.; Dudek, Gregory; Khatib, Oussama; Kumar, Vijay

2013-01-01

This work addresses the characterization and control of Magnetotactic Bacterium (MTB) which can be considered as a biological microrobot. Magnetic dipole moment of the MTB and response to a field-with-alternating-direction are characterized. First, the magnetic dipole moment is characterized using

Characterization and Control of Biological Microrobots

NARCIS (Netherlands)

Khalil, I.S.M.; Pichel, Marc Philippe; Pichel, M.P.; Zondervan, L.; Abelmann, Leon; Misra, Sarthak

2012-01-01

This work addresses the characterization and control of Magnetotactic Bacterium (MTB) which can be considered as a biological microrobot. Magnetic dipole moment of the MTB and response to a field-with-alternating-direction are characterized. First, the magnetic dipole moment is characterized using

Feedback dynamics and cell function: Why systems biology is called Systems Biology.

Science.gov (United States)

Wolkenhauer, Olaf; Mesarovic, Mihajlo

2005-05-01

A new paradigm, like Systems Biology, should challenge the way research has been conducted previously. This Opinion article aims to present Systems Biology, not as the application of engineering principles to biology but as a merger of systems- and control theory with molecular- and cell biology. In our view, the central dogma of Systems Biology is that it is system dynamics that gives rise to the functioning and function of cells. The concepts of feedback regulation and control of pathways and the coordination of cell function are emphasized as an important area of Systems Biology research. The hurdles and risks for this area are discussed from the perspective of dynamic pathway modelling. Most of all, the aim of this article is to promote mathematical modelling and simulation as a part of molecular- and cell biology. Systems Biology is a success if it is widely accepted that there is nothing more practical than a good theory.

Artificial cell mimics as simplified models for the study of cell biology.

Science.gov (United States)

Salehi-Reyhani, Ali; Ces, Oscar; Elani, Yuval

2017-07-01

Living cells are hugely complex chemical systems composed of a milieu of distinct chemical species (including DNA, proteins, lipids, and metabolites) interconnected with one another through a vast web of interactions: this complexity renders the study of cell biology in a quantitative and systematic manner a difficult task. There has been an increasing drive towards the utilization of artificial cells as cell mimics to alleviate this, a development that has been aided by recent advances in artificial cell construction. Cell mimics are simplified cell-like structures, composed from the bottom-up with precisely defined and tunable compositions. They allow specific facets of cell biology to be studied in isolation, in a simplified environment where control of variables can be achieved without interference from a living and responsive cell. This mini-review outlines the core principles of this approach and surveys recent key investigations that use cell mimics to address a wide range of biological questions. It will also place the field in the context of emerging trends, discuss the associated limitations, and outline future directions of the field. Impact statement Recent years have seen an increasing drive to construct cell mimics and use them as simplified experimental models to replicate and understand biological phenomena in a well-defined and controlled system. By summarizing the advances in this burgeoning field, and using case studies as a basis for discussion on the limitations and future directions of this approach, it is hoped that this minireview will spur others in the experimental biology community to use artificial cells as simplified models with which to probe biological systems.

The role of ionizing radiation in biological control of agricultural pests

International Nuclear Information System (INIS)

Mansour, M.

2011-01-01

Although the commercial biological control industry is growing, it still represents only a small portion of the international market of pest control sales (about 3%). This low ratio is due to several factors including high cost of production of biological control agents and technical and regulatory difficulties that complicate the shipping procedures and create trade barriers. This article summarizes the role of ionizing radiation in supporting the use of biological control agents in insect pest control and concentrates on its role in the production, transport, distribution, and release of parasites and predators and the advantages that ionizing radiation can offer, in comparison with traditional techniques. (author)

BioModels Database: a repository of mathematical models of biological processes.

Science.gov (United States)

Chelliah, Vijayalakshmi; Laibe, Camille; Le Novère, Nicolas

2013-01-01

BioModels Database is a public online resource that allows storing and sharing of published, peer-reviewed quantitative, dynamic models of biological processes. The model components and behaviour are thoroughly checked to correspond the original publication and manually curated to ensure reliability. Furthermore, the model elements are annotated with terms from controlled vocabularies as well as linked to relevant external data resources. This greatly helps in model interpretation and reuse. Models are stored in SBML format, accepted in SBML and CellML formats, and are available for download in various other common formats such as BioPAX, Octave, SciLab, VCML, XPP and PDF, in addition to SBML. The reaction network diagram of the models is also available in several formats. BioModels Database features a search engine, which provides simple and more advanced searches. Features such as online simulation and creation of smaller models (submodels) from the selected model elements of a larger one are provided. BioModels Database can be accessed both via a web interface and programmatically via web services. New models are available in BioModels Database at regular releases, about every 4 months.

Biology of Leptoypha hospita (Hemiptera: Tingidae), a Potential Biological Control Agent of Chinese Privet

Science.gov (United States)

Yanzhuo Zhang; James L. Hanula; Scott Horn; Kristine Braman; Jianghua Sun

2011-01-01

The biology of Leptoypha hospita Drake et Poor (Hemiptera: Tingidae), a potential biological control agent from China for Chinese privet, Ligustrum sinense Lour., was studied in quarantine in the United States. Both nymphs and adults feed on Chinese privet mesophyll cells that lead to a bleached appearance of leaves and dieback of branch tips. L. hospita has five...

21 CFR 310.4 - Biologics; products subject to license control.

Science.gov (United States)

2010-04-01

... 21 Food and Drugs 5 2010-04-01 2010-04-01 false Biologics; products subject to license control... to license control. (a) If a drug has an approved license under section 351 of the Public Health.... (b) To obtain marketing approval for radioactive biological products for human use, as defined in...

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.

Model checking optimal finite-horizon control for probabilistic gene regulatory networks.

Science.gov (United States)

Wei, Ou; Guo, Zonghao; Niu, Yun; Liao, Wenyuan

2017-12-14

Probabilistic Boolean networks (PBNs) have been proposed for analyzing external control in gene regulatory networks with incorporation of uncertainty. A context-sensitive PBN with perturbation (CS-PBNp), extending a PBN with context-sensitivity to reflect the inherent biological stability and random perturbations to express the impact of external stimuli, is considered to be more suitable for modeling small biological systems intervened by conditions from the outside. In this paper, we apply probabilistic model checking, a formal verification technique, to optimal control for a CS-PBNp that minimizes the expected cost over a finite control horizon. We first describe a procedure of modeling a CS-PBNp using the language provided by a widely used probabilistic model checker PRISM. We then analyze the reward-based temporal properties and the computation in probabilistic model checking; based on the analysis, we provide a method to formulate the optimal control problem as minimum reachability reward properties. Furthermore, we incorporate control and state cost information into the PRISM code of a CS-PBNp such that automated model checking a minimum reachability reward property on the code gives the solution to the optimal control problem. We conduct experiments on two examples, an apoptosis network and a WNT5A network. Preliminary experiment results show the feasibility and effectiveness of our approach. The approach based on probabilistic model checking for optimal control avoids explicit computation of large-size state transition relations associated with PBNs. It enables a natural depiction of the dynamics of gene regulatory networks, and provides a canonical form to formulate optimal control problems using temporal properties that can be automated solved by leveraging the analysis power of underlying model checking engines. This work will be helpful for further utilization of the advances in formal verification techniques in system biology.

Biological effect of penetration controlled irradiation with ion beams

Energy Technology Data Exchange (ETDEWEB)

Tanaka, Atsushi; Shimizu, Takashi; Kikuchi, Masahiro; Kobayashi, Yasuhiko; Watanabe, Hiroshi [Japan Atomic Energy Research Inst., Takasaki, Gunma (Japan). Takasaki Radiation Chemistry Research Establishment; Yamashita, Takao

1997-03-01

To investigate the effect of local irradiation with ion beams on biological systems, technique for penetration controlled irradiation has been established. The range in a target was controlled by changing the distance from beam window in the atmosphere, and could be controlled linearly up to about 31 {mu}m in biological material. In addition, the effects of the penetration controlled irradiations with 1.5 MeV/u C and He ions were examined using tobacco pollen. The increased frequency of leaky pollen produced by ion beams suggests that the efficient pollen envelope damages would be induced at the range-end of ion beams. (author)

Predictive modelling of complex agronomic and biological systems.

Science.gov (United States)

Keurentjes, Joost J B; Molenaar, Jaap; Zwaan, Bas J

2013-09-01

Biological systems are tremendously complex in their functioning and regulation. Studying the multifaceted behaviour and describing the performance of such complexity has challenged the scientific community for years. The reduction of real-world intricacy into simple descriptive models has therefore convinced many researchers of the usefulness of introducing mathematics into biological sciences. Predictive modelling takes such an approach another step further in that it takes advantage of existing knowledge to project the performance of a system in alternating scenarios. The ever growing amounts of available data generated by assessing biological systems at increasingly higher detail provide unique opportunities for future modelling and experiment design. Here we aim to provide an overview of the progress made in modelling over time and the currently prevalent approaches for iterative modelling cycles in modern biology. We will further argue for the importance of versatility in modelling approaches, including parameter estimation, model reduction and network reconstruction. Finally, we will discuss the difficulties in overcoming the mathematical interpretation of in vivo complexity and address some of the future challenges lying ahead. © 2013 John Wiley & Sons Ltd.

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...

Understanding Federal regulations as guidelines for classical biological control programs

Science.gov (United States)

Michael E. Montgomery

2011-01-01

This chapter reviews the legislation and rules that provide the foundation for federal regulation of the introduction of natural enemies of insects as biological control agents. It also outlines the steps for complying with regulatory requirements, using biological control of Adelges tsugae Annand, the hemlock woolly adelgid (HWA), as an example. The...

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.

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.

Using biological control research in the classroom to promote scientific inquiry and literacy

Science.gov (United States)

Many scientists who research biological control also teach at universities or more informally through cooperative outreach. The purpose of this paper is to review biological control activities for the classroom in four refereed journals, The American Biology Teacher, Journal of Biological Education...

Synthetic biology and regulatory networks: where metabolic systems biology meets control engineering.

Science.gov (United States)

He, Fei; Murabito, Ettore; Westerhoff, Hans V

2016-04-01

Metabolic pathways can be engineered to maximize the synthesis of various products of interest. With the advent of computational systems biology, this endeavour is usually carried out through in silico theoretical studies with the aim to guide and complement further in vitro and in vivo experimental efforts. Clearly, what counts is the result in vivo, not only in terms of maximal productivity but also robustness against environmental perturbations. Engineering an organism towards an increased production flux, however, often compromises that robustness. In this contribution, we review and investigate how various analytical approaches used in metabolic engineering and synthetic biology are related to concepts developed by systems and control engineering. While trade-offs between production optimality and cellular robustness have already been studied diagnostically and statically, the dynamics also matter. Integration of the dynamic design aspects of control engineering with the more diagnostic aspects of metabolic, hierarchical control and regulation analysis is leading to the new, conceptual and operational framework required for the design of robust and productive dynamic pathways. © 2016 The Author(s).

Economic Benefits of Advanced Control Strategies in Biological Nutrient Removal Systems

DEFF Research Database (Denmark)

Carstensen, J.; Nielsen, M.K.; Harremoës, Poul

1994-01-01

little regards to the variations in load and biomass activity. However, these dynamics can be evaluated on-line using grey box models to describe the most important features of the hydraulic and biological processes. Simulation studies of plants with an alternating process have shown that control...... strategies incorporating information from the grey box models are capable of reducing the total nitrogen discharge as well as energy costs. These results have a major impact on both existing and future plants. In fact, it is expected that future plants can be reduced with 10-20 per cent in size...

Biological control of ticks

Science.gov (United States)

Samish, M.; Ginsberg, H.; Glazer, I.; Bowman, A.S.; Nuttall, P.

2004-01-01

Ticks have numerous natural enemies, but only a few species have been evaluated as tick biocontrol agents (BCAs). Some laboratory results suggest that several bacteria are pathogenic to ticks, but their mode of action and their potential value as biocontrol agents remain to be determined. The most promising entomopathogenic fungi appear to be Metarhizium anisopliae and Beauveria bassiana, strains of which are already commercially available for the control of some pests. Development of effective formulations is critical for tick management. Entomopathogenic nematodes that are pathogenic to ticks can potentially control ticks, but improved formulations and selection of novel nematode strains are needed. Parasitoid wasps of the genus Ixodiphagus do not typically control ticks under natural conditions, but inundative releases show potential value. Most predators of ticks are generalists, with a limited potential for tick management (one possible exception is oxpeckers in Africa). Biological control is likely to play a substantial role in future IPM programmes for ticks because of the diversity of taxa that show high potential as tick BCAs. Considerable research is required to select appropriate strains, develop them as BCAs, establish their effectiveness, and devise production strategies to bring them to practical use.

Using Biological-Control Research in the Classroom to Promote Scientific Inquiry & Literacy

Science.gov (United States)

Richardson, Matthew L.; Richardson, Scott L.; Hall, David G.

2012-01-01

Scientists researching biological control should engage in education because translating research programs into classroom activities is a pathway to increase scientific literacy among students. Classroom activities focused on biological control target all levels of biological organization and can be cross-disciplinary by drawing from subject areas…

Isolation of microorganisms for biological control the moniliophthora roreri

OpenAIRE

suarez contreras, liliana yanet; Rangel Riaño, Alba Luz

2014-01-01

Moniliophlhora roreri is the causal agent of cocoa Moniliasis, which produces losses of up to 60% of the crop, as it affects only its commercial product, the cob. Biological control appears as an alternative management, using endophytic microorganisms. The reason because of this research came up was that it was aimed to isolate microorganisms with antagonist potential for biological control towards the phytopathogen M. roreri in Norte de Santander. This is done through isolation and identifica...

Microbiome studies in the biological control of plant pathogens

Science.gov (United States)

Biological control of plant pathogens, although it has been a successful alternative that has allowed to select microorganisms for the generation of bioproducts and to understand multiple biological mechanisms, cannot be considered as a strategy defined only from the selection of a range of cultiva...

Assessing Probabilistic Risk Assessment Approaches for Insect Biological Control Introductions

Directory of Open Access Journals (Sweden)

Leyla V. Kaufman

2017-07-01

Full Text Available The introduction of biological control agents to new environments requires host specificity tests to estimate potential non-target impacts of a prospective agent. Currently, the approach is conservative, and is based on physiological host ranges determined under captive rearing conditions, without consideration for ecological factors that may influence realized host range. We use historical data and current field data from introduced parasitoids that attack an endemic Lepidoptera species in Hawaii to validate a probabilistic risk assessment (PRA procedure for non-target impacts. We use data on known host range and habitat use in the place of origin of the parasitoids to determine whether contemporary levels of non-target parasitism could have been predicted using PRA. Our results show that reasonable predictions of potential non-target impacts may be made if comprehensive data are available from places of origin of biological control agents, but scant data produce poor predictions. Using apparent mortality data rather than marginal attack rate estimates in PRA resulted in over-estimates of predicted non-target impact. Incorporating ecological data into PRA models improved the predictive power of the risk assessments.

Version control of pathway models using XML patches.

Science.gov (United States)

Saffrey, Peter; Orton, Richard

2009-03-17

Computational modelling has become an important tool in understanding biological systems such as signalling pathways. With an increase in size complexity of models comes a need for techniques to manage model versions and their relationship to one another. Model version control for pathway models shares some of the features of software version control but has a number of differences that warrant a specific solution. We present a model version control method, along with a prototype implementation, based on XML patches. We show its application to the EGF/RAS/RAF pathway. Our method allows quick and convenient storage of a wide range of model variations and enables a thorough explanation of these variations. Trying to produce these results without such methods results in slow and cumbersome development that is prone to frustration and human error.

Biologically controlled minerals as potential indicators of life

Science.gov (United States)

Schwartz, D. E.; Mancinelli, R. L.; Kaneshiro, E.

1991-01-01

Minerals can be produced and deposited either by abiotic or biologic means. Regardless of their origin, mineral crystals reflect the environment conditions (e.g., temperature, pressure, chemical composition, and redox potential) present during crystal formation. Biologically-produced mineral crystals are grown or reworked under the control of their host organism and reflect an environment different from the abiotic environment. In addition, minerals of either biologic or abiotic origin have great longevities. For these reasons, biologically produced minerals have been proposed as biomarkers. Biomarkers are key morphological, chemical, and isotopic signatures of living systems that can be used to determine if life processes have occurred. Studies of biologically controlled minerals produced by the protist, Paramecium tetraurelia, were initiated since techniques have already been developed to culture them and isolate their crystalline material, and methods are already in place to analyze this material. Two direct crystalline phases were identified. One phase, whose chemical composition is high in Mg, was identified as struvite. The second phase, whose chemical composition is high in Ca, has not been previously found occurring naturally and may be considered a newly discovered material. Analyses are underway to determine the characteristics of these minerals in order to compare them with characteristics of these minerals in order to compare them with characteristics of minerals formed abiotically, but with the same chemical composition.

Continuum Modeling of Biological Network Formation

KAUST Repository

Albi, Giacomo; Burger, Martin; Haskovec, Jan; Markowich, Peter A.; Schlottbom, Matthias

2017-01-01

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

Theoretical Biology and Medical Modelling: ensuring continued growth and future leadership.

Science.gov (United States)

Nishiura, Hiroshi; Rietman, Edward A; Wu, Rongling

2013-07-11

Theoretical biology encompasses a broad range of biological disciplines ranging from mathematical biology and biomathematics to philosophy of biology. Adopting a broad definition of "biology", Theoretical Biology and Medical Modelling, an open access journal, considers original research studies that focus on theoretical ideas and models associated with developments in biology and medicine.

Augmentative biological control of arthropods in Latin America

NARCIS (Netherlands)

Lenteren, van J.C.; Bueno, V.H.P.

2003-01-01

Augmentative forms of biological control, where natural enemies are periodically introduced, are applied over large areas in various cropping systems in Latin America. About 25% of the world area under augmentative control is situated in this region. Well-known examples are the use of species of the

On the limitations of standard statistical modeling in biological systems: a full Bayesian approach for biology.

Science.gov (United States)

Gomez-Ramirez, Jaime; Sanz, Ricardo

2013-09-01

One of the most important scientific challenges today is the quantitative and predictive understanding of biological function. Classical mathematical and computational approaches have been enormously successful in modeling inert matter, but they may be inadequate to address inherent features of biological systems. We address the conceptual and methodological obstacles that lie in the inverse problem in biological systems modeling. We introduce a full Bayesian approach (FBA), a theoretical framework to study biological function, in which probability distributions are conditional on biophysical information that physically resides in the biological system that is studied by the scientist. Copyright © 2013 Elsevier Ltd. All rights reserved.

Ex-ante analysis of economic returns from biological control of coconut mite in Tanzania

NARCIS (Netherlands)

Oleke, J.M.; Manyong, V.; Mignouna, D.; Isinika, A.; Mutabazi, K.; Hanna, R.; Sabelis, M.

2013-01-01

The coconut mite, Aceria guerreronis Keifer, has been identified as one of the pests that pose a threat to the coconut industry in Benin. The study presents the simulation results of the economic benefits of the biological control of coconut mites in Benin using a standard economic surplus model. In

Biologically-Inspired Control Architecture for Musical Performance Robots

Directory of Open Access Journals (Sweden)

Jorge Solis

2014-10-01

Full Text Available At Waseda University, since 1990, the authors have been developing anthropomorphic musical performance robots as a means for understanding human control, introducing novel ways of interaction between musical partners and robots, and proposing applications for humanoid robots. In this paper, the design of a biologically-inspired control architecture for both an anthropomorphic flutist robot and a saxophone playing robot are described. As for the flutist robot, the authors have focused on implementing an auditory feedback system to improve the calibration procedure for the robot in order to play all the notes correctly during a performance. In particular, the proposed auditory feedback system is composed of three main modules: an Expressive Music Generator, a Feed Forward Air Pressure Control System and a Pitch Evaluation System. As for the saxophone-playing robot, a pressure-pitch controller (based on the feedback error learning to improve the sound produced by the robot during a musical performance was proposed and implemented. In both cases studied, a set of experiments are described to verify the improvements achieved while considering biologically-inspired control approaches.

Evaluation of Orius species for biological control of Frankliniella occidentalis (Pergande) (Thysanoptera: Thripidae)

NARCIS (Netherlands)

Tommasini, M.G.

2003-01-01

Key words: Thysanoptera, Frankliniella occidentalis, Heteroptera, Orius leavigatu, Orius majusculu, Orius niger, Orius insidiosus, Biology, Diapause, Biological control.The overall aim of this research was to develop a biological control programme for F. occidentalis through the selection of

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

DEFF Research Database (Denmark)

Green, Sara; Batterman, Robert

2017-01-01

A common reductionist assumption is that macro-scale behaviors can be described "bottom-up" if only sufficient details about lower-scale processes are available. The view that an "ideal" or "fundamental" physics would be sufficient to explain all macro-scale phenomena has been met with criticism ...... modeling in developmental biology. In such contexts, the relation between models at different scales and from different disciplines is neither reductive nor completely autonomous, but interdependent....... 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...

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.

Opportunities for biological weed control in Europe

NARCIS (Netherlands)

Scheepens, P.C.; Müller-Schärer, H.; Kempenaar, C.

2001-01-01

The development and application of biological weed control offer greatopportunities not only for farmers, nature conservationists and othervegetation managers but also for institutions and companies that wish tosell plant protection services and products, and for the general publicthat demands safe

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...

Genome Scale Modeling in Systems Biology: Algorithms and Resources

Science.gov (United States)

Najafi, Ali; Bidkhori, Gholamreza; Bozorgmehr, Joseph H.; Koch, Ina; Masoudi-Nejad, Ali

2014-01-01

In recent years, in silico studies and trial simulations have complemented experimental procedures. A model is a description of a system, and a system is any collection of interrelated objects; an object, moreover, is some elemental unit upon which observations can be made but whose internal structure either does not exist or is ignored. Therefore, any network analysis approach is critical for successful quantitative modeling of biological systems. This review highlights some of most popular and important modeling algorithms, tools, and emerging standards for representing, simulating and analyzing cellular networks in five sections. Also, we try to show these concepts by means of simple example and proper images and graphs. Overall, systems biology aims for a holistic description and understanding of biological processes by an integration of analytical experimental approaches along with synthetic computational models. In fact, biological networks have been developed as a platform for integrating information from high to low-throughput experiments for the analysis of biological systems. We provide an overview of all processes used in modeling and simulating biological networks in such a way that they can become easily understandable for researchers with both biological and mathematical backgrounds. Consequently, given the complexity of generated experimental data and cellular networks, it is no surprise that researchers have turned to computer simulation and the development of more theory-based approaches to augment and assist in the development of a fully quantitative understanding of cellular dynamics. PMID:24822031

Selection of Trichogramma for inundative biological control

NARCIS (Netherlands)

Pak, G.A.

1988-01-01

This thesis presents a study of the potential for biological control of lepidopterous pests on cabbage crops in the Netherlands, by means of inundative releases of the egg parasite Trichogramma (Hymenoptera, Trichogrammatidae). The objective of this study is to investigate the

Incorporating biological control into IPM decision making

Science.gov (United States)

Of the many ways biological control can be incorporated into Integrated Pest Management (IPM) programs, natural enemy thresholds are arguably most easily adopted by stakeholders. Integration of natural enemy thresholds into IPM programs requires ecological and cost/benefit crop production data, thr...

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

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

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...

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.

Biological forcing controls the chemistry of the coral exoskeleton

Science.gov (United States)

Meibom, A.; Mostefaoui, S.; Cuif, J.; Yurimoto, H.; Dauphin, Y.; Houlbreque, F.; Dunbar, R.; Constantz, B.

2006-12-01

A multitude of marine organisms produce calcium carbonate skeletons that are used extensively to reconstruct water temperature variability of the tropical and subtropical oceans - a key parameter in global climate-change models. Such paleo-climate reconstructions are based on the notion that skeletal oxygen isotopic composition and certain trace-element abundances (e.g., Sr/Ca and Mg/Ca ratios) vary in response to changes in the water temperature. However, it is a fundamental problem that poorly understood biological processes introduce large compositional deviations from thermodynamic equilibrium and hinder precise calibrations of many paleo-climate proxies. Indeed, the role of water temperature in controlling the composition of the skeleton is far from understood. We have studied trace-element abundances as well as oxygen and carbon isotopic compositions of individual skeletal components in the zooxanthellate and non-zooxanthellate corals at ultra-structural, i.e. micrometer to sub-micrometer length scales. From this body of work we draw the following, generalized conclusions: 1) Centers of calcification (COC) are not in equilibrium with seawater. Notably, the Sr/Ca ratio is higher than expected for aragonite equilibrium with seawater at the temperature at which the skeleton was formed. Furthermore, the COC are further away from equilibrium with seawater than fibrous skeleton in terms of stable isotope composition. 2) COC are dramatically different from the fibrous aragonite skeleton in terms of trace element composition. 3) Neither trace element nor stable isotope variations in the fibrous (bulk) part of the skeleton are directly related to changes in SST. In fact, changes in SST can have very little to do with the observed compositional variations. 4) Trace element variations in the fibrous (bulk) part of the skeleton are not related to the activity of zooxanthellae. These observations are directly relevant to the issue of biological versus non-biological

Global existence and asymptotic behavior of a model for biological control of invasive species via supermale introduction

KAUST Repository

Parshad, Rana

2013-01-01

The purpose of this manuscript is to propose a model for the biological control of invasive species, via introduction of phenotypically modified organisms into a target population. We are inspired by the earlier Trojan Y Chromosome model [J.B. Gutierrez, J.L. Teem, J. Theo. Bio., 241(22), 333-341, 2006]. However, in the current work, we remove the assumption of logisticgrowth rate, and do not consider the addition of sex-reversed supermales. Also the constant birth and death coefficients, considered earlier, are replaced by functionally dependent ones. In this case the nonlinearities present serious difficulties since they change sign, and the components of the solution are not a priori bounded, in some Lp-space for p large, to permit theapplication of the well known regularizing effect principle. Thus functional methods to deducethe global existence in time, for the system in question, are not applicable. Our techniques are based on the Lyapunov functional method. We prove global existence of solutions, as well asexistence of a finite dimensional global attractor, that supports states of extinction. Our analytical finding are in accordance with numerical simulations, which we also present. © 2013 International Press.

An Integrated Biological Control System At Hanford

International Nuclear Information System (INIS)

Johnson, A.R.; Caudill, J.G.; Giddings, R.F.; Rodriguez, J.M.; Roos, R.C.; Wilde, J.W.

2010-01-01

In 1999 an integrated biological control system was instituted at the U.S. Department of Energy's Hanford Site. Successes and changes to the program needed to be communicated to a large and diverse mix of organizations and individuals. Efforts at communication are directed toward the following: Hanford Contractors (Liquid or Tank Waste, Solid Waste, Environmental Restoration, Science and Technology, Site Infrastructure), General Hanford Employees, and Hanford Advisory Board (Native American Tribes, Environmental Groups, Local Citizens, Washington State and Oregon State regulatory agencies). Communication was done through direct interface meetings, individual communication, where appropriate, and broadly sharing program reports. The objectives of the communication efforts was to have the program well coordinated with Hanford contractors, and to have the program understood well enough that all stakeholders would have confidence in the work performed by the program to reduce or elimate spread of radioactive contamination by biotic vectors. Communication of successes and changes to an integrated biological control system instituted in 1999 at the Department of Energy's Hanford Site have required regular interfaces with not only a diverse group of Hanford contractors (i.e., those responsible for liquid or tank waste, solid wastes, environmental restoration, science and technology, and site infrastructure), and general Hanford employees, but also with a consortium of designated stake holders organized as the Hanford Advisory Board (i.e., Native American tribes, various environmental groups, local citizens, Washington state and Oregon regulatory agencies, etc.). Direct interface meetings, individual communication where appropriate, and transparency of the biological control program were the methods and outcome of this effort.

AN INTEGRATED BIOLOGICAL CONTROL SYSTEM AT HANFORD

Energy Technology Data Exchange (ETDEWEB)

JOHNSON AR; CAUDILL JG; GIDDINGS RF; RODRIGUEZ JM; ROOS RC; WILDE JW

2010-02-11

In 1999 an integrated biological control system was instituted at the U.S. Department of Energy's Hanford Site. Successes and changes to the program needed to be communicated to a large and diverse mix of organizations and individuals. Efforts at communication are directed toward the following: Hanford Contractors (Liquid or Tank Waste, Solid Waste, Environmental Restoration, Science and Technology, Site Infrastructure), General Hanford Employees, and Hanford Advisory Board (Native American Tribes, Environmental Groups, Local Citizens, Washington State and Oregon State regulatory agencies). Communication was done through direct interface meetings, individual communication, where appropriate, and broadly sharing program reports. The objectives of the communication efforts was to have the program well coordinated with Hanford contractors, and to have the program understood well enough that all stakeholders would have confidence in the work performed by the program to reduce or elimated spread of radioactive contamination by biotic vectors. Communication of successes and changes to an integrated biological control system instituted in 1999 at the Department of Energy's Hanford Site have required regular interfaces with not only a diverse group of Hanford contractors (i.e., those responsible for liquid or tank waste, solid wastes, environmental restoration, science and technology, and site infrastructure), and general Hanford employees, but also with a consortium of designated stake holders organized as the Hanford Advisory Board (i.e., Native American tribes, various environmental groups, local citizens, Washington state and Oregon regulatory agencies, etc.). Direct interface meetings, individual communication where appropriate, and transparency of the biological control program were the methods and outcome of this effort.

Maternal feeding controls fetal biological clock.

Directory of Open Access Journals (Sweden)

Hidenobu Ohta

Full Text Available BACKGROUND: It is widely accepted that circadian physiological rhythms of the fetus are affected by oscillators in the maternal brain that are coupled to the environmental light-dark (LD cycle. METHODOLOGY/PRINCIPAL FINDINGS: To study the link between fetal and maternal biological clocks, we investigated the effects of cycles of maternal food availability on the rhythms of Per1 gene expression in the fetal suprachiasmatic nucleus (SCN and liver using a transgenic rat model whose tissues express luciferase in vitro. Although the maternal SCN remained phase-locked to the LD cycle, maternal restricted feeding phase-advanced the fetal SCN and liver by 5 and 7 hours respectively within the 22-day pregnancy. CONCLUSIONS/SIGNIFICANCE: Our results demonstrate that maternal feeding entrains the fetal SCN and liver independently of both the maternal SCN and the LD cycle. This indicates that maternal-feeding signals can be more influential for the fetal SCN and particular organ oscillators than hormonal signals controlled by the maternal SCN, suggesting the importance of a regular maternal feeding schedule for appropriate fetal molecular clockwork during pregnancy.

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.

Biological control of Meloidogyne incognita by Trichoderma ...

African Journals Online (AJOL)

Biological control against the root-knot nematode, Meloidogyne incognita was proven to occur in tomato, Solanum lycopersicom, soil-drenched with different isolates of Trichoderma harzianum and a commercial suspension of Serratia marcescens (Nemaless). The potential of such biocontrol agents to trigger plant defense ...

The use of biologically based cancer risk models in radiation epidemiology

International Nuclear Information System (INIS)

Krewski, D.; Zielinski, J.M.; Hazelton, W.D.; Garner, M.J.; Moolgavkar, S.H.

2003-01-01

Biologically based risk projection models for radiation carcinogenesis seek to describe the fundamental biological processes involved in neoplastic transformation of somatic cells into malignant cancer cells. A validated biologically based model, whose parameters have a direct biological interpretation, can also be used to extrapolate cancer risks to different exposure conditions with some confidence. In this article, biologically based models for radiation carcinogenesis, including the two-stage clonal expansion (TSCE) model and its extensions, are reviewed. The biological and mathematical bases for such models are described, and the implications of key model parameters for cancer risk assessment examined. Specific applications of versions of the TSCE model to important epidemiologic datasets are discussed, including the Colorado uranium miners' cohort; a cohort of Chinese tin miners; the lifespan cohort of atomic bomb survivors in Hiroshima and Nagasaki; and a cohort of over 200,000 workers included in the National Dose Registry (NDR) of Canada. (author)

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...

75 FR 64984 - Availability of an Environmental Assessment for a Biological Control Agent for Hawkweeds

Science.gov (United States)

2010-10-21

... hawkweed gall wasp, Aulacidea subterminalis, into the continental United States as a biological control... United States for the biological control of hawkweeds (Hieracium pilosella, H. aurantiacum, H... control, and the use of biological control organisms. The use of herbicides, while effective, is limited...

BIOLOGICAL CONTROL - AS A MEANS TO CONTROL INSECT PESTS IN AZERBAIJAN

Directory of Open Access Journals (Sweden)

Z. M. Mamedov

2013-01-01

Full Text Available Two hundreds and twenty species parasites and predators of pests of various agricultures are revealed in Azerbaijan. The complex of entomophages of certain pests of agricultures is studied: 48 species of parasites and predators of Chloridea obsoleta 21 species of entomophages of Pectinophora malvella Hb., over 160 species of entomophages of pests of ozehards and vegetables, 34 species of entomophages of pests of forests. The hundreds species of entomophages and some entomophogenous microbes and antagonists are revealed. Biology and ecology of over 60 species of entomophages and useful microorganisims which are prospective as biological control agents are studied.

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.

Do biological-based strategies hold promise to biofouling control in MBRs?

KAUST Repository

Malaeb, Lilian

2013-10-01

Biofouling in membrane bioreactors (MBRs) remains a primary challenge for their wider application, despite the growing acceptance of MBRs worldwide. Research studies on membrane fouling are extensive in the literature, with more than 200 publications on MBR fouling in the last 3 years; yet, improvements in practice on biofouling control and management have been remarkably slow. Commonly applied cleaning methods are only partially effective and membrane replacement often becomes frequent. The reason for the slow advancement in successful control of biofouling is largely attributed to the complex interactions of involved biological compounds and the lack of representative-for-practice experimental approaches to evaluate potential effective control strategies. Biofouling is driven by microorganisms and their associated extra-cellular polymeric substances (EPS) and microbial products. Microorganisms and their products convene together to form matrices that are commonly treated as a black box in conventional control approaches. Biological-based antifouling strategies seem to be a promising constituent of an effective integrated control approach since they target the essence of biofouling problems. However, biological-based strategies are in their developmental phase and several questions should be addressed to set a roadmap for translating existing and new information into sustainable and effective control techniques. This paper investigates membrane biofouling in MBRs from the microbiological perspective to evaluate the potential of biological-based strategies in offering viable control alternatives. Limitations of available control methods highlight the importance of an integrated anti-fouling approach including biological strategies. Successful development of these strategies requires detailed characterization of microorganisms and EPS through the proper selection of analytical tools and assembly of results. Existing microbiological/EPS studies reveal a number of

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.

Noise Controlled Synchronization in Potassium Coupled Neural Models

DEFF Research Database (Denmark)

Postnov, D. E.; Ryazanova, L. S.; Zhirin, R. A.

2007-01-01

The paper applies biologically plausible models to investigate how noise input to small ensembles of neurons, coupled via the extracellular potassium concentration, can influence their firing patterns. Using the noise intensity and the volume of the extracellular space as control parameters, we......-temporal oscillations in neuronal ensembles....

Function of dynamic models in systems biology: linking structure to behaviour.

Science.gov (United States)

Knüpfer, Christian; Beckstein, Clemens

2013-10-08

Dynamic models in Systems Biology are used in computational simulation experiments for addressing biological questions. The complexity of the modelled biological systems and the growing number and size of the models calls for computer support for modelling and simulation in Systems Biology. This computer support has to be based on formal representations of relevant knowledge fragments. In this paper we describe different functional aspects of dynamic models. This description is conceptually embedded in our "meaning facets" framework which systematises the interpretation of dynamic models in structural, functional and behavioural facets. Here we focus on how function links the structure and the behaviour of a model. Models play a specific role (teleological function) in the scientific process of finding explanations for dynamic phenomena. In order to fulfil this role a model has to be used in simulation experiments (pragmatical function). A simulation experiment always refers to a specific situation and a state of the model and the modelled system (conditional function). We claim that the function of dynamic models refers to both the simulation experiment executed by software (intrinsic function) and the biological experiment which produces the phenomena under investigation (extrinsic function). We use the presented conceptual framework for the function of dynamic models to review formal accounts for functional aspects of models in Systems Biology, such as checklists, ontologies, and formal languages. Furthermore, we identify missing formal accounts for some of the functional aspects. In order to fill one of these gaps we propose an ontology for the teleological function of models. We have thoroughly analysed the role and use of models in Systems Biology. The resulting conceptual framework for the function of models is an important first step towards a comprehensive formal representation of the functional knowledge involved in the modelling and simulation process

Quality control of X-ray irradiator by biological markers

International Nuclear Information System (INIS)

Miura, Miwa; Lukmanul Hakkim, F.; Yoshida, Masahiro; Matsuda, Naoki; Morita, Naoko

2011-01-01

The exposure of animals or cultured cells to radiation is the essential and common step in experimental researches to elucidate biological effects of radiation. When an X-ray generator is used as a radiation source, physical parameters including dose, dose rate, and the energy spectrum of X-ray play crucial roles in biological outcome. Therefore, those parameters are the important points to be checked in quality control and to be carefully considered in advance to the irradiation to obtain the accurate and reproductive results. Here we measured radiation dose emitted from the X-ray irradiator for research purposes by using clonogenic survival of cultured mammalian cells as a biological marker in parallel with physical dosimetry. The results drawn from both methods exhibited good consistency in the dose distribution on the irradiation stage. Furthermore, the close relationship was observed between cell survival and the photon energy spectrum by using different filter components. These results suggest that biological dosimetry is applicable to quality control of X-ray irradiator in adjunct to physical dosimetry and that it possibly helps better understanding of the optimal irradiating condition by X-ray users in life-science field. (author)

Quantitative computational models of molecular self-assembly in systems biology.

Science.gov (United States)

Thomas, Marcus; Schwartz, Russell

2017-05-23

Molecular self-assembly is the dominant form of chemical reaction in living systems, yet efforts at systems biology modeling are only beginning to appreciate the need for and challenges to accurate quantitative modeling of self-assembly. Self-assembly reactions are essential to nearly every important process in cell and molecular biology and handling them is thus a necessary step in building comprehensive models of complex cellular systems. They present exceptional challenges, however, to standard methods for simulating complex systems. While the general systems biology world is just beginning to deal with these challenges, there is an extensive literature dealing with them for more specialized self-assembly modeling. This review will examine the challenges of self-assembly modeling, nascent efforts to deal with these challenges in the systems modeling community, and some of the solutions offered in prior work on self-assembly specifically. The review concludes with some consideration of the likely role of self-assembly in the future of complex biological system models more generally.

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

Thresholds for HLB vector control in infected commercial citrus and compatibility with biological control

OpenAIRE

Monzo, C.; Hendricks, K.; Roberts, P.; Stansly, P. A.

2014-01-01

Control of the HLB vector, Diaphorina citri Kuwayama, is considered a basic component for management this disease, even in a high HLB incidence scenario. Such control is mostly chemically oriented. However, over use of insecticides would increase costs and be incompatible with biological control. Establishment of economic thresholds for psyllid control under different price scenarios could optimize returns on investment.

Toward computational cumulative biology by combining models of biological datasets.

Science.gov (United States)

Faisal, Ali; Peltonen, Jaakko; Georgii, Elisabeth; Rung, Johan; Kaski, Samuel

2014-01-01

A main challenge of data-driven sciences is how to make maximal use of the progressively expanding databases of experimental datasets in order to keep research cumulative. We introduce the idea of a modeling-based dataset retrieval engine designed for relating a researcher's experimental dataset to earlier work in the field. The search is (i) data-driven to enable new findings, going beyond the state of the art of keyword searches in annotations, (ii) modeling-driven, to include both biological knowledge and insights learned from data, and (iii) scalable, as it is accomplished without building one unified grand model of all data. Assuming each dataset has been modeled beforehand, by the researchers or automatically by database managers, we apply a rapidly computable and optimizable combination model to decompose a new dataset into contributions from earlier relevant models. By using the data-driven decomposition, we identify a network of interrelated datasets from a large annotated human gene expression atlas. While tissue type and disease were major driving forces for determining relevant datasets, the found relationships were richer, and the model-based search was more accurate than the keyword search; moreover, it recovered biologically meaningful relationships that are not straightforwardly visible from annotations-for instance, between cells in different developmental stages such as thymocytes and T-cells. Data-driven links and citations matched to a large extent; the data-driven links even uncovered corrections to the publication data, as two of the most linked datasets were not highly cited and turned out to have wrong publication entries in the database.

Managing conflict over biological control: the case of strawberry guava in Hawaii

Science.gov (United States)

Tracy Johnson

2016-01-01

Biological control researchers commonly avoid targets with potential for high conflict, but for certain highly damaging invaders with no viable management alternatives, it may be necessary to consider biological control even when it is likely to generate conflict. Discussed here is a case study, strawberry guava (Psidium cattleianum Sabine...

Rearing and Release of Megamelus scutellaris Berg (Hemiptera: Delphacidae) for Biological Control of Water hyacinth in 2015

Science.gov (United States)

2017-06-01

Hemiptera: Delphacidae) for Biological Control of Waterhyacinth in 2015 by Jan Freedman and Nathan Harms PURPOSE: Waterhyacinth biological control ... control agents. Three insects were released in the United States for biological control of waterhyacinth during the 1970s; two weevils, Neochetina...content) and competitive interactions with other biological control agents (e.g., Neochetina spp.), though their consideration in other biological

Thermodynamic modeling of transcription: sensitivity analysis differentiates biological mechanism from mathematical model-induced effects.

Science.gov (United States)

Dresch, Jacqueline M; Liu, Xiaozhou; Arnosti, David N; Ay, Ahmet

2010-10-24

Quantitative models of gene expression generate parameter values that can shed light on biological features such as transcription factor activity, cooperativity, and local effects of repressors. An important element in such investigations is sensitivity analysis, which determines how strongly a model's output reacts to variations in parameter values. Parameters of low sensitivity may not be accurately estimated, leading to unwarranted conclusions. Low sensitivity may reflect the nature of the biological data, or it may be a result of the model structure. Here, we focus on the analysis of thermodynamic models, which have been used extensively to analyze gene transcription. Extracted parameter values have been interpreted biologically, but until now little attention has been given to parameter sensitivity in this context. We apply local and global sensitivity analyses to two recent transcriptional models to determine the sensitivity of individual parameters. We show that in one case, values for repressor efficiencies are very sensitive, while values for protein cooperativities are not, and provide insights on why these differential sensitivities stem from both biological effects and the structure of the applied models. In a second case, we demonstrate that parameters that were thought to prove the system's dependence on activator-activator cooperativity are relatively insensitive. We show that there are numerous parameter sets that do not satisfy the relationships proferred as the optimal solutions, indicating that structural differences between the two types of transcriptional enhancers analyzed may not be as simple as altered activator cooperativity. Our results emphasize the need for sensitivity analysis to examine model construction and forms of biological data used for modeling transcriptional processes, in order to determine the significance of estimated parameter values for thermodynamic models. Knowledge of parameter sensitivities can provide the necessary

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

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.

Biological control by ( Coccinella algerica , Kovar 1977) against the ...

African Journals Online (AJOL)

Inputs from chemicals, particularly pesticides, to control crop pests have adverse effects on soil and the environment, among others. To reduce pest attacks, biological control with indigenous predators is the alternative and the cleanest, most environmentally friendly and ecologically balanced way. In order to achieve this ...

Modeling of nonlinear biological phenomena modeled by S-systems.

Science.gov (United States)

Mansouri, Majdi M; Nounou, Hazem N; Nounou, Mohamed N; Datta, Aniruddha A

2014-03-01

A central challenge in computational modeling of biological systems is the determination of the model parameters. In such cases, estimating these variables or parameters from other easily obtained measurements can be extremely useful. For example, time-series dynamic genomic data can be used to develop models representing dynamic genetic regulatory networks, which can be used to design intervention strategies to cure major diseases and to better understand the behavior of biological systems. Unfortunately, biological measurements are usually highly infected by errors that hide the important characteristics in the data. Therefore, these noisy measurements need to be filtered to enhance their usefulness in practice. This paper addresses the problem of state and parameter estimation of biological phenomena modeled by S-systems using Bayesian approaches, where the nonlinear observed system is assumed to progress according to a probabilistic state space model. The performances of various conventional and state-of-the-art state estimation techniques are compared. These techniques include the extended Kalman filter (EKF), unscented Kalman filter (UKF), particle filter (PF), and the developed variational Bayesian filter (VBF). Specifically, two comparative studies are performed. In the first comparative study, the state variables (the enzyme CadA, the model cadBA, the cadaverine Cadav and the lysine Lys for a model of the Cad System in Escherichia coli (CSEC)) are estimated from noisy measurements of these variables, and the various estimation techniques are compared by computing the estimation root mean square error (RMSE) with respect to the noise-free data. In the second comparative study, the state variables as well as the model parameters are simultaneously estimated. In this case, in addition to comparing the performances of the various state estimation techniques, the effect of the number of estimated model parameters on the accuracy and convergence of these

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

Identifying Ant-Mirid Spatial Interactions to Improve Biological Control in Cacao-Based Agroforestry System.

Science.gov (United States)

Bagny Beilhe, Leïla; Piou, Cyril; Tadu, Zéphirin; Babin, Régis

2018-06-06

The use of ants for biological control of insect pests was the first reported case of conservation biological control. Direct and indirect community interactions between ants and pests lead to differential spatial pattern. We investigated spatial interactions between mirids, the major cocoa pest in West Africa and numerically dominant ant species, using bivariate point pattern analysis to identify potential biological control agents. We assume that potential biological control agents should display negative spatial interactions with mirids considering their niche overlap. The mirid/ant data were collected in complex cacao-based agroforestry systems sampled in three agroecological areas over a forest-savannah gradient in Cameroon. Three species, Crematogaster striatula Emery (Hymenoptera: Formicidae), Crematogaster clariventris Mayr (Hymenoptera: Formicidae), and Oecophylla longinoda Latreille (Hymenoptera: Formicidae) with high predator and aggressive behaviors were identified as dominant and showed negative spatial relationships with mirids. The weaver ant, O. longinoda was identified as the only potential biological control agent, considering its ubiquity in the plots, the similarity in niche requirements, and the spatial segregation with mirids resulting probably from exclusion mechanisms. Combining bivariate point pattern analysis to good knowledge of insect ecology was an effective method to identify a potentially good biological control agent.

Generative models versus underlying symmetries to explain biological pattern.

Science.gov (United States)

Frank, S A

2014-06-01

Mathematical models play an increasingly important role in the interpretation of biological experiments. Studies often present a model that generates the observations, connecting hypothesized process to an observed pattern. Such generative models confirm the plausibility of an explanation and make testable hypotheses for further experiments. However, studies rarely consider the broad family of alternative models that match the same observed pattern. The symmetries that define the broad class of matching models are in fact the only aspects of information truly revealed by observed pattern. Commonly observed patterns derive from simple underlying symmetries. This article illustrates the problem by showing the symmetry associated with the observed rate of increase in fitness in a constant environment. That underlying symmetry reveals how each particular generative model defines a single example within the broad class of matching models. Further progress on the relation between pattern and process requires deeper consideration of the underlying symmetries. © 2014 The Author. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

1H NMR-based metabolic profiling reveals inherent biological variation in yeast and nematode model systems

International Nuclear Information System (INIS)

Szeto, Samuel S. W.; Reinke, Stacey N.; Lemire, Bernard D.

2011-01-01

The application of metabolomics to human and animal model systems is poised to provide great insight into our understanding of disease etiology and the metabolic changes that are associated with these conditions. However, metabolomic studies have also revealed that there is significant, inherent biological variation in human samples and even in samples from animal model systems where the animals are housed under carefully controlled conditions. This inherent biological variability is an important consideration for all metabolomics analyses. In this study, we examined the biological variation in 1 H NMR-based metabolic profiling of two model systems, the yeast Saccharomyces cerevisiae and the nematode Caenorhabditis elegans. Using relative standard deviations (RSD) as a measure of variability, our results reveal that both model systems have significant amounts of biological variation. The C. elegans metabolome possesses greater metabolic variance with average RSD values of 29 and 39%, depending on the food source that was used. The S. cerevisiae exometabolome RSD values ranged from 8% to 12% for the four strains examined. We also determined whether biological variation occurs between pairs of phenotypically identical yeast strains. Multivariate statistical analysis allowed us to discriminate between pair members based on their metabolic phenotypes. Our results highlight the variability of the metabolome that exists even for less complex model systems cultured under defined conditions. We also highlight the efficacy of metabolic profiling for defining these subtle metabolic alterations.

Biologic Constraints on Modelling Virus Assembly

Directory of Open Access Journals (Sweden)

Robert L. Garcea

2008-01-01

Full Text Available The mathematic modelling of icosahedral virus assembly has drawn increasing interest because of the symmetric geometry of the outer shell structures. Many models involve equilibrium expressions of subunit binding, with reversible subunit additions forming various intermediate structures. The underlying assumption is that a final lowest energy state drives the equilibrium toward assembly. In their simplest forms, these models have explained why high subunit protein concentrations and strong subunit association constants can result in kinetic traps forming off pathway partial and aberrant structures. However, the cell biology of virus assembly is exceedingly complex. The biochemistry and biology of polyoma and papillomavirus assembly described here illustrates many of these specific issues. Variables include the use of cellular ‘chaperone’ proteins as mediators of assembly fidelity, the coupling of assembly to encapsidation of a specific nucleic acid genome, the use of cellular structures as ‘workbenches’ upon which assembly occurs, and the underlying problem of making a capsid structure that is metastable and capable of rapid disassembly upon infection. Although formidable to model, incorporating these considerations could advance the relevance of mathematical models of virus assembly to the real world.

cellPACK: a virtual mesoscope to model and visualize structural systems biology.

Science.gov (United States)

Johnson, Graham T; Autin, Ludovic; Al-Alusi, Mostafa; Goodsell, David S; Sanner, Michel F; Olson, Arthur J

2015-01-01

cellPACK assembles computational models of the biological mesoscale, an intermediate scale (10-100 nm) between molecular and cellular biology scales. cellPACK's modular architecture unites existing and novel packing algorithms to generate, visualize and analyze comprehensive three-dimensional models of complex biological environments that integrate data from multiple experimental systems biology and structural biology sources. cellPACK is available as open-source code, with tools for validation of models and with 'recipes' and models for five biological systems: blood plasma, cytoplasm, synaptic vesicles, HIV and a mycoplasma cell. We have applied cellPACK to model distributions of HIV envelope protein to test several hypotheses for consistency with experimental observations. Biologists, educators and outreach specialists can interact with cellPACK models, develop new recipes and perform packing experiments through scripting and graphical user interfaces at http://cellPACK.org/.

Biological control of tortricids and aphids in strawberries

DEFF Research Database (Denmark)

Sigsgaard, Lene; Enkegaard, Annie; Eilenberg, Jørgen

Cropping practice and biological control can contribute to reduced pesticide use in strawberries. Organic strawberries are less attacked by strawberry tortricid and buckwheat flower strips can augment its natural enemies. Against shallot aphid the two-spot ladybird is promising....

Model fit versus biological relevance: Evaluating photosynthesis-temperature models for three tropical seagrass species

OpenAIRE

Matthew P. Adams; Catherine J. Collier; Sven Uthicke; Yan X. Ow; Lucas Langlois; Katherine R. O’Brien

2017-01-01

When several models can describe a biological process, the equation that best fits the data is typically considered the best. However, models are most useful when they also possess biologically-meaningful parameters. In particular, model parameters should be stable, physically interpretable, and transferable to other contexts, e.g. for direct indication of system state, or usage in other model types. As an example of implementing these recommended requirements for model parameters, we evaluat...

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.

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.

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

Biological control and invading freshwater snails. A case study.

Science.gov (United States)

Pointier, J P; Augustin, D

1999-12-01

Introductions of four species of freshwater snails occurred between 1972 and 1996 onto Guadeloupe Island. Two of them, Melanoides tuberculata and Marisa cornuarietis, were subsequently used as biological control agents against Biomphalaria glabrata, the snail intermediate host of intestinal schistosomiasis. In 1996, a general survey was carried out in 134 sites which had already been investigated in 1972. The total number of mollusc species had increased from 19 to 21. Site numbers housing B. glabrata and two other species had strongly declined. This decline may be mainly attributed to a competitive displacement by M. tuberculata and M. cornuarietis as illustrated by several biological control programmes. There were no changes in the remainder of the malacological fauna.

Model fit versus biological relevance: Evaluating photosynthesis-temperature models for three tropical seagrass species.

Science.gov (United States)

Adams, Matthew P; Collier, Catherine J; Uthicke, Sven; Ow, Yan X; Langlois, Lucas; O'Brien, Katherine R

2017-01-04

When several models can describe a biological process, the equation that best fits the data is typically considered the best. However, models are most useful when they also possess biologically-meaningful parameters. In particular, model parameters should be stable, physically interpretable, and transferable to other contexts, e.g. for direct indication of system state, or usage in other model types. As an example of implementing these recommended requirements for model parameters, we evaluated twelve published empirical models for temperature-dependent tropical seagrass photosynthesis, based on two criteria: (1) goodness of fit, and (2) how easily biologically-meaningful parameters can be obtained. All models were formulated in terms of parameters characterising the thermal optimum (T opt ) for maximum photosynthetic rate (P max ). These parameters indicate the upper thermal limits of seagrass photosynthetic capacity, and hence can be used to assess the vulnerability of seagrass to temperature change. Our study exemplifies an approach to model selection which optimises the usefulness of empirical models for both modellers and ecologists alike.

Model fit versus biological relevance: Evaluating photosynthesis-temperature models for three tropical seagrass species

Science.gov (United States)

Adams, Matthew P.; Collier, Catherine J.; Uthicke, Sven; Ow, Yan X.; Langlois, Lucas; O'Brien, Katherine R.

2017-01-01

When several models can describe a biological process, the equation that best fits the data is typically considered the best. However, models are most useful when they also possess biologically-meaningful parameters. In particular, model parameters should be stable, physically interpretable, and transferable to other contexts, e.g. for direct indication of system state, or usage in other model types. As an example of implementing these recommended requirements for model parameters, we evaluated twelve published empirical models for temperature-dependent tropical seagrass photosynthesis, based on two criteria: (1) goodness of fit, and (2) how easily biologically-meaningful parameters can be obtained. All models were formulated in terms of parameters characterising the thermal optimum (Topt) for maximum photosynthetic rate (Pmax). These parameters indicate the upper thermal limits of seagrass photosynthetic capacity, and hence can be used to assess the vulnerability of seagrass to temperature change. Our study exemplifies an approach to model selection which optimises the usefulness of empirical models for both modellers and ecologists alike.

Multi-level and hybrid modelling approaches for systems biology.

Science.gov (United States)

Bardini, R; Politano, G; Benso, A; Di Carlo, S

2017-01-01

During the last decades, high-throughput techniques allowed for the extraction of a huge amount of data from biological systems, unveiling more of their underling complexity. Biological systems encompass a wide range of space and time scales, functioning according to flexible hierarchies of mechanisms making an intertwined and dynamic interplay of regulations. This becomes particularly evident in processes such as ontogenesis, where regulative assets change according to process context and timing, making structural phenotype and architectural complexities emerge from a single cell, through local interactions. The information collected from biological systems are naturally organized according to the functional levels composing the system itself. In systems biology, biological information often comes from overlapping but different scientific domains, each one having its own way of representing phenomena under study. That is, the different parts of the system to be modelled may be described with different formalisms. For a model to have improved accuracy and capability for making a good knowledge base, it is good to comprise different system levels, suitably handling the relative formalisms. Models which are both multi-level and hybrid satisfy both these requirements, making a very useful tool in computational systems biology. This paper reviews some of the main contributions in this field.

Using consumption rate to assess potential predators for biological control of white perch

Directory of Open Access Journals (Sweden)

Gosch N.J.C.

2011-08-01

Full Text Available Control of undesirable fishes is important in aquatic systems, and using predation as a tool for biological control is an attractive option to fishery biologists. However, determining the appropriate predators for biological control is critical for success. The objective of this study was to evaluate the utility of consumption rate as an index to determine the most effective predators for biological control of an invasive fish. Consumption rate values were calculated for nine potential predators that prey on white perch Morone americana in Branched Oak and Pawnee reservoirs, Nebraska. The consumption rate index provided a unique and insightful means of determining the potential effectiveness of each predator species in controlling white perch. Cumulative frequency distributions facilitated interpretation by providing a graphical presentation of consumption rates by all individuals within each predator species. Largemouth bass Micropterus salmoides, walleye Sander vitreus and sauger S. canadensis were the most efficient white perch predators in both reservoirs; however, previous attempts to increase biomass of these predators have failed suggesting that successful biological control is unlikely using existing predator species in these Nebraska reservoirs.

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.

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.

Towards building hybrid biological/in silico neural networks for motor neuroprosthetic control

Directory of Open Access Journals (Sweden)

Mehmet eKocaturk

2015-08-01

Full Text Available In this article, we introduce the Bioinspired Neuroprosthetic Design Environment (BNDE as a practical platform for the development of novel brain machine interface (BMI controllers which are based on spiking model neurons. We built the BNDE around a hard real-time system so that it is capable of creating simulated synapses from extracellularly recorded neurons to model neurons. In order to evaluate the practicality of the BNDE for neuroprosthetic control experiments, a novel, adaptive BMI controller was developed and tested using real-time closed-loop simulations. The present controller consists of two in silico medium spiny neurons which receive simulated synaptic inputs from recorded motor cortical neurons. In the closed-loop simulations, the recordings from the cortical neurons were imitated using an external, hardware-based neural signal synthesizer. By implementing a reward-modulated spike timing-dependent plasticity rule, the controller achieved perfect target reach accuracy for a two target reaching task in one dimensional space. The BNDE combines the flexibility of software-based spiking neural network (SNN simulations with powerful online data visualization tools and is a low-cost, PC-based and all-in-one solution for developing neurally-inspired BMI controllers. We believe the BNDE is the first implementation which is capable of creating hybrid biological/in silico neural networks for motor neuroprosthetic control and utilizes multiple CPU cores for computationally intensive real-time SNN simulations.

The status of biological control and recommendations for improving uptake for the future

NARCIS (Netherlands)

Barratt, B.I.P.; Moran, V.C.; Bigler, F.; Lenteren, van J.C.

2018-01-01

Classical and augmentative biological control of insect pests and weeds has enjoyed a long history of successes. However, biocontrol practices have not been as universally accepted or optimally utilised as they could be. An International Organisation for Biological Control (IOBC) initiative brought

Universally sloppy parameter sensitivities in systems biology models.

Directory of Open Access Journals (Sweden)

Ryan N Gutenkunst

2007-10-01

Full Text Available Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a "sloppy" spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our growth-factor-signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters.

Universally sloppy parameter sensitivities in systems biology models.

Science.gov (United States)

Gutenkunst, Ryan N; Waterfall, Joshua J; Casey, Fergal P; Brown, Kevin S; Myers, Christopher R; Sethna, James P

2007-10-01

Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a "sloppy" spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our growth-factor-signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters.

Pythium species and isolate diversity influence inhibition by the biological control agent Streptomyces lydicus

Science.gov (United States)

Disease control of soilborne pathogens by biological control agents has often been inconsistent under field conditions. One factor that may contribute to this inconsistency is the variability in response among pathogen populations and/or communities to the selected biological control agent. One hund...

Boolean modeling in systems biology: an overview of methodology and applications

International Nuclear Information System (INIS)

Wang, Rui-Sheng; Albert, Réka; Saadatpour, Assieh

2012-01-01

Mathematical modeling of biological processes provides deep insights into complex cellular systems. While quantitative and continuous models such as differential equations have been widely used, their use is obstructed in systems wherein the knowledge of mechanistic details and kinetic parameters is scarce. On the other hand, a wealth of molecular level qualitative data on individual components and interactions can be obtained from the experimental literature and high-throughput technologies, making qualitative approaches such as Boolean network modeling extremely useful. In this paper, we build on our research to provide a methodology overview of Boolean modeling in systems biology, including Boolean dynamic modeling of cellular networks, attractor analysis of Boolean dynamic models, as well as inferring biological regulatory mechanisms from high-throughput data using Boolean models. We finally demonstrate how Boolean models can be applied to perform the structural analysis of cellular networks. This overview aims to acquaint life science researchers with the basic steps of Boolean modeling and its applications in several areas of systems biology. (paper)

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

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.

Biopesticides: An option for the biological pest control

Directory of Open Access Journals (Sweden)

Eusebio Nava Pérez

2012-09-01

Full Text Available The indiscriminate use of synthetic pesticides and the problems that its cause to human health, agriculture and the environment is comment, this paper also present general aspects about of biopesticides, and their uses in the biological pest control. By the nature these can be safely used in a sustainable agriculture. An example is the use of botanical pesticides whose active ingredient are the terpenes, alkaloids and phenolics, these have insecticide effects for many agriculture pests; also its are less expensive, are biodegradable and safe for humans and the environment, however havelittle residuality. Microbial pesticides are being introduced successfully to pests control in important crops such as; coffee, sugar cane, beans and corn. These products contain bacteria, fungi, viruses or nematodes. However, few entomopathogenic agents have been developed as effective biocontrol agents, one of them is the bacterium Bacillus thuringiensis (Berlinier for control of armyworm Spodoptera frugiperda (J.E Smith covering about 74% of the market,fungus 10% , viruses 5% and 11% others. Other upstanding case is the use of the fungus Beauveria bassiana (Balsamoagainst bean weevil Acanthoscelides obtectus (Say. Biopesticides have shown that when are used properly in the biological pest control its favor the practice of a sustainable agriculture, with less dependence of chemical insecticides.

Potential for widespread application of biological control of stored-product pests

DEFF Research Database (Denmark)

Hansen, Lise Stengaard

2007-01-01

Biological control of stored product pests has substantial potential in Europe". This is essentially the conclusion of the activities of a European working group funded by the COST system, an intergovernmental networking system. Working group 4 of COST action 842 (2000-2005) focussed on biologica...... for these situations will contribute to ensuring that stored food products are protected from insect and mite pests using techniques that are safe for consumers, workers and the environment.......Biological control of stored product pests has substantial potential in Europe". This is essentially the conclusion of the activities of a European working group funded by the COST system, an intergovernmental networking system. Working group 4 of COST action 842 (2000-2005) focussed on biological...

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

Polynomial algebra of discrete models in systems biology.

Science.gov (United States)

Veliz-Cuba, Alan; Jarrah, Abdul Salam; Laubenbacher, Reinhard

2010-07-01

An increasing number of discrete mathematical models are being published in Systems Biology, ranging from Boolean network models to logical models and Petri nets. They are used to model a variety of biochemical networks, such as metabolic networks, gene regulatory networks and signal transduction networks. There is increasing evidence that such models can capture key dynamic features of biological networks and can be used successfully for hypothesis generation. This article provides a unified framework that can aid the mathematical analysis of Boolean network models, logical models and Petri nets. They can be represented as polynomial dynamical systems, which allows the use of a variety of mathematical tools from computer algebra for their analysis. Algorithms are presented for the translation into polynomial dynamical systems. Examples are given of how polynomial algebra can be used for the model analysis. alanavc@vt.edu Supplementary data are available at Bioinformatics online.

Mathematical modeling in biology: A critical assessment

Energy Technology Data Exchange (ETDEWEB)

Buiatti, M. [Florence, Univ. (Italy). Dipt. di Biologia Animale e Genetica

1998-01-01

The molecular revolution and the development of biology-derived industry have led in the last fifty years to an unprecedented `lead forward` of life sciences in terms of experimental data. Less success has been achieved in the organisation of such data and in the consequent development of adequate explanatory and predictive theories and models. After a brief historical excursus inborn difficulties of mathematisation of biological objects and processes derived from the complex dynamics of life are discussed along with the logical tools (simplifications, choice of observation points etc.) used to overcome them. `Autistic`, monodisciplinary attitudes towards biological modeling of mathematicians, physicists, biologists aimed in each case at the use of the tools of other disciplines to solve `selfish` problems are also taken into account and a warning against derived dangers (reification of mono disciplinary metaphors, lack of falsification etc.) is given. Finally `top.down` (deductive) and `bottom up` (inductive) heuristic interactive approaches to mathematisation are critically discussed with the help of serie of examples.

Mathematical modeling in biology: A critical assessment

International Nuclear Information System (INIS)

Buiatti, M.

1998-01-01

The molecular revolution and the development of biology-derived industry have led in the last fifty years to an unprecedented 'lead forward' of life sciences in terms of experimental data. Less success has been achieved in the organisation of such data and in the consequent development of adequate explanatory and predictive theories and models. After a brief historical excursus inborn difficulties of mathematisation of biological objects and processes derived from the complex dynamics of life are discussed along with the logical tools (simplifications, choice of observation points etc.) used to overcome them. 'Autistic', monodisciplinary attitudes towards biological modeling of mathematicians, physicists, biologists aimed in each case at the use of the tools of other disciplines to solve 'selfish' problems are also taken into account and a warning against derived dangers (reification of mono disciplinary metaphors, lack of falsification etc.) is given. Finally 'top.down' (deductive) and 'bottom up' (inductive) heuristic interactive approaches to mathematisation are critically discussed with the help of serie of examples

Effect of a care plan based on Roy adaptation model biological dimension on stroke patients' physiologic adaptation level.

Science.gov (United States)

Alimohammadi, Nasrollah; Maleki, Bibi; Shahriari, Mohsen; Chitsaz, Ahmad

2015-01-01

Stroke is a stressful event with several functional, physical, psychological, social, and economic problems that affect individuals' different living balances. With coping strategies, patients try to control these problems and return to their natural life. The aim of this study is to investigate the effect of a care plan based on Roy adaptation model biological dimension on stroke patients' physiologic adaptation level. This study is a clinical trial in which 50 patients, affected by brain stroke and being admitted in the neurology ward of Kashani and Alzahra hospitals, were randomly assigned to control and study groups in Isfahan in 2013. Roy adaptation model care plan was administered in biological dimension in the form of four sessions and phone call follow-ups for 1 month. The forms related to Roy adaptation model were completed before and after intervention in the two groups. Chi-square test and t-test were used to analyze the data through SPSS 18. There was a significant difference in mean score of adaptation in physiological dimension in the study group after intervention (P adaptation in the patients affected by brain stroke in the study and control groups showed a significant increase in physiological dimension in the study group by 47.30 after intervention (P adaptation model biological dimension care plan can result in an increase in adaptation in patients with stroke in physiological dimension. Nurses can use this model for increasing patients' adaptation.

Natural biological control of pest mites in Brazilian sun coffee agroecosystems.

Science.gov (United States)

Teodoro, Adenir V; Sarmento, Renato A; Rêgo, Adriano S; da Graça S Maciel, Anilde

2010-06-01

Coffee is one of the leading commodities in tropical America. Although plantations are usually established under a canopy of trees in most producing countries in the region, Brazilian coffee is mostly produced under full sun conditions. Such simple, single-crop agroecosystems with intensive agrochemical inputs often suffer with pests like mites. Predatory mites of the family Phytoseiidae are the main natural enemies associated with pest mites in the field. However, these beneficial arthropods struggle to survive in intensive agroecosystems such as coffee monocultures due to unfavorable microclimatic conditions, widespread pesticide use, and lack of alternative food (pollen, nectar). Conservation biological control uses a range of management strategies to sustain and enhance populations of indigenous natural enemies such as predatory mites. We discuss here conservation biological control as a strategy to improve biological control of pest mites by native predatory mites in Brazilian coffee monocultures as well as some related patents.

Multiscale modeling of emergent materials: biological and soft matter

DEFF Research Database (Denmark)

Murtola, Teemu; Bunker, Alex; Vattulainen, Ilpo

2009-01-01

In this review, we focus on four current related issues in multiscale modeling of soft and biological matter. First, we discuss how to use structural information from detailed models (or experiments) to construct coarse-grained ones in a hierarchical and systematic way. This is discussed in the c......In this review, we focus on four current related issues in multiscale modeling of soft and biological matter. First, we discuss how to use structural information from detailed models (or experiments) to construct coarse-grained ones in a hierarchical and systematic way. This is discussed...

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

A Model of Controlled Growth

Science.gov (United States)

Bressan, Alberto; Lewicka, Marta

2018-03-01

We consider a free boundary problem for a system of PDEs, modeling the growth of a biological tissue. A morphogen, controlling volume growth, is produced by specific cells and then diffused and absorbed throughout the domain. The geometric shape of the growing tissue is determined by the instantaneous minimization of an elastic deformation energy, subject to a constraint on the volumetric growth. For an initial domain with C}^{2,α boundary, our main result establishes the local existence and uniqueness of a classical solution, up to a rigid motion.

Multiway modeling and analysis in stem cell systems biology

Directory of Open Access Journals (Sweden)

Vandenberg Scott L

2008-07-01

Full Text Available Abstract Background Systems biology refers to multidisciplinary approaches designed to uncover emergent properties of biological systems. Stem cells are an attractive target for this analysis, due to their broad therapeutic potential. A central theme of systems biology is the use of computational modeling to reconstruct complex systems from a wealth of reductionist, molecular data (e.g., gene/protein expression, signal transduction activity, metabolic activity, etc.. A number of deterministic, probabilistic, and statistical learning models are used to understand sophisticated cellular behaviors such as protein expression during cellular differentiation and the activity of signaling networks. However, many of these models are bimodal i.e., they only consider row-column relationships. In contrast, multiway modeling techniques (also known as tensor models can analyze multimodal data, which capture much more information about complex behaviors such as cell differentiation. In particular, tensors can be very powerful tools for modeling the dynamic activity of biological networks over time. Here, we review the application of systems biology to stem cells and illustrate application of tensor analysis to model collagen-induced osteogenic differentiation of human mesenchymal stem cells. Results We applied Tucker1, Tucker3, and Parallel Factor Analysis (PARAFAC models to identify protein/gene expression patterns during extracellular matrix-induced osteogenic differentiation of human mesenchymal stem cells. In one case, we organized our data into a tensor of type protein/gene locus link × gene ontology category × osteogenic stimulant, and found that our cells expressed two distinct, stimulus-dependent sets of functionally related genes as they underwent osteogenic differentiation. In a second case, we organized DNA microarray data in a three-way tensor of gene IDs × osteogenic stimulus × replicates, and found that application of tensile strain to a

Classical Biological Control of Invasive Legacy Crop Pests: New Technologies Offer Opportunities to Revisit Old Pest Problems in Perennial Tree Crops

Directory of Open Access Journals (Sweden)

Mark S. Hoddle

2014-12-01

Full Text Available Advances in scientific disciplines that support classical biological control have provided “new tools” that could have important applications for biocontrol programs for some long-established invasive arthropod pests. We suggest that these previously unavailable tools should be used in biological control programs targeting “legacy pests”, even if they have been targets of previously unsuccessful biocontrol projects. Examples of “new tools” include molecular analyses to verify species identities and likely geographic area of origin, climate matching and ecological niche modeling, preservation of natural enemy genetic diversity in quarantine, the use of theory from invasion biology to maximize establishment likelihoods for natural enemies, and improved understanding of the interactions between natural enemy and target pest microbiomes. This review suggests that opportunities exist for revisiting old pest problems and funding research programs using “new tools” for developing biological control programs for “legacy pests” could provide permanent suppression of some seemingly intractable pest problems. As a case study, we use citricola scale, Coccus pseudomagnoliarum, an invasive legacy pest of California citrus, to demonstrate the potential of new tools to support a new classical biological control program targeting this insect.

WE-DE-202-03: Modeling of Biological Processes - What Happens After Early Molecular Damage?

International Nuclear Information System (INIS)

McMahon, S.

2016-01-01

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are the most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological

WE-DE-202-03: Modeling of Biological Processes - What Happens After Early Molecular Damage?

Energy Technology Data Exchange (ETDEWEB)

McMahon, S. [Massachusetts General Hospital and Harvard Medical School (United States)

2016-06-15

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are the most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological

Benchmarking Measures of Network Controllability on Canonical Graph Models

Science.gov (United States)

Wu-Yan, Elena; Betzel, Richard F.; Tang, Evelyn; Gu, Shi; Pasqualetti, Fabio; Bassett, Danielle S.

2018-03-01

The control of networked dynamical systems opens the possibility for new discoveries and therapies in systems biology and neuroscience. Recent theoretical advances provide candidate mechanisms by which a system can be driven from one pre-specified state to another, and computational approaches provide tools to test those mechanisms in real-world systems. Despite already having been applied to study network systems in biology and neuroscience, the practical performance of these tools and associated measures on simple networks with pre-specified structure has yet to be assessed. Here, we study the behavior of four control metrics (global, average, modal, and boundary controllability) on eight canonical graphs (including Erdős-Rényi, regular, small-world, random geometric, Barábasi-Albert preferential attachment, and several modular networks) with different edge weighting schemes (Gaussian, power-law, and two nonparametric distributions from brain networks, as examples of real-world systems). We observe that differences in global controllability across graph models are more salient when edge weight distributions are heavy-tailed as opposed to normal. In contrast, differences in average, modal, and boundary controllability across graph models (as well as across nodes in the graph) are more salient when edge weight distributions are less heavy-tailed. Across graph models and edge weighting schemes, average and modal controllability are negatively correlated with one another across nodes; yet, across graph instances, the relation between average and modal controllability can be positive, negative, or nonsignificant. Collectively, these findings demonstrate that controllability statistics (and their relations) differ across graphs with different topologies and that these differences can be muted or accentuated by differences in the edge weight distributions. More generally, our numerical studies motivate future analytical efforts to better understand the mathematical

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 appearance...

Onchocerciasis control: biological research is still needed

Directory of Open Access Journals (Sweden)

Boussinesq M.

2008-09-01

Full Text Available Achievements obtained by the onchocerciasis control programmes should not lead to a relaxation in the biological research on Onchocerca volvulus. Issues such as the Loa loa-related postivermectin serious adverse events, the uncertainties as to whether onchocerciasis can be eliminated by ivermectin treatments, and the possible emergence of ivermectin-resistant O. volvulus populations should be addressed proactively. Doxycycline, moxidectin and emodepside appear to be promising as alternative drugs against onchocerciasis but support to researches in immunology and genomics should also be increased to develop new control tools, including both vaccines and macrofilaricidal drugs.

Automatic parameter estimation of multicompartmental neuron models via minimization of trace error with control adjustment.

Science.gov (United States)

Brookings, Ted; Goeritz, Marie L; Marder, Eve

2014-11-01

We describe a new technique to fit conductance-based neuron models to intracellular voltage traces from isolated biological neurons. The biological neurons are recorded in current-clamp with pink (1/f) noise injected to perturb the activity of the neuron. The new algorithm finds a set of parameters that allows a multicompartmental model neuron to match the recorded voltage trace. Attempting to match a recorded voltage trace directly has a well-known problem: mismatch in the timing of action potentials between biological and model neuron is inevitable and results in poor phenomenological match between the model and data. Our approach avoids this by applying a weak control adjustment to the model to promote alignment during the fitting procedure. This approach is closely related to the control theoretic concept of a Luenberger observer. We tested this approach on synthetic data and on data recorded from an anterior gastric receptor neuron from the stomatogastric ganglion of the crab Cancer borealis. To test the flexibility of this approach, the synthetic data were constructed with conductance models that were different from the ones used in the fitting model. For both synthetic and biological data, the resultant models had good spike-timing accuracy. Copyright © 2014 the American Physiological Society.

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.

Biology and life history of Argopistes tsekooni (Coleoptera: Chrysomelidae) in China, a promising biological control agent of Chinese privet.

Science.gov (United States)

Y-Z Zhang; J. Sun; J.L. Hanula

2009-01-01

The biology and life history of Argopistes tsekooni Chen (Coleoptera: Chrysomelidae), a potential biological control agent of Chinese privet, Ligustrum sinense Lour., was studied under laboratory and outdoor conditions in Huangshan City of Anhui Province, China, in 2006. A. tsekooni larvae are leafminers that...

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.

Enhancing biological control of basal stem rot disease (Ganoderma boninense) in oil palm plantations.

Science.gov (United States)

Susanto, A; Sudharto, P S; Purba, R Y

2005-01-01

Basal Stem Rot (BSR) disease caused by Ganoderma boninense is the most destructive disease in oil palm, especially in Indonesia and Malaysia. The available control measures for BSR disease such as cultural practices and mechanical and chemical treatment have not proved satisfactory due to the fact that Ganoderma has various resting stages such as melanised mycelium, basidiospores and pseudosclerotia. Alternative control measures to overcome the Ganoderma problem are focused on the use of biological control agents and planting resistant material. Present studies conducted at Indonesian Oil Palm Research Institute (IOPRI) are focused on enhancing the use of biological control agents for Ganoderma. These activities include screening biological agents from the oil palm rhizosphere in order to evaluate their effectiveness as biological agents in glasshouse and field trials, testing their antagonistic activities in large scale experiments and eradicating potential disease inoculum with biological agents. Several promising biological agents have been isolated, mainly Trichoderma harzianum, T. viride, Gliocladium viride, Pseudomonas fluorescens, and Bacillus sp. A glasshouse and field trial for Ganoderma control indicated that treatment with T. harzianum and G. viride was superior to Bacillus sp. A large scale trial showed that the disease incidence was lower in a field treated with biological agents than in untreated fields. In a short term programme, research activities at IOPRI are currently focusing on selecting fungi that can completely degrade plant material in order to eradicate inoculum. Digging holes around the palm bole and adding empty fruit bunches have been investigated as ways to stimulate biological agents.

75 FR 28232 - Availability of an Environmental Assessment for a Biological Control Agent for Hemlock Woolly...

Science.gov (United States)

2010-05-20

...] Availability of an Environmental Assessment for a Biological Control Agent for Hemlock Woolly Adelgid AGENCY..., into the continental United States for use as a biological control agent to reduce the severity of... biological control agent to reduce the severity of hemlock woolly adelgid (HWA) infestations. HWA, an...

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

Science.gov (United States)

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

2012-08-29

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. 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. 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 translated in a set of ordinary differential

Virtual Agonist-antagonist Mechanisms Produce Biological Muscle-like Functions: An Application for Robot Joint Control

DEFF Research Database (Denmark)

Xiong, Xiaofeng; Wörgötter, Florentin; Manoonpong, Poramate

2014-01-01

Purpose – Biological muscles of animals have a surprising variety of functions, i.e., struts, springs, and brakes. According to this, the purpose of this paper is to apply virtual agonist-antagonist mechanisms to robot joint control allowing for muscle-like functions and variably compliant joint......, variably compliant joint motions can be produced without mechanically bulky and complex mechanisms or complex force/toque sensing at each joint. Moreover, through tuning the damping coefficient of the VAAM, the functions of the VAAM are comparable to biological muscles. Originality/value – The model (i.......e., VAAM) provides a way forward to emulate muscle-like functions that are comparable to those found in physiological experiments of biological muscles. Based on these muscle-like functions, the robotic joints can easily achieve variable compliance that does not require complex physical components...

77 FR 46373 - Availability of an Environmental Assessment for a Biological Control Agent for Hemlock Woolly...

Science.gov (United States)

2012-08-03

...] Availability of an Environmental Assessment for a Biological Control Agent for Hemlock Woolly Adelgid AGENCY... States for use as a biological control agent to reduce the severity of hemlock woolly adelgid... beetle from the western United States, into the eastern United States for use as a biological control...

75 FR 69396 - Availability of an Environmental Assessment for a Biological Control Agent for Arundo donax

Science.gov (United States)

2010-11-12

... Biological Control Agent for Arundo donax AGENCY: Animal and Plant Health Inspection Service, USDA. ACTION... alternatives to, the release of Arundo scale into the continental United States for use as a biological control... a biological control agent to reduce the severity of Arundo donax infestations. A. donax is a highly...

Design control considerations for biologic-device combination products.

Science.gov (United States)

Anderson, Dave; Liu, Roger; Anand Subramony, J; Cammack, Jon

2017-03-01

Combination products are therapeutic and diagnostic medical products that combine drugs, devices, and/or biological products with one another. Historically, biologics development involved identifying efficacious doses administered to patients intravenously or perhaps by a syringe. Until fairly recently, there has been limited focus on developing an accompanying medical device, such as a prefilled syringe or auto-injector, to enable easy and more efficient delivery. For the last several years, and looking forward, where there may be little to distinguish biologics medicines with relatively similar efficacy profiles, the biotechnology market is beginning to differentiate products by patient-focused, biologic-device based combination products. As innovative as biologic-device combination products are, they can pose considerable development, regulatory, and commercialization challenges due to unique physicochemical properties and special clinical considerations (e.g., dosing volumes, frequency, co-medications, etc.) of the biologic medicine. A biologic-device combination product is a marriage between two partners with "cultural differences," so to speak. There are clear differences in the development, review, and commercialization processes of the biologic and the device. When these two cultures come together in a combination product, developers and reviewers must find ways to address the design controls and risk management processes of both the biologic and device, and knit them into a single entity with supporting product approval documentation. Moreover, digital medicine and connected health trends are pushing the boundaries of combination product development and regulations even further. Despite an admirable cooperation between industry and FDA in recent years, unique product configurations and design features have resulted in review challenges. These challenges have prompted agency reviewers to modernize consultation processes, while at the same time, promoting

An overview of bioinformatics methods for modeling biological pathways in yeast.

Science.gov (United States)

Hou, Jie; Acharya, Lipi; Zhu, Dongxiao; Cheng, Jianlin

2016-03-01

The advent of high-throughput genomics techniques, along with the completion of genome sequencing projects, identification of protein-protein interactions and reconstruction of genome-scale pathways, has accelerated the development of systems biology research in the yeast organism Saccharomyces cerevisiae In particular, discovery of biological pathways in yeast has become an important forefront in systems biology, which aims to understand the interactions among molecules within a cell leading to certain cellular processes in response to a specific environment. While the existing theoretical and experimental approaches enable the investigation of well-known pathways involved in metabolism, gene regulation and signal transduction, bioinformatics methods offer new insights into computational modeling of biological pathways. A wide range of computational approaches has been proposed in the past for reconstructing biological pathways from high-throughput datasets. Here we review selected bioinformatics approaches for modeling biological pathways inS. cerevisiae, including metabolic pathways, gene-regulatory pathways and signaling pathways. We start with reviewing the research on biological pathways followed by discussing key biological databases. In addition, several representative computational approaches for modeling biological pathways in yeast are discussed. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Estimating confidence intervals in predicted responses for oscillatory biological models.

Science.gov (United States)

St John, Peter C; Doyle, Francis J

2013-07-29

The dynamics of gene regulation play a crucial role in a cellular control: allowing the cell to express the right proteins to meet changing needs. Some needs, such as correctly anticipating the day-night cycle, require complicated oscillatory features. In the analysis of gene regulatory networks, mathematical models are frequently used to understand how a network's structure enables it to respond appropriately to external inputs. These models typically consist of a set of ordinary differential equations, describing a network of biochemical reactions, and unknown kinetic parameters, chosen such that the model best captures experimental data. However, since a model's parameter values are uncertain, and since dynamic responses to inputs are highly parameter-dependent, it is difficult to assess the confidence associated with these in silico predictions. In particular, models with complex dynamics - such as oscillations - must be fit with computationally expensive global optimization routines, and cannot take advantage of existing measures of identifiability. Despite their difficulty to model mathematically, limit cycle oscillations play a key role in many biological processes, including cell cycling, metabolism, neuron firing, and circadian rhythms. In this study, we employ an efficient parameter estimation technique to enable a bootstrap uncertainty analysis for limit cycle models. Since the primary role of systems biology models is the insight they provide on responses to rate perturbations, we extend our uncertainty analysis to include first order sensitivity coefficients. Using a literature model of circadian rhythms, we show how predictive precision is degraded with decreasing sample points and increasing relative error. Additionally, we show how this method can be used for model discrimination by comparing the output identifiability of two candidate model structures to published literature data. Our method permits modellers of oscillatory systems to confidently

Biological control of fusarium wilt of tomato by antagonist fungi and ...

African Journals Online (AJOL)

Yomi

2012-01-16

Jan 16, 2012 ... Key words: Biological control, fusarium wilt, tomato, antagonist fungi, cyanobacteria. INTRODUCTION ... severely affected by wilt disease caused by F. oxysporum f. sp. ..... Changing options for the control of deciduous fruit.

The Strategies of Modeling in Biology Education

Science.gov (United States)

Svoboda, Julia; Passmore, Cynthia

2013-01-01

Modeling, like inquiry more generally, is not a single method, but rather a complex suite of strategies. Philosophers of biology, citing the diverse aims, interests, and disciplinary cultures of biologists, argue that modeling is best understood in the context of its epistemic aims and cognitive payoffs. In the science education literature,…

Epigenetics and Why Biological Networks are More Controllable than Expected

Science.gov (United States)

Motter, Adilson

2013-03-01

A fundamental property of networks is that perturbations to one node can affect other nodes, potentially causing the entire system to change behavior or fail. In this talk, I will show that it is possible to exploit this same principle to control network behavior. This approach takes advantage of the nonlinear dynamics inherent to real networks, and allows bringing the system to a desired target state even when this state is not directly accessible or the linear counterpart is not controllable. Applications show that this framework permits both reprogramming a network to a desired task as well as rescuing networks from the brink of failure, which I will illustrate through various biological problems. I will also briefly review the progress our group has made over the past 5 years on related control of complex networks in non-biological domains.

Asymmetric positive feedback loops reliably control biological responses.

Science.gov (United States)

Ratushny, Alexander V; Saleem, Ramsey A; Sitko, Katherine; Ramsey, Stephen A; Aitchison, John D

2012-04-24

Positive feedback is a common mechanism enabling biological systems to respond to stimuli in a switch-like manner. Such systems are often characterized by the requisite formation of a heterodimer where only one of the pair is subject to feedback. This ASymmetric Self-UpREgulation (ASSURE) motif is central to many biological systems, including cholesterol homeostasis (LXRα/RXRα), adipocyte differentiation (PPARγ/RXRα), development and differentiation (RAR/RXR), myogenesis (MyoD/E12) and cellular antiviral defense (IRF3/IRF7). To understand why this motif is so prevalent, we examined its properties in an evolutionarily conserved transcriptional regulatory network in yeast (Oaf1p/Pip2p). We demonstrate that the asymmetry in positive feedback confers a competitive advantage and allows the system to robustly increase its responsiveness while precisely tuning the response to a consistent level in the presence of varying stimuli. This study reveals evolutionary advantages for the ASSURE motif, and mechanisms for control, that are relevant to pharmacologic intervention and synthetic biology applications.

Commercial Biological Control Agents Targeted Against Plant-Parasitic Root-knot Nematodes

Directory of Open Access Journals (Sweden)

Marie-Stéphane Tranier

2014-12-01

Full Text Available Root-knot nematodes are microscopic round worms, which cause severe agricultural losses. Their attacks affect the productivity by reducing the amount and the caliber of the fruits. Chemical control is widely used, but biological control appears to be a better solution, mainly using microorganisms to reduce the quantity of pests infecting crops. Biological control is developing gradually, and with time, more products are being marketed worldwide. They can be formulated with bacteria, viruses or with filamentous fungi, which can destroy and feed on phytoparasitic nematodes. To be used by the farmers, biopesticides must be legalized by the states, which has led to the establishment of a legal framework for their use, devised by various governmental organizations.

Protein-polymer nano-machines. Towards synthetic control of biological processes

Directory of Open Access Journals (Sweden)

Alexander Cameron

2004-09-01

Full Text Available Abstract The exploitation of nature's machinery at length scales below the dimensions of a cell is an exciting challenge for biologists, chemists and physicists, while advances in our understanding of these biological motifs are now providing an opportunity to develop real single molecule devices for technological applications. Single molecule studies are already well advanced and biological molecular motors are being used to guide the design of nano-scale machines. However, controlling the specific functions of these devices in biological systems under changing conditions is difficult. In this review we describe the principles underlying the development of a molecular motor with numerous potential applications in nanotechnology and the use of specific synthetic polymers as prototypic molecular switches for control of the motor function. The molecular motor is a derivative of a TypeI Restriction-Modification (R-M enzyme and the synthetic polymer is drawn from the class of materials that exhibit a temperature-dependent phase transition. The potential exploitation of single molecules as functional devices has been heralded as the dawn of new era in biotechnology and medicine. It is not surprising, therefore, that the efforts of numerous multidisciplinary teams 12. have been focused in attempts to develop these systems. as machines capable of functioning at the low sub-micron and nanometre length-scales 3. However, one of the obstacles for the practical application of single molecule devices is the lack of functional control methods in biological media, under changing conditions. In this review we describe the conceptual basis for a molecular motor (a derivative of a TypeI Restriction-Modification enzyme with numerous potential applications in nanotechnology and the use of specific synthetic polymers as prototypic molecular switches for controlling the motor function 4.

Ultrafast spectroscopy of model biological membranes

NARCIS (Netherlands)

Ghosh, Avishek

2009-01-01

In this PhD thesis, I have described the novel time-resolved sum-frequency generation (TR-SFG) spectroscopic technique that I developed during the course of my PhD research and used it study the ultrafast vibrational, structural and orientational dynamics of water molecules at model biological

Funding needed for assessments of weed biological control

Science.gov (United States)

John L. Maron; Dean E. Pearson; Stephen M. Hovick; Walter P. Carson

2010-01-01

Invasive non-native plants are a serious economic and ecological problem worldwide, and major efforts are therefore devoted to reducing weed abundance in agricultural and natural settings. Effective options for reducing invasive abundance and spread are few, although one common approach is biological control - the introduction of specialist herbivores or pathogens from...

SEEK: a systems biology data and model management platform.

NARCIS (Netherlands)

Wolstencroft, K.J.; Owen, S.; Krebs, O.; Nguyen, Q.; Stanford, N.J.; Golebiewski, M.; Weidemann, A.; Bittkowski, M.; An, L.; Shockley, D.; Snoep, J.L.; Mueller, W.; Goble, C.

2015-01-01

Background: Systems biology research typically involves the integration and analysis of heterogeneous data types in order to model and predict biological processes. Researchers therefore require tools and resources to facilitate the sharing and integration of data, and for linking of data to systems

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...

{sup 1}H NMR-based metabolic profiling reveals inherent biological variation in yeast and nematode model systems

Energy Technology Data Exchange (ETDEWEB)

Szeto, Samuel S. W.; Reinke, Stacey N.; Lemire, Bernard D., E-mail: bernard.lemire@ualberta.ca [University of Alberta, Department of Biochemistry, School of Molecular and Systems Medicine (Canada)

2011-04-15

The application of metabolomics to human and animal model systems is poised to provide great insight into our understanding of disease etiology and the metabolic changes that are associated with these conditions. However, metabolomic studies have also revealed that there is significant, inherent biological variation in human samples and even in samples from animal model systems where the animals are housed under carefully controlled conditions. This inherent biological variability is an important consideration for all metabolomics analyses. In this study, we examined the biological variation in {sup 1}H NMR-based metabolic profiling of two model systems, the yeast Saccharomyces cerevisiae and the nematode Caenorhabditis elegans. Using relative standard deviations (RSD) as a measure of variability, our results reveal that both model systems have significant amounts of biological variation. The C. elegans metabolome possesses greater metabolic variance with average RSD values of 29 and 39%, depending on the food source that was used. The S. cerevisiae exometabolome RSD values ranged from 8% to 12% for the four strains examined. We also determined whether biological variation occurs between pairs of phenotypically identical yeast strains. Multivariate statistical analysis allowed us to discriminate between pair members based on their metabolic phenotypes. Our results highlight the variability of the metabolome that exists even for less complex model systems cultured under defined conditions. We also highlight the efficacy of metabolic profiling for defining these subtle metabolic alterations.

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…

Structure, function, and behaviour of computational models in systems biology.

Science.gov (United States)

Knüpfer, Christian; Beckstein, Clemens; Dittrich, Peter; Le Novère, Nicolas

2013-05-31

Systems Biology develops computational models in order to understand biological phenomena. The increasing number and complexity of such "bio-models" necessitate computer support for the overall modelling task. Computer-aided modelling has to be based on a formal semantic description of bio-models. But, even if computational bio-models themselves are represented precisely in terms of mathematical expressions their full meaning is not yet formally specified and only described in natural language. We present a conceptual framework - the meaning facets - which can be used to rigorously specify the semantics of bio-models. A bio-model has a dual interpretation: On the one hand it is a mathematical expression which can be used in computational simulations (intrinsic meaning). On the other hand the model is related to the biological reality (extrinsic meaning). We show that in both cases this interpretation should be performed from three perspectives: the meaning of the model's components (structure), the meaning of the model's intended use (function), and the meaning of the model's dynamics (behaviour). In order to demonstrate the strengths of the meaning facets framework we apply it to two semantically related models of the cell cycle. Thereby, we make use of existing approaches for computer representation of bio-models as much as possible and sketch the missing pieces. The meaning facets framework provides a systematic in-depth approach to the semantics of bio-models. It can serve two important purposes: First, it specifies and structures the information which biologists have to take into account if they build, use and exchange models. Secondly, because it can be formalised, the framework is a solid foundation for any sort of computer support in bio-modelling. The proposed conceptual framework establishes a new methodology for modelling in Systems Biology and constitutes a basis for computer-aided collaborative research.

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.

Development of a Value Inquiry Model in Biology Education.

Science.gov (United States)

Jeong, Eun-Young; Kim, Young-Soo

2000-01-01

Points out the rapid advances in biology, increasing bioethical issues, and how students need to make rational decisions. Introduces a value inquiry model development that includes identifying and clarifying value problems; understanding biological knowledge related to conflict situations; considering, selecting, and evaluating each alternative;…

Evolving cell models for systems and synthetic biology.

Science.gov (United States)

Cao, Hongqing; Romero-Campero, Francisco J; Heeb, Stephan; Cámara, Miguel; Krasnogor, Natalio

2010-03-01

This paper proposes a new methodology for the automated design of cell models for systems and synthetic biology. Our modelling framework is based on P systems, a discrete, stochastic and modular formal modelling language. The automated design of biological models comprising the optimization of the model structure and its stochastic kinetic constants is performed using an evolutionary algorithm. The evolutionary algorithm evolves model structures by combining different modules taken from a predefined module library and then it fine-tunes the associated stochastic kinetic constants. We investigate four alternative objective functions for the fitness calculation within the evolutionary algorithm: (1) equally weighted sum method, (2) normalization method, (3) randomly weighted sum method, and (4) equally weighted product method. The effectiveness of the methodology is tested on four case studies of increasing complexity including negative and positive autoregulation as well as two gene networks implementing a pulse generator and a bandwidth detector. We provide a systematic analysis of the evolutionary algorithm's results as well as of the resulting evolved cell models.

75 FR 28233 - Availability of an Environmental Assessment for a Biological Control Agent for Asian Citrus Psyllid

Science.gov (United States)

2010-05-20

...] Availability of an Environmental Assessment for a Biological Control Agent for Asian Citrus Psyllid AGENCY... radiata, into the continental United States for use as a biological control agent to reduce the severity... of an alternative biological control agent, an encyrtid wasp, (Diaphorencyrtus aligarhensis). However...

Maneuvering control and configuration adaptation of a biologically inspired morphing aircraft

Science.gov (United States)

Abdulrahim, Mujahid

Natural flight as a source of inspiration for aircraft design was prominent with early aircraft but became marginalized as aircraft became larger and faster. With recent interest in small unmanned air vehicles, biological inspiration is a possible technology to enhance mission performance of aircraft that are dimensionally similar to gliding birds. Serial wing joints, loosely modeling the avian skeletal structure, are used in the current study to allow significant reconfiguration of the wing shape. The wings are reconfigured to optimize aerodynamic performance and maneuvering metrics related to specific mission tasks. Wing shapes for each mission are determined and related to the seagulls, falcons, albatrosses, and non-migratory African swallows on which the aircraft are based. Variable wing geometry changes the vehicle dynamics, affording versatility in flight behavior but also requiring appropriate compensation to maintain stability and controllability. Time-varying compensation is in the form of a baseline controller which adapts to both the variable vehicle dynamics and to the changing mission requirements. Wing shape is adapted in flight to minimize a cost function which represents energy, temporal, and spatial efficiency. An optimal control architecture unifies the control and adaptation tasks.

How causal analysis can reveal autonomy in models of biological systems

Science.gov (United States)

Marshall, William; Kim, Hyunju; Walker, Sara I.; Tononi, Giulio; Albantakis, Larissa

2017-11-01

Standard techniques for studying biological systems largely focus on their dynamical or, more recently, their informational properties, usually taking either a reductionist or holistic perspective. Yet, studying only individual system elements or the dynamics of the system as a whole disregards the organizational structure of the system-whether there are subsets of elements with joint causes or effects, and whether the system is strongly integrated or composed of several loosely interacting components. Integrated information theory offers a theoretical framework to (1) investigate the compositional cause-effect structure of a system and to (2) identify causal borders of highly integrated elements comprising local maxima of intrinsic cause-effect power. Here we apply this comprehensive causal analysis to a Boolean network model of the fission yeast (Schizosaccharomyces pombe) cell cycle. We demonstrate that this biological model features a non-trivial causal architecture, whose discovery may provide insights about the real cell cycle that could not be gained from holistic or reductionist approaches. We also show how some specific properties of this underlying causal architecture relate to the biological notion of autonomy. Ultimately, we suggest that analysing the causal organization of a system, including key features like intrinsic control and stable causal borders, should prove relevant for distinguishing life from non-life, and thus could also illuminate the origin of life problem. This article is part of the themed issue 'Reconceptualizing the origins of life'.

Biological control of Fusarium moniliforme in maize.

Science.gov (United States)

Bacon, C W; Yates, I E; Hinton, D M; Meredith, F

2001-05-01

Fusarium moniliforme Sheldon, a biological species of the mating populations within the (italic)Gibberella fujikuroi species complex, i.e., population A [= G. moniliformis (Sheld.) Wineland], is an example of a facultative fungal endophyte. During the biotrophic endophytic association with maize, as well as during saprophytic growth, F. moniliforme produces the fumonisins. The fungus is transmitted vertically and horizontally to the next generation of plants via clonal infection of seeds and plant debris. Horizontal infection is the manner by which this fungus is spread contagiously and through which infection occurs from the outside that can be reduced by application of certain fungicides. The endophytic phase is vertically transmitted. This type infection is important because it is not controlled by seed applications of fungicides, and it remains the reservoir from which infection and toxin biosynthesis takes place in each generation of plants. Thus, vertical transmission of this fungus is just as important as horizontal transmission. A biological control system using an endophytic bacterium, Bacillus subtilis, has been developed that shows great promise for reducing mycotoxin accumulation during the endophytic (vertical transmission) growth phase. Because this bacterium occupies the identical ecological niche within the plant, it is considered an ecological homologue to F. moniliforme, and the inhibitory mechanism, regardless of the mode of action, operates on the competitive exclusion principle. In addition to this bacterium, an isolate of a species of the fungus Trichoderma shows promise in the postharvest control of the growth and toxin accumulation from F. moniliforme on corn in storage.

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.

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...

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

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.

Compatible biological and chemical control systems for Rhizoctonia solani in potato

NARCIS (Netherlands)

Boogert, van den P.H.J.F.; Luttikholt, A.J.G.

2004-01-01

A series of chemical and biological control agents were tested for compatibility with the Rhizoctonia-specific biocontrol fungus Verticillium biguttatum aimed at designing novel control strategies for black scurf (Rhizoctonia solani) and other tuber diseases in potato. The efficacy of chemicals,

Biological control in agro-systems by means of the handling of entomophagous insects

International Nuclear Information System (INIS)

Nicholls, Clara Ines; Altieri, Miguel A

1998-01-01

From several decades ago the importance of natural enemies of the noxious organisms has been recognized. Unfortunately the introduction of the biological control has not had the desired dimension. The indiscriminate use of biocides products has altered the biodiversity of the agro-ecosystem. The parasitoids and predators have suffered the noxious effects of the plaguicides. These natural enemies of the plagues play a momentous paper in the regulation of noxious insects population. The predators of the insecta class register in diverse orders and the abundance of species is impressive. But the knowledge of their importance is only partial. In many countries the kindness of these organisms has not been specified and does not protect them. In the case of parasitoids something similar occurs. It is say that their biotic diversity is incalculable but very few species are exploited. In these two groups rest the classic biological control projects. The successes in projects of biological control are recognized and they are enlarging in several countries but more impulse is required. Due to demands of a sustainable agricultural production it should support the biological control of plagues. In this document general looks on the topic are expounded

Modeling biological gradient formation: combining partial differential equations and Petri nets.

Science.gov (United States)

Bertens, Laura M F; Kleijn, Jetty; Hille, Sander C; Heiner, Monika; Koutny, Maciej; Verbeek, Fons J

2016-01-01

Both Petri nets and differential equations are important modeling tools for biological processes. In this paper we demonstrate how these two modeling techniques can be combined to describe biological gradient formation. Parameters derived from partial differential equation describing the process of gradient formation are incorporated in an abstract Petri net model. The quantitative aspects of the resulting model are validated through a case study of gradient formation in the fruit fly.

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...

Compact Electro-Permeabilization System for Controlled Treatment of Biological Cells and Cell Medium Conductivity Change Measurement

Directory of Open Access Journals (Sweden)

Novickij Vitalij

2014-10-01

Full Text Available Subjection of biological cells to high intensity pulsed electric field results in the permeabilization of the cell membrane. Measurement of the electrical conductivity change allows an analysis of the dynamics of the process, determination of the permeabilization thresholds, and ion efflux influence. In this work a compact electro-permeabilization system for controlled treatment of biological cells is presented. The system is capable of delivering 5 μs - 5 ms repetitive square wave electric field pulses with amplitude up to 1 kV. Evaluation of the cell medium conductivity change is implemented in the setup, allowing indirect measurement of the ion concentration changes occurring due to the cell membrane permeabilization. The simulation model using SPICE and the experimental data of the proposed system are presented in this work. Experimental data with biological cells is also overviewed

Structural Identifiability of Dynamic Systems Biology Models.

Science.gov (United States)

Villaverde, Alejandro F; Barreiro, Antonio; Papachristodoulou, Antonis

2016-10-01

A powerful way of gaining insight into biological systems is by creating a nonlinear differential equation model, which usually contains many unknown parameters. Such a model is called structurally identifiable if it is possible to determine the values of its parameters from measurements of the model outputs. Structural identifiability is a prerequisite for parameter estimation, and should be assessed before exploiting a model. However, this analysis is seldom performed due to the high computational cost involved in the necessary symbolic calculations, which quickly becomes prohibitive as the problem size increases. In this paper we show how to analyse the structural identifiability of a very general class of nonlinear models by extending methods originally developed for studying observability. We present results about models whose identifiability had not been previously determined, report unidentifiabilities that had not been found before, and show how to modify those unidentifiable models to make them identifiable. This method helps prevent problems caused by lack of identifiability analysis, which can compromise the success of tasks such as experiment design, parameter estimation, and model-based optimization. The procedure is called STRIKE-GOLDD (STRuctural Identifiability taKen as Extended-Generalized Observability with Lie Derivatives and Decomposition), and it is implemented in a MATLAB toolbox which is available as open source software. The broad applicability of this approach facilitates the analysis of the increasingly complex models used in systems biology and other areas.

A methodology to annotate systems biology markup language models with the synthetic biology open language.

Science.gov (United States)

Roehner, Nicholas; Myers, Chris J

2014-02-21

Recently, we have begun to witness the potential of synthetic biology, noted here in the form of bacteria and yeast that have been genetically engineered to produce biofuels, manufacture drug precursors, and even invade tumor cells. The success of these projects, however, has often failed in translation and application to new projects, a problem exacerbated by a lack of engineering standards that combine descriptions of the structure and function of DNA. To address this need, this paper describes a methodology to connect the systems biology markup language (SBML) to the synthetic biology open language (SBOL), existing standards that describe biochemical models and DNA components, respectively. Our methodology involves first annotating SBML model elements such as species and reactions with SBOL DNA components. A graph is then constructed from the model, with vertices corresponding to elements within the model and edges corresponding to the cause-and-effect relationships between these elements. Lastly, the graph is traversed to assemble the annotating DNA components into a composite DNA component, which is used to annotate the model itself and can be referenced by other composite models and DNA components. In this way, our methodology can be used to build up a hierarchical library of models annotated with DNA components. Such a library is a useful input to any future genetic technology mapping algorithm that would automate the process of composing DNA components to satisfy a behavioral specification. Our methodology for SBML-to-SBOL annotation is implemented in the latest version of our genetic design automation (GDA) software tool, iBioSim.

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.

Snake Robots Modelling, Mechatronics, and Control

CERN Document Server

Liljebäck, Pål; Stavdahl, Øyvind; Gravdahl, Jan Tommy

2013-01-01

Snake Robots is a novel treatment of theoretical and practical topics related to snake robots: robotic mechanisms designed to move like biological snakes and able to operate in challenging environments in which human presence is either undesirable or impossible. Future applications of such robots include search and rescue, inspection and maintenance, and subsea operations. Locomotion in unstructured environments is a focus for this book. The text targets the disparate muddle of approaches to modelling, development and control of snake robots in current literature, giving a unified presentation of recent research results on snake robot locomotion to increase the reader’s basic understanding of these mechanisms and their motion dynamics and clarify the state of the art in the field. The book is a complete treatment of snake robotics, with topics ranging from mathematical modelling techniques, through mechatronic design and implementation, to control design strategies. The development of two snake robots is de...

Geometric Aspects of Force Controllability for a Swimming Model

International Nuclear Information System (INIS)

Khapalov, A. Y.

2008-01-01

We study controllability properties (swimming capabilities) of a mathematical model of an abstract object which 'swims' in the 2-D Stokes fluid. Our goal is to investigate how the geometric shape of this object affects the forces acting upon it. Such problems are of interest in biology and engineering applications dealing with propulsion systems in fluids

Nematodes for the biological control of the woodwasp, Sirex noctilio

Science.gov (United States)

Robin A. Bedding

2007-01-01

The tylenchid nematode Beddingia (Deladenus) siricidicola (Bedding) is by far the most important control agent of Sirex noctilio F., a major pest of pine plantations. It sterilizes female sirex, is density dependent, can achieve nearly 100 percent parasitism and, as a result of its complicated biology can be readily manipulated for sirex control. Bedding and Iede (2005...

A biologically inspired meta-control navigation system for the Psikharpax rat robot

International Nuclear Information System (INIS)

Caluwaerts, K; Staffa, M; N’Guyen, S; Grand, C; Dollé, L; Favre-Félix, A; Girard, B; Khamassi, M

2012-01-01

A biologically inspired navigation system for the mobile rat-like robot named Psikharpax is presented, allowing for self-localization and autonomous navigation in an initially unknown environment. The ability of parts of the model (e.g. the strategy selection mechanism) to reproduce rat behavioral data in various maze tasks has been validated before in simulations. But the capacity of the model to work on a real robot platform had not been tested. This paper presents our work on the implementation on the Psikharpax robot of two independent navigation strategies (a place-based planning strategy and a cue-guided taxon strategy) and a strategy selection meta-controller. We show how our robot can memorize which was the optimal strategy in each situation, by means of a reinforcement learning algorithm. Moreover, a context detector enables the controller to quickly adapt to changes in the environment—recognized as new contexts—and to restore previously acquired strategy preferences when a previously experienced context is recognized. This produces adaptivity closer to rat behavioral performance and constitutes a computational proposition of the role of the rat prefrontal cortex in strategy shifting. Moreover, such a brain-inspired meta-controller may provide an advancement for learning architectures in robotics. (paper)

ADAM: analysis of discrete models of biological systems using computer algebra.

Science.gov (United States)

Hinkelmann, Franziska; Brandon, Madison; Guang, Bonny; McNeill, Rustin; Blekherman, Grigoriy; Veliz-Cuba, Alan; Laubenbacher, Reinhard

2011-07-20

Many biological systems are modeled qualitatively with discrete models, such as probabilistic Boolean networks, logical models, Petri nets, and agent-based models, to gain a better understanding of them. The computational complexity to analyze the complete dynamics of these models grows exponentially in the number of variables, which impedes working with complex models. There exist software tools to analyze discrete models, but they either lack the algorithmic functionality to analyze complex models deterministically or they are inaccessible to many users as they require understanding the underlying algorithm and implementation, do not have a graphical user interface, or are hard to install. Efficient analysis methods that are accessible to modelers and easy to use are needed. We propose a method for efficiently identifying attractors and introduce the web-based tool Analysis of Dynamic Algebraic Models (ADAM), which provides this and other analysis methods for discrete models. ADAM converts several discrete model types automatically into polynomial dynamical systems and analyzes their dynamics using tools from computer algebra. Specifically, we propose a method to identify attractors of a discrete model that is equivalent to solving a system of polynomial equations, a long-studied problem in computer algebra. Based on extensive experimentation with both discrete models arising in systems biology and randomly generated networks, we found that the algebraic algorithms presented in this manuscript are fast for systems with the structure maintained by most biological systems, namely sparseness and robustness. For a large set of published complex discrete models, ADAM identified the attractors in less than one second. Discrete modeling techniques are a useful tool for analyzing complex biological systems and there is a need in the biological community for accessible efficient analysis tools. ADAM provides analysis methods based on mathematical algorithms as a web

Evaluation of impedance on biological Tissues using automatic control measurement system

Energy Technology Data Exchange (ETDEWEB)

Kil, Sang Hyeong; Shin, Dong Hoon; Lee, Seong Mo [Pusan National University, Yangsan (Korea, Republic of); Lee, Moo Seok; Kim, Sang Sik [Pusan National University, Busan (Korea, Republic of); Kim, Gun FDo; Lee, Jong Kyu [Pukyung National University, Busan (Korea, Republic of)

2015-08-15

Each biological tissue has endemic electrical characteristics owing to various differences such as those in cellular arrangement or organization form. The endemic electrical characteristics change when any biological change occurs. This work is a preliminary study surveying the changes in the electrical characteristics of biological tissue caused by radiation exposure. For protection against radiation hazards, therefore the electrical characteristics of living tissue were evaluated after development of the automatic control measurement system using LabVIEW. No alteration of biological tissues was observed before and after measurement of the electrical characteristics, and the biological tissues exhibited similar patterns. Through repeated measurements using the impedance/gain-phase analyzer, the coefficient of variation was determined as within 10%. The reproducibility impedance phase difference in electrical characteristics of the biological tissue did not change, and the tissue had resistance. The absolute value of impedance decreased constantly in proportion to the frequency. It has become possible to understand the electrical characteristics of biological tissues through the measurements made possible by the use of the developed.

Evaluation of impedance on biological Tissues using automatic control measurement system

International Nuclear Information System (INIS)

Kil, Sang Hyeong; Shin, Dong Hoon; Lee, Seong Mo; Lee, Moo Seok; Kim, Sang Sik; Kim, Gun FDo; Lee, Jong Kyu

2015-01-01

Each biological tissue has endemic electrical characteristics owing to various differences such as those in cellular arrangement or organization form. The endemic electrical characteristics change when any biological change occurs. This work is a preliminary study surveying the changes in the electrical characteristics of biological tissue caused by radiation exposure. For protection against radiation hazards, therefore the electrical characteristics of living tissue were evaluated after development of the automatic control measurement system using LabVIEW. No alteration of biological tissues was observed before and after measurement of the electrical characteristics, and the biological tissues exhibited similar patterns. Through repeated measurements using the impedance/gain-phase analyzer, the coefficient of variation was determined as within 10%. The reproducibility impedance phase difference in electrical characteristics of the biological tissue did not change, and the tissue had resistance. The absolute value of impedance decreased constantly in proportion to the frequency. It has become possible to understand the electrical characteristics of biological tissues through the measurements made possible by the use of the developed.

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.)

A framework to establish credibility of computational models in biology.

Science.gov (United States)

Patterson, Eann A; Whelan, Maurice P

2017-10-01

Computational models in biology and biomedical science are often constructed to aid people's understanding of phenomena or to inform decisions with socioeconomic consequences. Model credibility is the willingness of people to trust a model's predictions and is often difficult to establish for computational biology models. A 3 × 3 matrix has been proposed to allow such models to be categorised with respect to their testability and epistemic foundation in order to guide the selection of an appropriate process of validation to supply evidence to establish credibility. Three approaches to validation are identified that can be deployed depending on whether a model is deemed untestable, testable or lies somewhere in between. In the latter two cases, the validation process involves the quantification of uncertainty which is a key output. The issues arising due to the complexity and inherent variability of biological systems are discussed and the creation of 'digital twins' proposed as a means to alleviate the issues and provide a more robust, transparent and traceable route to model credibility and acceptance. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Trait-Dependent Biogeography: (Re)Integrating Biology into Probabilistic Historical Biogeographical Models.

Science.gov (United States)

Sukumaran, Jeet; Knowles, L Lacey

2018-04-20

The development of process-based probabilistic models for historical biogeography has transformed the field by grounding it in modern statistical hypothesis testing. However, most of these models abstract away biological differences, reducing species to interchangeable lineages. We present here the case for reintegration of biology into probabilistic historical biogeographical models, allowing a broader range of questions about biogeographical processes beyond ancestral range estimation or simple correlation between a trait and a distribution pattern, as well as allowing us to assess how inferences about ancestral ranges themselves might be impacted by differential biological traits. We show how new approaches to inference might cope with the computational challenges resulting from the increased complexity of these trait-based historical biogeographical models. Copyright © 2018 Elsevier Ltd. All rights reserved.

Bridging Mechanistic and Phenomenological Models of Complex Biological Systems.

Science.gov (United States)

Transtrum, Mark K; Qiu, Peng

2016-05-01

The inherent complexity of biological systems gives rise to complicated mechanistic models with a large number of parameters. On the other hand, the collective behavior of these systems can often be characterized by a relatively small number of phenomenological parameters. We use the Manifold Boundary Approximation Method (MBAM) as a tool for deriving simple phenomenological models from complicated mechanistic models. The resulting models are not black boxes, but remain expressed in terms of the microscopic parameters. In this way, we explicitly connect the macroscopic and microscopic descriptions, characterize the equivalence class of distinct systems exhibiting the same range of collective behavior, and identify the combinations of components that function as tunable control knobs for the behavior. We demonstrate the procedure for adaptation behavior exhibited by the EGFR pathway. From a 48 parameter mechanistic model, the system can be effectively described by a single adaptation parameter τ characterizing the ratio of time scales for the initial response and recovery time of the system which can in turn be expressed as a combination of microscopic reaction rates, Michaelis-Menten constants, and biochemical concentrations. The situation is not unlike modeling in physics in which microscopically complex processes can often be renormalized into simple phenomenological models with only a few effective parameters. The proposed method additionally provides a mechanistic explanation for non-universal features of the behavior.

The biological control as a strategy to support nontraditional agricultural exports in Peru: An empirical analysis

Directory of Open Access Journals (Sweden)

Franklin Duarte Cueva

2012-12-01

Full Text Available The study is oriented to explore the general characteristics of agriculture, the biological control as a pest control mechanism and agro export industry. In this context, we try to promote the use of biological control as a strategy to support nontraditional exports related to products such as asparagus and fresh avocados grown in the La Libertad Department (Peru, through an agronomic and management approach. Biological control is the basis of integrated pest management (IPM and contributes to the conservation of agricultural ecosystems allowing to export companies reduce costs, fulfill international phytosanitary measures and supports the preservation of the environment and health. Thus, the Peruvian agro export companies could build a sustainable competitive advantage and seek a positioning as socially responsible firms. We analyze variables such as crop statistics, comparative costs between biological control and chemical control, main destination markets for asparagus and fresh avocados, international standards, among others.

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.

Suppressive composts from organic wastes as agents of biological control of fusariosis in Tatartan Republic (Russia)

Science.gov (United States)

Gumerova, Raushaniya; Galitskaya, Polina; Beru, Franchesca; Selivanovskaya, Svetlana

2015-04-01

Plant diseases are one of the seriously limiting factors of agriculture efficiency around the world. Diseases caused by fungi are the major threat to plants. Crop protection in modern agriculture heavily depends on chemical fungicides. Disadvantages of chemical pesticides soon became apparent as damage to the environment and a hazard to human health. In this regard use of biopesticides becomes an attractive alternative method of plant protection. For biological control of fungal plant diseases, separate bacterial or fungal strains as well as their communities can be used. Biopreparations must consist of microbes that are typical for local climate and soil conditions and therefore are able to survive in environments for a long time. Another option of plant pests' biological control is implementation of suppressive composts made of agricultural or other organic wastes. These composts can not only prevent the development of plant diseases, but also improve the soil fertility. The objective of this work was estimation of potential of composts and strains isolated from these composts as means for biological control of fusariosis that is one of the most widespread plant soil born disease. The composts were made up of the commonly produced agricultural wastes produced in Tatarstan Republic (Russia). Fusarium oxysporum f. sp. radicis-lycopersici was used as a model phytopathogen. Ten types of organic waste (Goat manure (GM), Chicken dung (CD), Chicken dung with straw addition (CS), Rabbit dung (RD), Cow manure (CM), Rerotting pork manure (RPM), Fresh pork manure (FPM), Pork manure with sawdust and straw (PMS), the remains of plants and leaves (PL), the vegetable waste (VW) were sampled in the big farms situated in Tatarstan Republic which is one of the main agricultural regions of Russia. The initial wastes were composted for 150 days. Further, the following characteristics of the composts were assessed: pH, electro conductivity, TOC, DOC, Ntot. On petri dishes with meat

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

The big data moniker is nowhere better deserved than to describe the ever-increasing prodigiousness and complexity of biological and medical datasets. New methods are needed to generate and test hypotheses, foster biological interpretation, and build validated predictors. Although multivariate techniques such as cluster analysis may allow researchers to identify groups, or clusters, of related variables, the accuracies and effectiveness of traditional clustering methods diminish for large and hyper dimensional datasets. Topic modeling is an active research field in machine learning and has been mainly used as an analytical tool to structure large textual corpora for data mining. Its ability to reduce high dimensionality to a small number of latent variables makes it suitable as a means for clustering or overcoming clustering difficulties in large biological and medical datasets. In this study, three topic model-derived clustering methods, highest probable topic assignment, feature selection and feature extraction, are proposed and tested on the cluster analysis of three large datasets: Salmonella pulsed-field gel electrophoresis (PFGE) dataset, lung cancer dataset, and breast cancer dataset, which represent various types of large biological or medical datasets. All three various methods are shown to improve the efficacy/effectiveness of clustering results on the three datasets in comparison to traditional methods. A preferable cluster analysis method emerged for each of the three datasets on the basis of replicating known biological truths. Topic modeling could be advantageously applied to the large datasets of biological or medical research. The three proposed topic model-derived clustering methods, highest probable topic assignment, feature selection and feature extraction, yield clustering improvements for the three different data types. Clusters more efficaciously represent truthful groupings and subgroupings in the data than traditional methods, suggesting

The biological carbon pump in the ocean: Reviewing model representations and its feedbacks on climate perturbations.

Science.gov (United States)

Hülse, Dominik; Arndt, Sandra; Ridgwell, Andy; Wilson, Jamie

2016-04-01

The ocean-sediment system, as the biggest carbon reservoir in the Earth's carbon cycle, plays a crucial role in regulating atmospheric carbon dioxide concentrations and climate. Therefore, it is essential to constrain the importance of marine carbon cycle feedbacks on global warming and ocean acidification. Arguably, the most important single component of the ocean's carbon cycle is the so-called "biological carbon pump". It transports carbon that is fixed in the light-flooded surface layer of the ocean to the deep ocean and the surface sediment, where it is degraded/dissolved or finally buried in the deep sediments. Over the past decade, progress has been made in understanding different factors that control the efficiency of the biological carbon pump and their feedbacks on the global carbon cycle and climate (i.e. ballasting = ocean acidification feedback; temperature dependant organic matter degradation = global warming feedback; organic matter sulphurisation = anoxia/euxinia feedback). Nevertheless, many uncertainties concerning the interplay of these processes and/or their relative significance remain. In addition, current Earth System Models tend to employ empirical and static parameterisations of the biological pump. As these parametric representations are derived from a limited set of present-day observations, their ability to represent carbon cycle feedbacks under changing climate conditions is limited. The aim of my research is to combine past carbon cycling information with a spatially resolved global biogeochemical model to constrain the functioning of the biological pump and to base its mathematical representation on a more mechanistic approach. Here, I will discuss important aspects that control the efficiency of the ocean's biological carbon pump, review how these processes of first order importance are mathematically represented in existing Earth system Models of Intermediate Complexity (EMIC) and distinguish different approaches to approximate

A graphical method for reducing and relating models in systems biology.

Science.gov (United States)

Gay, Steven; Soliman, Sylvain; Fages, François

2010-09-15

In Systems Biology, an increasing collection of models of various biological processes is currently developed and made available in publicly accessible repositories, such as biomodels.net for instance, through common exchange formats such as SBML. To date, however, there is no general method to relate different models to each other by abstraction or reduction relationships, and this task is left to the modeler for re-using and coupling models. In mathematical biology, model reduction techniques have been studied for a long time, mainly in the case where a model exhibits different time scales, or different spatial phases, which can be analyzed separately. These techniques are however far too restrictive to be applied on a large scale in systems biology, and do not take into account abstractions other than time or phase decompositions. Our purpose here is to propose a general computational method for relating models together, by considering primarily the structure of the interactions and abstracting from their dynamics in a first step. We present a graph-theoretic formalism with node merge and delete operations, in which model reductions can be studied as graph matching problems. From this setting, we derive an algorithm for deciding whether there exists a reduction from one model to another, and evaluate it on the computation of the reduction relations between all SBML models of the biomodels.net repository. In particular, in the case of the numerous models of MAPK signalling, and of the circadian clock, biologically meaningful mappings between models of each class are automatically inferred from the structure of the interactions. We conclude on the generality of our graphical method, on its limits with respect to the representation of the structure of the interactions in SBML, and on some perspectives for dealing with the dynamics. The algorithms described in this article are implemented in the open-source software modeling platform BIOCHAM available at http

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.).

PENGARUH MODEL PEMBELAJARAN SYNECTICS DIPADU MIND MAPS TERHADAP KEMAMPUAN BERPIKIR KREATIF, SIKAP KREATIF, DAN PENGUASAAN MATERI BIOLOGI

Directory of Open Access Journals (Sweden)

Muh Khalifah Mustami

2007-12-01

Full Text Available One of the important tasks in teaching is assisting students to think. Synectics Model matched with Mind Maps are viewed necessary to be applied in the instruction in order to achieve the target.The research is an experiment research with pre-test post-test control group design. The results of analyses indicate that: (1 there is significance difference with the mean score of creative think ability, creative attitude, and mastery of biology materials due to difference of instruction model used, (2 there is no significant difference of mean score of creative attitude among the students who belong to the high and low achievement. (3 there is no interactional effect between the instructional model used with the students entry behavior towards creative thinking ability, creative attitude, and mastery of biology materials.

Speed adaptation in a powered transtibial prosthesis controlled with a neuromuscular model.

Science.gov (United States)

Markowitz, Jared; Krishnaswamy, Pavitra; Eilenberg, Michael F; Endo, Ken; Barnhart, Chris; Herr, Hugh

2011-05-27

Control schemes for powered ankle-foot prostheses would benefit greatly from a means to make them inherently adaptive to different walking speeds. Towards this goal, one may attempt to emulate the intact human ankle, as it is capable of seamless adaptation. Human locomotion is governed by the interplay among legged dynamics, morphology and neural control including spinal reflexes. It has been suggested that reflexes contribute to the changes in ankle joint dynamics that correspond to walking at different speeds. Here, we use a data-driven muscle-tendon model that produces estimates of the activation, force, length and velocity of the major muscles spanning the ankle to derive local feedback loops that may be critical in the control of those muscles during walking. This purely reflexive approach ignores sources of non-reflexive neural drive and does not necessarily reflect the biological control scheme, yet can still closely reproduce the muscle dynamics estimated from biological data. The resulting neuromuscular model was applied to control a powered ankle-foot prosthesis and tested by an amputee walking at three speeds. The controller produced speed-adaptive behaviour; net ankle work increased with walking speed, highlighting the benefits of applying neuromuscular principles in the control of adaptive prosthetic limbs.

Controlled polymer synthesis--from biomimicry towards synthetic biology.

Science.gov (United States)

Pasparakis, George; Krasnogor, Natalio; Cronin, Leroy; Davis, Benjamin G; Alexander, Cameron

2010-01-01

The controlled assembly of synthetic polymer structures is now possible with an unprecedented range of functional groups and molecular architectures. In this critical review we consider how the ability to create artificial materials over lengthscales ranging from a few nm to several microns is generating systems that not only begin to mimic those in nature but also may lead to exciting applications in synthetic biology (139 references).

Computer modeling in developmental biology: growing today, essential tomorrow.

Science.gov (United States)

Sharpe, James

2017-12-01

D'Arcy Thompson was a true pioneer, applying mathematical concepts and analyses to the question of morphogenesis over 100 years ago. The centenary of his famous book, On Growth and Form , is therefore a great occasion on which to review the types of computer modeling now being pursued to understand the development of organs and organisms. Here, I present some of the latest modeling projects in the field, covering a wide range of developmental biology concepts, from molecular patterning to tissue morphogenesis. Rather than classifying them according to scientific question, or scale of problem, I focus instead on the different ways that modeling contributes to the scientific process and discuss the likely future of modeling in developmental biology. © 2017. Published by The Company of Biologists Ltd.

The inception and evolution of a unique masters program in cancer biology, prevention and control.

Science.gov (United States)

Cousin, Carolyn; Blancato, Jan

2010-09-01

The University of the District of Columbia (UDC) and the Lombardi Comprehensive Cancer Center (LCCC), Georgetown University Medical Center established a Masters Degree Program in Cancer Biology, Prevention and Control at UDC that is jointly administered and taught by UDC and LCCC faculty. The goal of the Masters Degree Program is to educate students as master-level cancer professionals capable of conducting research and service in cancer biology, prevention, and control or to further advance the education of students to pursue doctoral studies. The Program's unique nature is reflected in its philosophy "the best cancer prevention and control researchers are those with a sound understanding of cancer biology". This program is a full-time, 2-year, 36-credit degree in which students take half of their coursework at UDC and half of their coursework at LCCC. During the second year, students are required to conduct research either at LCCC or UDC. Unlike most cancer biology programs, this unique Program emphasizes both cancer biology and cancer outreach training.

77 FR 46373 - Field Release of Aphelinus glycinis for the Biological Control of the Soybean Aphid in the...

Science.gov (United States)

2012-08-03

... Inspection Service [Docket No APHIS-2012-0061] Field Release of Aphelinus glycinis for the Biological Control... for the biological control of the soybean aphid, Aphis glycines, in the continental United States. We... glycinis for the Biological Control of the Soybean Aphid in the Continental United States'' (March 2012...

Modeling Dispersion of Chemical-Biological Agents in Three Dimensional Living Space

International Nuclear Information System (INIS)

William S. Winters

2002-01-01

This report documents a series of calculations designed to demonstrate Sandia's capability in modeling the dispersal of chemical and biological agents in complex three-dimensional spaces. The transport of particles representing biological agents is modeled in a single room and in several connected rooms. The influence of particle size, particle weight and injection method are studied

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

Biological control of corky root in tomato.

Science.gov (United States)

Fiume, G; Fiume, F

2008-01-01

Corky root caused by Pyrenochaeta lycopersici (Schneider et Gerlach) is one of the most important soil borne fungal pathogens which develops in the soils, causing diseases in different crops. The research was carried out to evaluate the effectiveness of the biological control of corky root on tomato. Biological control was performed by using Trichoderma viride Pers. 18/17 SS, Streptomyces spp. AtB42 and Bacillus subtilis M51 PI. According to present and future regulations on the use of chemical fungicides and considering that treatments must avoids environmental pollution, the main object of this research was to find alternative strategies by using biocontrol agents against P. lycopersici that affect tomato plants. In laboratory, the effectiveness of T. viride 18/17 SS, Streptomyces spp. AtB42 and B. subtilis M51 PI to control P. lycopersici were studied. In greenhouse, the research was carried out comparing the following treatments: 1) untreated control; 2) T. viride 18/17 SS; 3) Streptomyces spp. AtB42; 4) B. subtilis M51 PI. Roots of plants of tomato H3028 Hazera were treated with the antagonist suspensions just prior of transplant. Treatments were repeated about 2 months after, with the same suspensions sprayed on the soil to the plant collar. In dual culture, the inhibition of P. lycopersici ranged up to 81.2% (caused from T. viride 18/17 SS), 75.6% (from Streptomyces spp. AtB42) and 66.8% (from B. subtilis M51 PI). In greenhouse trials, with regard to corky root symptoms, all treated plots showed signifycative differences compared to untreated. T. viride gave the better results followed by Streptomyces spp. and then by B. subtilis. The fungus antagonist showed good root surface competence such as demonstrated its persistence on the roots surface of the tomato plants whose roots were treated with T. viride 18/17 SS up to 2 months before.

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.

Evaluation of biological models using Spacelab

Science.gov (United States)

Tollinger, D.; Williams, B. A.

1980-01-01

Biological models of hypogravity effects are described, including the cardiovascular-fluid shift, musculoskeletal, embryological and space sickness models. These models predict such effects as loss of extracellular fluid and electrolytes, decrease in red blood cell mass, and the loss of muscle and bone mass in weight-bearing portions of the body. Experimentation in Spacelab by the use of implanted electromagnetic flow probes, by fertilizing frog eggs in hypogravity and fixing the eggs at various stages of early development and by assessing the role of the vestibulocular reflex arc in space sickness is suggested. It is concluded that the use of small animals eliminates the uncertainties caused by corrective or preventive measures employed with human subjects.

Methylene Diphosphonate Chemical and Biological control of MDP complex

International Nuclear Information System (INIS)

Aungurarat, Angkanan; Ngamprayad, Tippanan

2000-01-01

Technetium-9 9m MDP easy prepared from MDP kits which different sources such as OAP (In house), SIGMA. The resulting Tc 9 9m -MDP preparations were controlled in chemical and biological tests to compare the different results in these cases: radiochemical purity, the quantity of starting material and biodistribution result

[Physicians' knowledge in Israel on the biology and control of head lice].

Science.gov (United States)

Mumcuoglu, Kosta Y; Mumcuoglu, Michael; Danilevich, Maria; Gilead, Leon

2008-10-01

Health providers such as physicians, nurses and pharmacists should be knowledgeable about the biology of head lice and the ways to control them effectively, in order to reduce the proportion of children infested with head lice. To evaluate the knowledge of physicians in Israel on the biology and epidemiology of lice, as well as their experience with infested individuals and their preferences for diagnosis, prophylaxis and control. An anonymous questionnaire with 37 questions was used. The first 20 questions addressed the general knowledge of physicians on lice biology and control, while the remaining 17 questions were related to their personal experience with lice and louse treatment. Out of 273 physicians interviewed 66.8% had good knowledge of lice, while the remaining 33.2% had some knowledge on lice. The difference between the groups of physicians with medium and good knowledge on lice was borderline significant (P=0.0722), with the dermatologists borderline significantly less knowledgeable than the rest (P=0.0765). Significant differences were found between those physicians with 4-6 or 11-20 years of professional experience and the remaining groups (twice Pbiology and control was higher than male physicians (39.4% and 29.4%, respectively), the differences were borderline significant (P=0.09). Pediatricians and dermatologists examined significantly more children than family physicians and general practitioners (P control of head louse infestations.

76 FR 3076 - Availability of an Environmental Assessment for a Biological Control Agent for Air Potato

Science.gov (United States)

2011-01-19

...] Availability of an Environmental Assessment for a Biological Control Agent for Air Potato AGENCY: Animal and... environmental assessment (EA) relative to the control of air potato (Dioscorea bulbifera). The EA considers the... States for use as a biological control agent to reduce the severity of air potato infestations. We are...

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.

SBMLeditor: effective creation of models in the Systems Biology Markup language (SBML).

Science.gov (United States)

Rodriguez, Nicolas; Donizelli, Marco; Le Novère, Nicolas

2007-03-06

The need to build a tool to facilitate the quick creation and editing of models encoded in the Systems Biology Markup language (SBML) has been growing with the number of users and the increased complexity of the language. SBMLeditor tries to answer this need by providing a very simple, low level editor of SBML files. Users can create and remove all the necessary bits and pieces of SBML in a controlled way, that maintains the validity of the final SBML file. SBMLeditor is written in JAVA using JCompneur, a library providing interfaces to easily display an XML document as a tree. This decreases dramatically the development time for a new XML editor. The possibility to include custom dialogs for different tags allows a lot of freedom for the editing and validation of the document. In addition to Xerces, SBMLeditor uses libSBML to check the validity and consistency of SBML files. A graphical equation editor allows an easy manipulation of MathML. SBMLeditor can be used as a module of the Systems Biology Workbench. SBMLeditor contains many improvements compared to a generic XML editor, and allow users to create an SBML model quickly and without syntactic errors.

[Accidents with biological materials among nurses in a training hospital: case-control study].

Science.gov (United States)

Dalarosa, Micheline Gisele; Lautert, Liana

2009-03-01

This case-control study aimed at analyzing the association between occupational stress and disagreement between chronotype and the work shift of nurses who suffered accidents with biological materials in a hospital of Porto Alegre, Rio Grande do Sul, Brazil. A number of 99 workers who suffered accidents (cases) and 232 that had not suffered accidents (controls) were interviewed. Data were collected through the Job Stress Scale according to Karasek's model and the Horne-Ostberg scale The occurrence of accident was not statistically associated with high work requirement scores (p = 0.317), with a chronobiological profile discordant with work shift (p = 0.563), or with other labor variables associated to accidents--overtime, having two jobs (p = 1.000). In addition, there was no significant difference (chi2 Pearson; p = 1.00) among the scores of professionals with high work requirements who work in shifts discordant with their chronotype, both in the case group and in the control group as well.

Radiochemical and biological control of metaiodobenzyl-guanidine (MIBG) labeled with 131I

International Nuclear Information System (INIS)

Barboza, M.R.F.F. de; Muramoto, E.; Colturato, M.T.; Silva Valente Goncalves, R. da; Pereira, N.P.S. de; Almeida, M.A.T.M. de; Silva, C.P.G. da.

1988-07-01

This study shows the standardization of the radiochemical control of MIBG - 131 I in eletrophoretic system and also the biological control in Wistar rat for a period of time, not longer than 60 minutes after tracer administration. (author) [pt

Conservation biological control and enemy diversity on a landscape scale

NARCIS (Netherlands)

Tscharntke, T.; Bommarco, R.; Clough, Y.; Crist, T.O.; Kleijn, D.; Rand, T.A.; Tylianakis, J.M.; Nouhuys, S.; Vidal, S.

2007-01-01

Conservation biological control in agroecosystems requires a landscape management perspective, because most arthropod species experience their habitat at spatial scales beyond the plot level, and there is spillover of natural enemies across the crop–noncrop interface. The species pool in the

Reliability of unstable periodic orbit based control strategies in biological systems

Energy Technology Data Exchange (ETDEWEB)

Mishra, Nagender; Singh, Harinder P. [Department of Physics and Astrophysics, University of Delhi, Delhi 110007 (India); Hasse, Maria [Institut für Höchstleistungsrechnen, Universität Stuttgart, D-70569 Stuttgart (Germany); Biswal, B. [Cluster Innovation Center, University of Delhi, Delhi 110007 (India); Sri Venkateswara College, University of Delhi, Delhi 110021 (India)

2015-04-15

Presence of recurrent and statistically significant unstable periodic orbits (UPOs) in time series obtained from biological systems is now routinely used as evidence for low dimensional chaos. Extracting accurate dynamical information from the detected UPO trajectories is vital for successful control strategies that either aim to stabilize the system near the fixed point or steer the system away from the periodic orbits. A hybrid UPO detection method from return maps that combines topological recurrence criterion, matrix fit algorithm, and stringent criterion for fixed point location gives accurate and statistically significant UPOs even in the presence of significant noise. Geometry of the return map, frequency of UPOs visiting the same trajectory, length of the data set, strength of the noise, and degree of nonstationarity affect the efficacy of the proposed method. Results suggest that establishing determinism from unambiguous UPO detection is often possible in short data sets with significant noise, but derived dynamical properties are rarely accurate and adequate for controlling the dynamics around these UPOs. A repeat chaos control experiment on epileptic hippocampal slices through more stringent control strategy and adaptive UPO tracking is reinterpreted in this context through simulation of similar control experiments on an analogous but stochastic computer model of epileptic brain slices. Reproduction of equivalent results suggests that far more stringent criteria are needed for linking apparent success of control in such experiments with possible determinism in the underlying dynamics.

Reliability of unstable periodic orbit based control strategies in biological systems

International Nuclear Information System (INIS)

Mishra, Nagender; Singh, Harinder P.; Hasse, Maria; Biswal, B.

2015-01-01

Presence of recurrent and statistically significant unstable periodic orbits (UPOs) in time series obtained from biological systems is now routinely used as evidence for low dimensional chaos. Extracting accurate dynamical information from the detected UPO trajectories is vital for successful control strategies that either aim to stabilize the system near the fixed point or steer the system away from the periodic orbits. A hybrid UPO detection method from return maps that combines topological recurrence criterion, matrix fit algorithm, and stringent criterion for fixed point location gives accurate and statistically significant UPOs even in the presence of significant noise. Geometry of the return map, frequency of UPOs visiting the same trajectory, length of the data set, strength of the noise, and degree of nonstationarity affect the efficacy of the proposed method. Results suggest that establishing determinism from unambiguous UPO detection is often possible in short data sets with significant noise, but derived dynamical properties are rarely accurate and adequate for controlling the dynamics around these UPOs. A repeat chaos control experiment on epileptic hippocampal slices through more stringent control strategy and adaptive UPO tracking is reinterpreted in this context through simulation of similar control experiments on an analogous but stochastic computer model of epileptic brain slices. Reproduction of equivalent results suggests that far more stringent criteria are needed for linking apparent success of control in such experiments with possible determinism in the underlying dynamics

When one model is not enough: Combining epistemic tools in systems biology

DEFF Research Database (Denmark)

Green, Sara

2013-01-01

. The conceptual repertoire of Rheinberger’s historical epistemology offers important insights for an analysis of the modelling practice. I illustrate this with a case study on network modeling in systems biology where engineering approaches are applied to the study of biological systems. I shall argue...

Biological Control of Diseases of Vegetables Grown Hydroponically in Thailand: Challenge and Opportunity.

Science.gov (United States)

Kanjanamaneesathian, Mana

2015-01-01

In Thailand, yield loss due to plant diseases in vegetables grown hydroponically is very high as a result of the growers` lack of knowledge for controlling diseases and their un- willingness to invest in setting-up the proper hydroponic system from the beginning. Severe root rot disease caused by Pythium spp. is frequent and can be anticipated in the hot climate in Thailand. This review focuses on the diseases in temperate lettuces which have been produced hydroponically and have been attacked by plant pathogens, particularly Pythium spp. Biological control of vegetable diseases grown hydroponically has been investigated in Thailand. Research is being carried out to identify effective strains of the antagonists, formulating the applicable products and delivering them appropriately to control the disease. Products of Bacillus subtilis, Chaetomium globosom and Trichoderma harzianum have been recommended for use to control diseases in vegetables grown hydroponically. Control efficacy of these products is varied as the biological products have been used by the growers in the paradigm of using chemical fungicide for disease control in hydroponic production system, overlooking the intrinsic characteristics of the biological control products. The recent patent, which minimizes the effects of sunlight and heat on the nutrient solution without the use of an external energy for cooling the nutrient, should be applied in producing hydroponic vegetables to mitigate poor plant growth and root rot disease outbreak in Thailand.

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.

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.

Biclustering with Flexible Plaid Models to Unravel Interactions between Biological Processes.

Science.gov (United States)

Henriques, Rui; Madeira, Sara C

2015-01-01

Genes can participate in multiple biological processes at a time and thus their expression can be seen as a composition of the contributions from the active processes. Biclustering under a plaid assumption allows the modeling of interactions between transcriptional modules or biclusters (subsets of genes with coherence across subsets of conditions) by assuming an additive composition of contributions in their overlapping areas. Despite the biological interest of plaid models, few biclustering algorithms consider plaid effects and, when they do, they place restrictions on the allowed types and structures of biclusters, and suffer from robustness problems by seizing exact additive matchings. We propose BiP (Biclustering using Plaid models), a biclustering algorithm with relaxations to allow expression levels to change in overlapping areas according to biologically meaningful assumptions (weighted and noise-tolerant composition of contributions). BiP can be used over existing biclustering solutions (seizing their benefits) as it is able to recover excluded areas due to unaccounted plaid effects and detect noisy areas non-explained by a plaid assumption, thus producing an explanatory model of overlapping transcriptional activity. Experiments on synthetic data support BiP's efficiency and effectiveness. The learned models from expression data unravel meaningful and non-trivial functional interactions between biological processes associated with putative regulatory modules.

Adaptive Fuzzy-Lyapunov Controller Using Biologically Inspired Swarm Intelligence

Directory of Open Access Journals (Sweden)

Alejandro Carrasco Elizalde

2008-01-01

Full Text Available The collective behaviour of swarms produces smarter actions than those achieved by a single individual. Colonies of ants, flocks of birds and fish schools are examples of swarms interacting with their environment to achieve a common goal. This cooperative biological intelligence is the inspiration for an adaptive fuzzy controller developed in this paper. Swarm intelligence is used to adjust the parameters of the membership functions used in the adaptive fuzzy controller. The rules of the controller are designed using a computing-with-words approach called Fuzzy-Lyapunov synthesis to improve the stability and robustness of an adaptive fuzzy controller. Computing-with-words provides a powerful tool to manipulate numbers and symbols, like words in a natural language.

Biological control of fruit flies (Diptera: Tephritidae) through parasitoid augmentative releases: Current status

International Nuclear Information System (INIS)

Montoya, Pablo; Liedo, Pablo

2000-01-01

Fruit flies are among the main pests affecting the world fruit industry (Aluja 1993). Bait sprays have traditionally been used successfully to control them; however, the side effects on the environment and health hazards commonly associated with pesticides, have resulted in strong public opposition to the use of bait sprays. This is particularly so when sprays are applied in urban areas or in coffee plantations where, although Medflies are present, they do not pose a danger to crops. Alternative methods that are effective and environmental friendly to suppress fruit fly populations are highly desirable. Biological control, the use of natural enemies to suppress pest populations, represents such an alternative. Some of the most successful cases of biological control are the control of Iceria purchasi Maskell (Homoptera: Margarodidae) by Rodolia cardinalis Mulsant (Coleoptera: Coccinellidae) in California (De Bach 1968, van den Bosch et al. 1982), and the control of Aleurocanthus woglumi Ashby (Homoptera: Aleyrodidae) mainly by Encarsia (=Prospaltella) opulenta Silv. (Hymenoptera: Aphelinidae) in Mexico (Jimenez 1961, 1971), both using the classical approach. However, this approach has been limited to certain conditions of environmental stability and biodiversity which are only found in a few ecosystems. Other factors, such as types of pests, the economic threshold and product quality requirements represent additional limitations. The best option in many cases could be augmentative biological control, which could overcome some of the deficiencies of the classical approach (Sivinski 1996). According to Knipling (1992) and Barclay (1987), augmentative biological control can be considered as a formal alternative for suppressing pest populations and even for use in eradication programmes, after integration with the sterile insect technique (SIT). In this approach, mass production of natural enemies is required and this production has to be cost effective

Poly lactic acid based injectable delivery systems for controlled release of a model protein, lysozyme.

Science.gov (United States)

Al-Tahami, Khaled; Meyer, Amanda; Singh, Jagdish

2006-02-01

The objective of this study was to evaluate the critical formulation parameters (i.e., polymer concentration, polymer molecular weight, and solvent nature) affecting the controlled delivery of a model protein, lysozyme, from injectable polymeric implants. The conformational stability and biological activity of the released lysozyme were also investigated. Three formulations containing 10%, 20%, and 30% (w/v) poly lactic acid (PLA) in triacetin were investigated. It was found that increasing polymer concentration in the formulations led to a lower burst effect and a slower release rate. Formulation with a high molecular weight polymer showed a greater burst effect as compared to those containing low molecular weight. Conformational stability and biological activity of released samples were studied by differential scanning calorimeter and enzyme activity assay, respectively. The released samples had significantly (P solution kept at same conditions). Increasing polymer concentration increased both the conformational stability and the biological activity of released lysozyme. In conclusion, phase sensitive polymer-based delivery systems were able to deliver a model protein, lysozyme, in a conformationally stable and biologically active form at a controlled rate over an extended period.

Biologically based modelling and simulation of carcinogenesis at low doses

International Nuclear Information System (INIS)

Ouchi, Noriyuki B.

2003-01-01

The process of the carcinogenesis is studied by computer simulation. In general, we need a large number of experimental samples to detect mutations at low doses, but in practice it is difficult to get such a large number of data. To satisfy the requirements of the situation at low doses, it is good to study the process of carcinogenesis using biologically based mathematical model. We have mainly studied it by using as known as 'multi-stage model'; the model seems to get complicated, as we adopt the recent new findings of molecular biological experiments. Moreover, the basic idea of the multi-stage model is based on the epidemiologic data of log-log variation of cancer incidence with age, it seems to be difficult to compare with experimental data of irradiated cell culture system, which has been increasing in recent years. Taking above into consideration, we concluded that we had better make new model with following features: 1) a unit of the target system is a cell, 2) the new information of the molecular biology can be easily introduced, 3) having spatial coordinates for checking a colony formation or tumorigenesis. In this presentation, we will show the detail of the model and some simulation results about the carcinogenesis. (author)

A Novel Method to Verify Multilevel Computational Models of Biological Systems Using Multiscale Spatio-Temporal Meta Model Checking.

Science.gov (United States)

Pârvu, Ovidiu; 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 meta model checking concept. To automate the computational model verification process we have implemented the model checking approach in the software tool Mule (http://mule.modelchecking.org). Its applicability is illustrated against four systems biology computational models previously published in the literature encoding the rat cardiovascular system dynamics, the uterine contractions of labour

Symmetry structure in discrete models of biochemical systems: natural subsystems and the weak control hierarchy in a new model of computation driven by interactions.

Science.gov (United States)

Nehaniv, Chrystopher L; Rhodes, John; Egri-Nagy, Attila; Dini, Paolo; Morris, Eric Rothstein; Horváth, Gábor; Karimi, Fariba; Schreckling, Daniel; Schilstra, Maria J

2015-07-28

Interaction computing is inspired by the observation that cell metabolic/regulatory systems construct order dynamically, through constrained interactions between their components and based on a wide range of possible inputs and environmental conditions. The goals of this work are to (i) identify and understand mathematically the natural subsystems and hierarchical relations in natural systems enabling this and (ii) use the resulting insights to define a new model of computation based on interactions that is useful for both biology and computation. The dynamical characteristics of the cellular pathways studied in systems biology relate, mathematically, to the computational characteristics of automata derived from them, and their internal symmetry structures to computational power. Finite discrete automata models of biological systems such as the lac operon, the Krebs cycle and p53-mdm2 genetic regulation constructed from systems biology models have canonically associated algebraic structures (their transformation semigroups). These contain permutation groups (local substructures exhibiting symmetry) that correspond to 'pools of reversibility'. These natural subsystems are related to one another in a hierarchical manner by the notion of 'weak control'. We present natural subsystems arising from several biological examples and their weak control hierarchies in detail. Finite simple non-Abelian groups are found in biological examples and can be harnessed to realize finitary universal computation. This allows ensembles of cells to achieve any desired finitary computational transformation, depending on external inputs, via suitably constrained interactions. Based on this, interaction machines that grow and change their structure recursively are introduced and applied, providing a natural model of computation driven by interactions.

Stakeholder perceptions: Biological control of Russian olive (Elaeagnus angustifolia)

Science.gov (United States)

Sharlene E. Sing; Kevin J. Delaney

2016-01-01

An online survey was distributed through email lists provided by various stakeholder groups on behalf of the International Consortium for Biological Control of Russian Olive in spring of 2012. A total of 392 respondents replied from 24 U.S. states and 1 Canadian province. Questions posed in the survey were designed to identify and categorize 1) stakeholders by...

Is the efficacy of biological control against plant diseases likely to be more durable than that of chemical pesticides?

Directory of Open Access Journals (Sweden)

Marc eBardin

2015-07-01

Full Text Available The durability of a control method for plant protection is defined as the persistence of its efficacy in space and time. It depends on (i the selection pressure exerted by it on populations of plant pathogens and (ii on the capacity of these pathogens to adapt to the control method. Erosion of effectiveness of conventional plant protection methods has been widely studied in the past. For example, apparition of resistance to chemical pesticides in plant pathogens or pests has been extensively documented. The durability of biological control has often been assumed to be higher than that of chemical control. Results concerning pest management in agricultural systems have shown that this assumption may not always be justified. Resistance of various pests to one or several toxins of Bacillus thuringensis and apparition of resistance of the codling moth Cydia pomonella to the Cydia pomonella granulovirus have, for example, been described. In contrast with the situation for pests, the durability of biological control of plant diseases has hardly been studied and no scientific reports proving the loss of efficiency of biological control agents against plant pathogens in practice has been published so far. Knowledge concerning the possible erosion of effectiveness of biological control is essential to ensure a durable efficacy of biological control agents on target plant pathogens. This knowledge will result in identifying risk factors that can foster the selection of strains of plant pathogens resistant to biological control agents. It will also result in identifying types of biological control agents with lower risk of efficacy loss i.e. modes of action of biological control agents that does not favor the selection of resistant isolates in natural populations of plant pathogens. An analysis of the scientific literature was then conducted to assess the potential for plant pathogens to become resistant to biological control agents.

Yeast as a Model System to Study Tau Biology

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Ann De Vos

2011-01-01

Full Text Available Hyperphosphorylated and aggregated human protein tau constitutes a hallmark of a multitude of neurodegenerative diseases called tauopathies, exemplified by Alzheimer's disease. In spite of an enormous amount of research performed on tau biology, several crucial questions concerning the mechanisms of tau toxicity remain unanswered. In this paper we will highlight some of the processes involved in tau biology and pathology, focusing on tau phosphorylation and the interplay with oxidative stress. In addition, we will introduce the development of a human tau-expressing yeast model, and discuss some crucial results obtained in this model, highlighting its potential in the elucidation of cellular processes leading to tau toxicity.

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

Improving the cost-effectiveness, trade and safety of biological control for agricultural insect pests using nuclear techniques

Science.gov (United States)

If appropriately applied, biological control offers one of the most promising, environmentally sound, and sustainable control tactics for arthropod pests and weeds for application as part of an integrated pest management (IPM) approach. Public support for biological control as one of the preferred m...

The neural optimal control hierarchy for motor control

Science.gov (United States)

DeWolf, T.; Eliasmith, C.

2011-10-01

Our empirical, neuroscientific understanding of biological motor systems has been rapidly growing in recent years. However, this understanding has not been systematically mapped to a quantitative characterization of motor control based in control theory. Here, we attempt to bridge this gap by describing the neural optimal control hierarchy (NOCH), which can serve as a foundation for biologically plausible models of neural motor control. The NOCH has been constructed by taking recent control theoretic models of motor control, analyzing the required processes, generating neurally plausible equivalent calculations and mapping them on to the neural structures that have been empirically identified to form the anatomical basis of motor control. We demonstrate the utility of the NOCH by constructing a simple model based on the identified principles and testing it in two ways. First, we perturb specific anatomical elements of the model and compare the resulting motor behavior with clinical data in which the corresponding area of the brain has been damaged. We show that damaging the assigned functions of the basal ganglia and cerebellum can cause the movement deficiencies seen in patients with Huntington's disease and cerebellar lesions. Second, we demonstrate that single spiking neuron data from our model's motor cortical areas explain major features of single-cell responses recorded from the same primate areas. We suggest that together these results show how NOCH-based models can be used to unify a broad range of data relevant to biological motor control in a quantitative, control theoretic framework.

The sensitivity of Turing self-organization to biological feedback delays: 2D models of fish pigmentation

KAUST Repository

Gaffney, E. A.

2013-10-01

© The authors 2013. Turing morphogen models have been extensively explored in the context of large-scale self-organization in multicellular biological systems. However, reconciling the detailed biology of morphogen dynamics, while accounting for time delays associated with gene expression, reveals aberrant behaviours that are not consistent with early developmental self-organization, especially the requirement for exquisite temporal control. Attempts to reconcile the interpretation of Turing\\'s ideas with an increasing understanding of the mechanisms driving zebrafish pigmentation suggests that one should reconsider Turing\\'s model in terms of pigment cells rather than morphogens (Nakamasu et al., 2009, PNAS, 106, 8429-8434; Yamaguchi et al., 2007, PNAS, 104, 4790-4793). Here the dynamics of pigment cells is subject to response delays implicit in the cell cycle and apoptosis. Hence we explore simulations of fish skin patterning, focussing on the dynamical influence of gene expression delays in morphogen-based Turing models and response delays for cell-based Turing models. We find that reconciling the mechanisms driving the behaviour of Turing systems with observations of fish skin patterning remains a fundamental challenge.

An Evaluation of Teachers' Attitudes and Beliefs Levels on Classroom Control in Terms of Teachers' Sense of Efficacy (The Sample of Biology Teachers in Turkey)

Science.gov (United States)

Kurt, Hakan

2014-01-01

The aim of this study is to evaluate biology teachers' attitudes and belief levels on classroom control in terms of teachers' sense of efficacy. The screening model was used in the study. The study group was comprised of 135 biology teachers. In this study, Teachers' Sense of Efficacy Scale (TSES) and The Attitudes and Beliefs on Classroom Control…

Control of Stochastic Master Equation Models of Genetic Regulatory Networks by Approximating Their Average Behavior

Science.gov (United States)

Umut Caglar, Mehmet; Pal, Ranadip

2010-10-01

The central dogma of molecular biology states that ``information cannot be transferred back from protein to either protein or nucleic acid.'' However, this assumption is not exactly correct in most of the cases. There are a lot of feedback loops and interactions between different levels of systems. These types of interactions are hard to analyze due to the lack of data in the cellular level and probabilistic nature of interactions. Probabilistic models like Stochastic Master Equation (SME) or deterministic models like differential equations (DE) can be used to analyze these types of interactions. SME models based on chemical master equation (CME) can provide detailed representation of genetic regulatory system, but their use is restricted by the large data requirements and computational costs of calculations. The differential equations models on the other hand, have low calculation costs and much more adequate to generate control procedures on the system; but they are not adequate to investigate the probabilistic nature of interactions. In this work the success of the mapping between SME and DE is analyzed, and the success of a control policy generated by DE model with respect to SME model is examined. Index Terms--- Stochastic Master Equation models, Differential Equation Models, Control Policy Design, Systems biology

Candidate predators for biological control of the poultry red mite Dermanyssus gallinae

NARCIS (Netherlands)

Lesna, I.; Wolfs, P.; Faraji, F.; Roy, L.; Komdeur, J.; Sabelis, M.W.

2009-01-01

The poultry red mite, Dermanyssus gallinae, is currently a significant pest in the poultry industry in Europe. Biological control by the introduction of predatory mites is one of the various options for controlling poultry red mites. Here, we present the first results of an attempt to identify

Candidate predators for biological control of the poultry red mite Dermanyssus gallinae

NARCIS (Netherlands)

Lesna, Izabela; Wolfs, Peter; Faraji, Farid; Roy, Lise; Komdeur, Jan; Sabelis, Maurice W.

The poultry red mite, Dermanyssus gallinae, is currently a significant pest in the poultry industry in Europe. Biological control by the introduction of predatory mites is one of the various options for controlling poultry red mites. Here, we present the first results of an attempt to identify

Building executable biological pathway models automatically from BioPAX

NARCIS (Netherlands)

Willemsen, Timo; Feenstra, Anton; Groth, Paul

2013-01-01

The amount of biological data exposed in semantic formats is steadily increasing. In particular, pathway information (a model of how molecules interact within a cell) from databases such as KEGG and WikiPathways are available in a standard RDF-based format BioPAX. However, these models are

Modeling of the bacterial mechanism of methicillin-resistance by a systems biology approach.

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Ida Autiero

Full Text Available BACKGROUND: A microorganism is a complex biological system able to preserve its functional features against external perturbations and the ability of the living systems to oppose to these external perturbations is defined "robustness". The antibiotic resistance, developed by different bacteria strains, is a clear example of robustness and of ability of the bacterial system to acquire a particular functional behaviour in response to environmental changes. In this work we have modeled the whole mechanism essential to the methicillin-resistance through a systems biology approach. The methicillin is a beta-lactamic antibiotic that act by inhibiting the penicillin-binding proteins (PBPs. These PBPs are involved in the synthesis of peptidoglycans, essential mesh-like polymers that surround cellular enzymes and are crucial for the bacterium survival. METHODOLOGY: The network of genes, mRNA, proteins and metabolites was created using CellDesigner program and the data of molecular interactions are stored in Systems Biology Markup Language (SBML. To simulate the dynamic behaviour of this biochemical network, the kinetic equations were associated with each reaction. CONCLUSIONS: Our model simulates the mechanism of the inactivation of the PBP by methicillin, as well as the expression of PBP2a isoform, the regulation of the SCCmec elements (SCC: staphylococcal cassette chromosome and the synthesis of peptidoglycan by PBP2a. The obtained results by our integrated approach show that the model describes correctly the whole phenomenon of the methicillin resistance and is able to respond to the external perturbations in the same way of the real cell. Therefore, this model can be useful to develop new therapeutic approaches for the methicillin control and to understand the general mechanism regarding the cellular resistance to some antibiotics.

Augmenting Plant Immune Responses and Biological Control by Microbial Determinants

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Sang Moo Lee

2015-09-01

Full Text Available Plant have developed sophisticated defence mechanisms against microbial pathogens. The recent accumulated information allow us to understand the nature of plant immune responses followed by recognition of microbial factors/determinants through cutting-edge genomics and multi-omics techniques. However, the practical approaches to sustain plant health using enhancement of plant immunity is yet to be fully appreciated. Here, we overviewed the general concept and representative examples on the plant immunity. The fungal, bacterial, and viral determinants that was previously reported as the triggers of plant immune responses are introduced and described as the potential protocol of biological control. Specifically, the role of chitin, glucan, lipopolysaccharides/extracellular polysaccharides, microbe/pathogen-associated molecular pattern, antibiotics, mimic-phytohormones, N-acyl homoserine lactone, harpin, vitamins, and volatile organic compounds are considered. We hope that this review stimulates scientific community and farmers to broaden their knowledge on the microbial determinant-based biological control and to apply the technology on the integrated pest management program.

Causal biological network database: a comprehensive platform of causal biological network models focused on the pulmonary and vascular systems.

Science.gov (United States)

Boué, Stéphanie; Talikka, Marja; Westra, Jurjen Willem; Hayes, William; Di Fabio, Anselmo; Park, Jennifer; Schlage, Walter K; Sewer, Alain; Fields, Brett; Ansari, Sam; Martin, Florian; Veljkovic, Emilija; Kenney, Renee; Peitsch, Manuel C; Hoeng, Julia

2015-01-01

With the wealth of publications and data available, powerful and transparent computational approaches are required to represent measured data and scientific knowledge in a computable and searchable format. We developed a set of biological network models, scripted in the Biological Expression Language, that reflect causal signaling pathways across a wide range of biological processes, including cell fate, cell stress, cell proliferation, inflammation, tissue repair and angiogenesis in the pulmonary and cardiovascular context. This comprehensive collection of networks is now freely available to the scientific community in a centralized web-based repository, the Causal Biological Network database, which is composed of over 120 manually curated and well annotated biological network models and can be accessed at http://causalbionet.com. The website accesses a MongoDB, which stores all versions of the networks as JSON objects and allows users to search for genes, proteins, biological processes, small molecules and keywords in the network descriptions to retrieve biological networks of interest. The content of the networks can be visualized and browsed. Nodes and edges can be filtered and all supporting evidence for the edges can be browsed and is linked to the original articles in PubMed. Moreover, networks may be downloaded for further visualization and evaluation. Database URL: http://causalbionet.com © The Author(s) 2015. Published by Oxford University Press.

Do biological-based strategies hold promise to biofouling control in MBRs?

KAUST Repository

Malaeb, Lilian; Le-Clech, Pierre; Vrouwenvelder, Johannes S.; Ayoub, George M.; Saikaly, Pascal

2013-01-01

. The reason for the slow advancement in successful control of biofouling is largely attributed to the complex interactions of involved biological compounds and the lack of representative-for-practice experimental approaches to evaluate potential effective

Achilles and the tortoise: Some caveats to mathematical modeling in biology.

Science.gov (United States)

Gilbert, Scott F

2018-01-31

Mathematical modeling has recently become a much-lauded enterprise, and many funding agencies seek to prioritize this endeavor. However, there are certain dangers associated with mathematical modeling, and knowledge of these pitfalls should also be part of a biologist's training in this set of techniques. (1) Mathematical models are limited by known science; (2) Mathematical models can tell what can happen, but not what did happen; (3) A model does not have to conform to reality, even if it is logically consistent; (4) Models abstract from reality, and sometimes what they eliminate is critically important; (5) Mathematics can present a Platonic ideal to which biologically organized matter strives, rather than a trial-and-error bumbling through evolutionary processes. This "Unity of Science" approach, which sees biology as the lowest physical science and mathematics as the highest science, is part of a Western belief system, often called the Great Chain of Being (or Scala Natura), that sees knowledge emerge as one passes from biology to chemistry to physics to mathematics, in an ascending progression of reason being purification from matter. This is also an informal model for the emergence of new life. There are now other informal models for integrating development and evolution, but each has its limitations. Copyright © 2018 Elsevier Ltd. All rights reserved.

Information-theoretic analysis of the dynamics of an executable biological model.

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Avital Sadot

Full Text Available To facilitate analysis and understanding of biological systems, large-scale data are often integrated into models using a variety of mathematical and computational approaches. Such models describe the dynamics of the biological system and can be used to study the changes in the state of the system over time. For many model classes, such as discrete or continuous dynamical systems, there exist appropriate frameworks and tools for analyzing system dynamics. However, the heterogeneous information that encodes and bridges molecular and cellular dynamics, inherent to fine-grained molecular simulation models, presents significant challenges to the study of system dynamics. In this paper, we present an algorithmic information theory based approach for the analysis and interpretation of the dynamics of such executable models of biological systems. We apply a normalized compression distance (NCD analysis to the state representations of a model that simulates the immune decision making and immune cell behavior. We show that this analysis successfully captures the essential information in the dynamics of the system, which results from a variety of events including proliferation, differentiation, or perturbations such as gene knock-outs. We demonstrate that this approach can be used for the analysis of executable models, regardless of the modeling framework, and for making experimentally quantifiable predictions.

Assessing the status of biological control as a management tool for suppression of invasive alien plants in South Africa

OpenAIRE

Zachariades, Costas; Paterson, Iain D.; Strathie, Lorraine W.; Hill, Martin P.; van Wilgen, Brian W.

2017-01-01

Background: Biological control of invasive alien plants (IAPs) using introduced natural enemies contributes significantly to sustained, cost-effective management of natural resources in South Africa. The status of, and prospects for, biological control is therefore integral to National Status Reports (NSRs) on Biological Invasions, the first of which is due in 2017. Objectives: Our aim was to evaluate the status of, and prospects for, biological control of IAPs in South Africa. We discuss...

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…

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.

Biological control agent for mosquito larvae: Review on the killifish ...

African Journals Online (AJOL)

This review attempts to give an account on the recent advances on the killifish Aphanius dispar dispar as a biological control agent for mosquito larvae. Thirty six (36) articles of literature (scientific papers, technical and workshop reports) on this subject covering the period between 1980 and 2009 were reviewed.

Biological effects of low-dose ionizing radiation exposure

International Nuclear Information System (INIS)

Reinoehl-Kompa, Sabine; Baldauf, Daniela; Heller, Horst

2009-01-01

The report on the meeting of the Strahlenschutzkommission 2007 concerning biological effects of low-dose ionizing radiation exposure includes the following contributions: Adaptive response. The importance of DNA damage mechanisms for the biological efficiency of low-energy photons. Radiation effects in mammography: the relative biological radiation effects of low-energy photons. Radiation-induced cataracts. Carcinomas following prenatal radiation exposure. Intercellular apoptosis induction and low-dose irradiation: possible consequences for the oncogenesis control. Mechanistic models for the carcinogenesis with radiation-induced cell inactivation: application to all solid tumors in the Japanese atomic bomb survivors. Microarrays at low radiation doses. Mouse models for the analysis of biological effects of low-dose ionizing radiation. The bystander effect: observations, mechanisms and implications. Lung carcinoma risk of Majak workers - modeling of carcinogenesis and the bystander effect. Microbeam studies in radiation biology - an overview. Carcinogenesis models with radiation-induced genomic instability. Application to two epidemiological cohorts.

Reevaluation of the value of autoparasitoids in biological control.

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Lian-Sheng Zang

Full Text Available Autoparasitoids with the capacity of consuming primary parasitoids that share the same hosts to produce males are analogous to intraguild predators. The use of autoparasitoids in biological control programs is a controversial matter because there is little evidence to support the view that autoparasitoids do not disrupt and at times may promote suppression of insect pests in combination with primary parasitoids. We found that Encarsia sophia, a facultative autoparasitoid, preferred to use heterospecific hosts as secondary hosts for producing males. The autoparasitoids mated with males originated from heterospecifics may parasitize more hosts than those mated with males from conspecifics. Provided with an adequate number of males, the autoparasitoids killed more hosts than En. formosa, a commonly used parasitoid for biological control of whiteflies. This study supports the view that autoparasitoids in combination with primary parasitoids do not disrupt pest management and may enhance such programs. The demonstrated preference of an autoparasitoid for heterospecifics and improved performance of males from heterospecifics observed in this study suggests these criteria should be considered in strategies that endeavor to mass-produce and utilize autoparasitoids in the future.

Biological control agents for suppression of post-harvest diseases of potatoes: strategies on discovery and development

Science.gov (United States)

As used in plant pathology, the term "biological control" or its short form “biocontrol” commonly refers to the decrease in the inoculum or the disease-producing activity of a pathogen accomplished through one or more organisms, including the host plant but excluding man. Biological control of plant...

A Conceptual Model to Identify Intent to Use Chemical-Biological Weapons

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Mary Zalesny

2017-10-01

Full Text Available This paper describes a conceptual model to identify and interrelate indicators of intent of non-state actors to use chemical or biological weapons. The model expands on earlier efforts to understand intent to use weapons of mass destruction by building upon well-researched theories of intent and behavior and focusing on a sub-set of weapons of mass destruction (WMD to account for the distinct challenges of employing different types of WMD in violent acts. The conceptual model is presented as a first, critical step in developing a computational model for assessing the potential for groups to use chemical or biological weapons.

Biology and Water Pollution Control.

Science.gov (United States)

Warren, Charles E.

Within this text, the reader is attuned to the role biology can and should play in combating the alarming increase in water pollution. Both the urgency of the problem and the biological techniques that are being developed to cope with the water pollution crisis are scrutinized; what is and is not known about the problem is explained; past,…

Defining and detecting structural sensitivity in biological models: developing a new framework.

Science.gov (United States)

Adamson, M W; Morozov, A Yu

2014-12-01

When we construct mathematical models to represent biological systems, there is always uncertainty with regards to the model specification--whether with respect to the parameters or to the formulation of model functions. Sometimes choosing two different functions with close shapes in a model can result in substantially different model predictions: a phenomenon known in the literature as structural sensitivity, which is a significant obstacle to improving the predictive power of biological models. In this paper, we revisit the general definition of structural sensitivity, compare several more specific definitions and discuss their usefulness for the construction and analysis of biological models. Then we propose a general approach to reveal structural sensitivity with regards to certain system properties, which considers infinite-dimensional neighbourhoods of the model functions: a far more powerful technique than the conventional approach of varying parameters for a fixed functional form. In particular, we suggest a rigorous method to unearth sensitivity with respect to the local stability of systems' equilibrium points. We present a method for specifying the neighbourhood of a general unknown function with [Formula: see text] inflection points in terms of a finite number of local function properties, and provide a rigorous proof of its completeness. Using this powerful result, we implement our method to explore sensitivity in several well-known multicomponent ecological models and demonstrate the existence of structural sensitivity in these models. Finally, we argue that structural sensitivity is an important intrinsic property of biological models, and a direct consequence of the complexity of the underlying real systems.

Three-dimensional models of cancer for pharmacology and cancer cell biology: capturing tumor complexity in vitro/ex vivo.

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Hickman, John A; Graeser, Ralph; de Hoogt, Ronald; Vidic, Suzana; Brito, Catarina; Gutekunst, Matthias; van der Kuip, Heiko

2014-09-01

Cancers are complex and heterogeneous pathological "organs" in a dynamic interplay with their host. Models of human cancer in vitro, used in cancer biology and drug discovery, are generally highly reductionist. These cancer models do not incorporate complexity or heterogeneity. This raises the question as to whether the cancer models' biochemical circuitry (not their genome) represents, with sufficient fidelity, a tumor in situ. Around 95% of new anticancer drugs eventually fail in clinical trial, despite robust indications of activity in existing in vitro pre-clinical models. Innovative models are required that better capture tumor biology. An important feature of all tissues, and tumors, is that cells grow in three dimensions. Advances in generating and characterizing simple and complex (with added stromal components) three-dimensional in vitro models (3D models) are reviewed in this article. The application of stirred bioreactors to permit both scale-up/scale-down of these cancer models and, importantly, methods to permit controlled changes in environment (pH, nutrients, and oxygen) are also described. The challenges of generating thin tumor slices, their utility, and potential advantages and disadvantages are discussed. These in vitro/ex vivo models represent a distinct move to capture the realities of tumor biology in situ, but significant characterization work still remains to be done in order to show that their biochemical circuitry accurately reflects that of a tumor. Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

Biologically Inspired Modular Neural Control for a Leg-Wheel Hybrid Robot

DEFF Research Database (Denmark)

Manoonpong, Poramate; Wörgötter, Florentin; Laksanacharoen, Pudit

2014-01-01

In this article we present modular neural control for a leg-wheel hybrid robot consisting of three legs with omnidirectional wheels. This neural control has four main modules having their functional origin in biological neural systems. A minimal recurrent control (MRC) module is for sensory signal...... processing and state memorization. Its outputs drive two front wheels while the rear wheel is controlled through a velocity regulating network (VRN) module. In parallel, a neural oscillator network module serves as a central pattern generator (CPG) controls leg movements for sidestepping. Stepping directions...... or they can serve as useful modules for other module-based neural control applications....

Micrasterias as a model system in plant cell biology

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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.

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......, anaerobic digestion and combinations hereof are available in the model, but the user can change all key parameters in the biological treatment module so that specific local plants and processes can be modelled. EASEWASTE is one of the newest waste LCA models and the biological treatment module was built...... partly on features of earlier waste-LCA models, but offers additional facilities, more flexibility, transparency and user-friendliness. The paper presents the main features of the module and provides some examples illustrating the capability of the model in environmentally assessing and discriminating...

SBRML: a markup language for associating systems biology data with models.

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Dada, Joseph O; Spasić, Irena; Paton, Norman W; Mendes, Pedro

2010-04-01

Research in systems biology is carried out through a combination of experiments and models. Several data standards have been adopted for representing models (Systems Biology Markup Language) and various types of relevant experimental data (such as FuGE and those of the Proteomics Standards Initiative). However, until now, there has been no standard way to associate a model and its entities to the corresponding datasets, or vice versa. Such a standard would provide a means to represent computational simulation results as well as to frame experimental data in the context of a particular model. Target applications include model-driven data analysis, parameter estimation, and sharing and archiving model simulations. We propose the Systems Biology Results Markup Language (SBRML), an XML-based language that associates a model with several datasets. Each dataset is represented as a series of values associated with model variables, and their corresponding parameter values. SBRML provides a flexible way of indexing the results to model parameter values, which supports both spreadsheet-like data and multidimensional data cubes. We present and discuss several examples of SBRML usage in applications such as enzyme kinetics, microarray gene expression and various types of simulation results. The XML Schema file for SBRML is available at http://www.comp-sys-bio.org/SBRML under the Academic Free License (AFL) v3.0.

Fuzzy logic for plant-wide control of biological wastewater treatment process including greenhouse gas emissions.

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Santín, I; Barbu, M; Pedret, C; Vilanova, R

2018-06-01

The application of control strategies is increasingly used in wastewater treatment plants with the aim of improving effluent quality and reducing operating costs. Due to concerns about the progressive growth of greenhouse gas emissions (GHG), these are also currently being evaluated in wastewater treatment plants. The present article proposes a fuzzy controller for plant-wide control of the biological wastewater treatment process. Its design is based on 14 inputs and 6 outputs in order to reduce GHG emissions, nutrient concentration in the effluent and operational costs. The article explains and shows the effect of each one of the inputs and outputs of the fuzzy controller, as well as the relationship between them. Benchmark Simulation Model no 2 Gas is used for testing the proposed control strategy. The results of simulation results show that the fuzzy controller is able to reduce GHG emissions while improving, at the same time, the common criteria of effluent quality and operational costs. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Studies on bacterial flora and biological control agent of Cydia ...

African Journals Online (AJOL)

In the present study, in order to find a more effective and safe biological control agent against Cydia pomonella, we investigated the bacterial flora and tested them for insecticidal effects on this insect. According to morphological, physiological and biochemical tests, bacterial flora were identified as Proteus rettgeri (Cp1), ...

The perception of corn farmers about biological control of Caradrina ...

African Journals Online (AJOL)

The purpose of this study was to analyze the perception of corn farmers about biological control of Caradrina by Braconid in Dezful Township, Khouzestan Province, Iran. The method used in this study was correlative descriptive and causal relation. A random sample of Dezful township corn farmers of Khouzestan Province, ...

Evaluation of biologic occupational risk control practices: quality indicators development and validation.

Science.gov (United States)

Takahashi, Renata Ferreira; Gryschek, Anna Luíza F P L; Izumi Nichiata, Lúcia Yasuko; Lacerda, Rúbia Aparecida; Ciosak, Suely Itsuko; Gir, Elucir; Padoveze, Maria Clara

2010-05-01

There is growing demand for the adoption of qualification systems for health care practices. This study is aimed at describing the development and validation of indicators for evaluation of biologic occupational risk control programs. The study involved 3 stages: (1) setting up a research team, (2) development of indicators, and (3) validation of the indicators by a team of specialists recruited to validate each attribute of the developed indicators. The content validation method was used for the validation, and a psychometric scale was developed for the specialists' assessment. A consensus technique was used, and every attribute that obtained a Content Validity Index of at least 0.75 was approved. Eight indicators were developed for the evaluation of the biologic occupational risk prevention program, with emphasis on accidents caused by sharp instruments and occupational tuberculosis prevention. The indicators included evaluation of the structure, process, and results at the prevention and biologic risk control levels. The majority of indicators achieved a favorable consensus regarding all validated attributes. The developed indicators were considered validated, and the method used for construction and validation proved to be effective. Copyright (c) 2010 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Mosby, Inc. All rights reserved.

Modeling of various contact theories for the manipulation of different biological micro/nanoparticles based on AFM

Science.gov (United States)

Korayem, M. H.; Taheri, M.

2014-01-01

In this article, the modeling of various contact theories to be applied in the biomanipulation of different micro/nanoparticles based on the atomic force microscope has been studied, and the effect of adhesion force in different contact models on indentation depth and contact angle between tip and substrate has been explored for the target biological micro/nanoparticle. The contact models used in this research include the Hertz, JKR, DMT, BCP, COS, PT, and the SUN models. Also, the target particles comprise the biological micro/nanoparticles of DNA, yeast, platelet, and nanobacterium. Previous research works have investigated the contact models for the manipulation of non-biological gold micro/nanoparticles in the air environment. Since in a real biomanipulation situation, the biological micro/nanoparticles are displaced in biological environments; in this article, various contact theories for the biomanipulation of biological micro/nanoparticles in different biological environments have been modeled and compared for the first time. The results of modeling indicate that the use of Hertz contact model in analyzing the biomanipulation of biological nanoparticles is not appropriate, because it does not take the adhesion force into consideration and thus produces a significant error. Also, all the six contact models developed in this article show larger deformations for studied bionanoparticles in comparison to the gold nanoparticles, which can be justified with regards to the mechanical properties of gold.

Modeling the Biological Diversity of Pig Carcasses

DEFF Research Database (Denmark)

Erbou, Søren Gylling Hemmingsen

This thesis applies methods from medical image analysis for modeling the biological diversity of pig carcasses. The Danish meat industry is very focused on improving product quality and productivity by optimizing the use of the carcasses and increasing productivity in the abattoirs. In order...... equipment is investigated, without the need for a calibration against a less accurate manual dissection. The rest of the contributions regard the construction and use of point distribution models (PDM). PDM’s are able to capture the shape variation of a population of shapes, in this case a 3D surface...

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

The increased availability of high-resolution ocean data globally has enabled more detailed analyses of physical-biological interactions and their consequences to the ecosystem. We present IBMlib, which is a versatile, portable and computationally effective framework for conducting Lagrangian...... scales. The open-source framework features a minimal robust interface to facilitate the coupling between individual-level biological models and oceanographic models, and we provide application examples including forward/backward simulations, habitat connectivity calculations, assessing ocean conditions...

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

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.

The role and control of sludge age in biological nutrient removal activated sludge systems.

Science.gov (United States)

Ekama, G A

2010-01-01

The sludge age is the most fundamental and important parameter in the design, operation and control of biological nutrient removal (BNR) activated sludge (AS) systems. Generally, the better the effluent and waste sludge quality required from the system, the longer the sludge age, the larger the biological reactor and the more wastewater characteristics need to be known. Controlling the reactor concentration does not control sludge age, only the mass of sludge in the system. When nitrification is a requirement, sludge age control becomes a requirement and the secondary settling tanks can no longer serve the dual purpose of clarifier and waste activated sludge thickeners. The easiest and most practical way to control sludge age is with hydraulic control by wasting a defined proportion of the reactor volume daily. In AS plants with reactor concentration control, nitrification fails first. With hydraulic control of sludge age, nitrification will not fail, rather the plant fails by shedding solids over the secondary settling tank effluent weirs.

Beware the tail that wags the dog: informal and formal models in biology.

Science.gov (United States)

Gunawardena, Jeremy

2014-11-05

Informal models have always been used in biology to guide thinking and devise experiments. In recent years, formal mathematical models have also been widely introduced. It is sometimes suggested that formal models are inherently superior to informal ones and that biology should develop along the lines of physics or economics by replacing the latter with the former. Here I suggest to the contrary that progress in biology requires a better integration of the formal with the informal. © 2014 Gunawardena. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication 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).

Differential physiological responses of dalmatian toadflax, Linaria dalmatica L. Miller, to injury from two insect biological control agents: Implications for decision-making in biological control

Science.gov (United States)

Robert K. D. Peterson; Sharlene E. Sing; David K. Weaver

2005-01-01

Successful biological control of invasive weeds with specialist herbivorous insects is predicated on the assumption that the injury stresses the weeds sufficiently to cause reductions in individual fitness. Because plant gas exchange directly impacts growth and fitness, characterizing how injury affects these primary processes may provide a key indicator of...

Dynamical compensation and structural identifiability of biological models: Analysis, implications, and reconciliation.

Science.gov (United States)

Villaverde, Alejandro F; Banga, Julio R

2017-11-01

The concept of dynamical compensation has been recently introduced to describe the ability of a biological system to keep its output dynamics unchanged in the face of varying parameters. However, the original definition of dynamical compensation amounts to lack of structural identifiability. This is relevant if model parameters need to be estimated, as is often the case in biological modelling. Care should we taken when using an unidentifiable model to extract biological insight: the estimated values of structurally unidentifiable parameters are meaningless, and model predictions about unmeasured state variables can be wrong. Taking this into account, we explore alternative definitions of dynamical compensation that do not necessarily imply structural unidentifiability. Accordingly, we show different ways in which a model can be made identifiable while exhibiting dynamical compensation. Our analyses enable the use of the new concept of dynamical compensation in the context of parameter identification, and reconcile it with the desirable property of structural identifiability.

The choice of a biological model in assessing internal dose equivalent

International Nuclear Information System (INIS)

Parodo, A.; Erre, N.

1977-01-01

Many are the biological models related to kinetic behavior of radioactive materials within the organism, or in an organ. This is true particularly for the metabolic kinetics of bone-seekers radionuclides described differently by various authors: as a consequence, different forms of the retention function have been used in calculating internal dose equivalent. In our opinion, the retention functions expressed as linear combinations of exponential terms with negative exponents are preferable. In fact, they can be obtained by coherent compartmental analysis and allow a mathematical formalism fairly well definite and easily adaptable to computers. Moreover, it is possible to make use of graphs and monograms already published. The role of the biological model in internal dosimetry, referred to the reliability of the quantitative informations on the kinetic behavior of the radionuclides in the organism and, therefrom, to the accuracy of the doses calculated, is discussed. By comparing the results obtained with different biological models, one finds that the choice of a model is less important than the choice of the value of the appropriate parameters

Converting differential-equation models of biological systems to membrane computing.

Science.gov (United States)

Muniyandi, Ravie Chandren; Zin, Abdullah Mohd; Sanders, J W

2013-12-01

This paper presents a method to convert the deterministic, continuous representation of a biological system by ordinary differential equations into a non-deterministic, discrete membrane computation. The dynamics of the membrane computation is governed by rewrite rules operating at certain rates. That has the advantage of applying accurately to small systems, and to expressing rates of change that are determined locally, by region, but not necessary globally. Such spatial information augments the standard differentiable approach to provide a more realistic model. A biological case study of the ligand-receptor network of protein TGF-β is used to validate the effectiveness of the conversion method. It demonstrates the sense in which the behaviours and properties of the system are better preserved in the membrane computing model, suggesting that the proposed conversion method may prove useful for biological systems in particular. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

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.

Biological Efficacy of Herbicides for Weed Control in Noncropped Areas

Directory of Open Access Journals (Sweden)