Modelling protein localisation and positional information in subcellular systems

Cells and their component structures are highly organised. The correct function of many biological systems relies upon not only temporal control of protein levels but also spatial control of protein localisation within cells. Mathematical modelling allows us to quantitatively test potential mechanisms for protein localisation and spatial organisation. Here we present models of three examples of spatial organisation within individual cells. In the bacterium E. coli, the site of cell division is partly determined by the Min proteins. The Min proteins oscillate between the cell poles and suppress formation of the division ring here, thereby restricting division to midcell. We present a stochastic model of the Min protein dynamics, and use this model to investigate partitioning of the Min proteins between the daughter cells during cell division. The Min proteins determine the correct position for cell division by forming a timeaveraged concentration gradient which is minimal at midcell. Concentration gradients are involved in a range of subcellular processes, and are particularly important for obtaining positional information. By analysing the low copy number spatiotemporal uctuations in protein concentrations for a single polar gradient and two oppositelydirected gradients, we estimate the positional precision that can be achieved in vivo. We nd that time-averaging is vital for high precision. The embryo of the nematode C. elegans has become a model system for the study of cell polarity. At the one-cell stage, the PAR proteins form anterior and posterior domains in a dynamic process driven by contraction of cortical actomyosin. We present a continuum model for this system, including a highly simpli ed model of the actomyosin dynamics. Our model suggests that the known PAR protein interactions 5 are insu cient to explain the experimentally observed cytoplasmic polarity. We discuss a number of modi cations to the model which reproduce the correct cytoplasmic distributions

Principles and Concepts of Agent-Based Modelling for Developing Geospatial Simulations

The aim of this paper is to outline fundamental concepts and principles of the Agent-Based Modelling (ABM) paradigm, with particular reference to the development of geospatial simulations. The paper begins with a brief definition of modelling, followed by a classification of model types, and a comment regarding a shift (in certain circumstances) towards modelling systems at the individual-level. In particular, automata approaches (e.g. Cellular Automata, CA, and ABM) have been particularly popular, with ABM moving to the fore. A definition of agents and agent-based models is given; identifying their advantages and disadvantages, especially in relation to geospatial modelling. The potential use of agent-based models is discussed, and how-to instructions for developing an agent-based model are provided. Types of simulation / modelling systems available for ABM are defined, supplemented with criteria to consider before choosing a particular system for a modelling endeavour. Information pertaining to a selection of simulation / modelling systems (Swarm, MASON, Repast, StarLogo, NetLogo, OBEUS, AgentSheets and AnyLogic) is provided, categorised by their licensing policy (open source, shareware / freeware and proprietary systems). The evaluation (i.e. verification, calibration, validation and analysis) of agent-based models and their output is examined, and noteworthy applications are discussed.Geographical Information Systems (GIS) are a particularly useful medium for representing model input and output of a geospatial nature. However, GIS are not well suited to dynamic modelling (e.g. ABM). In particular, problems of representing time and change within GIS are highlighted. Consequently, this paper explores the opportunity of linking (through coupling or integration / embedding) a GIS with a simulation / modelling system purposely built, and therefore better suited to supporting the requirements of ABM. This paper concludes with a synthesis of the discussion that has proceeded. The aim of this paper is to outline fundamental concepts and principles of the Agent-Based Modelling (ABM) paradigm, with particular reference to the development of geospatial simulations. The paper begins with a brief definition of modelling, followed by a classification of model types, and a comment regarding a shift (in certain circumstances) towards modelling systems at the individual-level. In particular, automata approaches (e.g. Cellular Automata, CA, and ABM) have been particularly popular, with ABM moving to the fore. A definition of agents and agent-based models is given; identifying their advantages and disadvantages, especially in relation to geospatial modelling. The potential use of agent-based models is discussed, and how-to instructions for developing an agent-based model are provided. Types of simulation / modelling systems available for ABM are defined, supplemented with criteria to consider before choosing a particular system for a modelling endeavour. Information pertaining to a selection of simulation / modelling systems (Swarm, MASON, Repast, StarLogo, NetLogo, OBEUS, AgentSheets and AnyLogic) is provided, categorised by their licensing policy (open source, shareware / freeware and proprietary systems). The evaluation (i.e. verification, calibration, validation and analysis) of agent-based models and their output is examined, and noteworthy applications are discussed.Geographical Information Systems (GIS) are a particularly useful medium for representing model input and output of a geospatial nature. However, GIS are not well suited to dynamic modelling (e.g. ABM). In particular, problems of representing time and change within GIS are highlighted. Consequently, this paper explores the opportunity of linking (through coupling or integration / embedding) a GIS with a simulation / modelling system purposely built, and therefore better suited to supporting the requirements of ABM. This paper concludes with a synthesis of the discussion that has proceeded

Model-driven design of geo-information services

This thesis presents a method for the development of distributed geo-information systems. The method is organised around the design principles of modularity, reuse and replaceability. The method enables the modelling of both behavioural and informational aspects of geo-information systems in an integrated way. This thesis introduces the concept the Geo-information Service Infrastructure (GSI)

Modelling of a Flexible Manoeuvring System Using ANFIS Techniques

The increased utilization of flexible structure systems, such as flexible manipulators and flexible aircraft in various applications, has been motivated by the requirements of industrial automation in recent years. Robust optimal control of flexible structures with active feedback techniques requires accurate models of the base structure, and knowledge of uncertainties of these models. Such information may not be easy to acquire for certain systems. An adaptive Neuro-Fuzzy inference Systems (ANFIS) use the learning ability of neural networks to adjust the membership function parameters in a fuzzy inference system. Hence, modelling using ANFIS is preferred in such applications. This paper discusses modelling of a nonlinear flexible system namely a twin rotor multi-input multi-output system using ANFIS techniques. Pitch and yaw motions are modelled and tested by model validation techniques. The obtained results indicate that ANFIS modelling is powerful to facilitate modelling of complex systems associated with nonlinearity and uncertainty

Enterprise Information Systems and Business Process Modelling in Training and Research

The University of Debrecen introduced the five year “informatics agricultural engineer” course in the 2002/2003 academic year. In the 2006/2007 the „informatics and agricultural administration engineer“ BSc course has been introduced. The courses are run by the Agricultural Economics and Rural Development faculty. Starting of this course is demanded by the Hungarian agro-food sector, Governmental offices, Institutes, which need the applications of wide range informatics tools and systems. The business process modelling and management is becoming important part of implementing and running information systems. The ARIS is one of the leader products in modelling. The other important system is the SAP in the ERP market. In our education program we are using these products. The ARIS toolset is very useful for research on business modelling in agri-food companies too

Business Domain Modelling using an Integrated Framework

This paper presents an application of a “Systematic Soft Domain Driven Design Framework” as a soft systems approach to domain-driven design of information systems development. The framework combining techniques from Soft Systems Methodology (SSM), the Unified Modelling Language (UML), and an implementation pattern known as “Naked Objects”. This framework have been used in action research projects that have involved the investigation and modelling of business processes using object-oriented domain models and the implementation of software systems based on those domain models. Within this framework, Soft Systems Methodology (SSM) is used as a guiding methodology to explore the problem situation and to develop the domain model using UML for the given business domain. The framework is proposed and evaluated in our previous works, and a real case study “Information Retrieval System for academic research” is used, in this paper, to show further practice and evaluation of the framework in different business domain. We argue that there are advantages from combining and using techniques from different methodologies in this way for business domain modelling. The framework is overviewed and justified as multimethodology using Mingers multimethodology ideas

Qualitative modelling and analysis of regulations in multi-cellular systems using Petri nets and topological collections

In this paper, we aim at modelling and analyzing the regulation processes in multi-cellular biological systems, in particular tissues. The modelling framework is based on interconnected logical regulatory networks a la Rene Thomas equipped with information about their spatial relationships. The semantics of such models is expressed through colored Petri nets to implement regulation rules, combined with topological collections to implement the spatial information. Some constraints are put on the the representation of spatial information in order to preserve the possibility of an enumerative and exhaustive state space exploration. This paper presents the modelling framework, its semantics, as well as a prototype implementation that allowed preliminary experimentation on some applications.Comment: In Proceedings MeCBIC 2010, arXiv:1011.005

A methodological proposal and tool support for the HL7 standards compliance in the development of health information systems

Health information systems are increasingly complex, and their development is presented as a challenge for software development companies offering quality, maintainable and interoperable products. HL7 (Health level 7) International, an international non-profit organization, defines and maintains standards related to health information systems. However, the modelling languages proposed by HL7 are far removed from standard languages and widely known by software engineers. In these lines, NDT is a software development methodology that has a support tool called NDT-Suite and is based, on the one hand, on the paradigm of model-driven engineering and, on the other hand, in UML that is a widely recognized standard language. This paper proposes an extension of the NDT methodology called MoDHE (Model Driven Health Engineering) to offer software engineers a methodology capable of modelling health information systems conforming to HL7 using UML domain models

Framework to Enhance Teaching and Learning in System Analysis and Unified Modelling Language

Cowling, MA ORCiD: 0000-0003-1444-1563; Munoz Carpio, JC ORCiD: 0000-0003-0251-5510Systems Analysis modelling is considered foundational for Information and Communication Technology (ICT) students, with introductory and advanced units included in nearly all ICT and computer science degrees. Yet despite this, novice systems analysts (learners) find modelling and systems thinking quite difficult to learn and master. This makes the process of teaching the fundamentals frustrating and time intensive. This paper will discuss the foundational problems that learners face when learning Systems Analysis modelling. Through a systematic literature review, a framework will be proposed based on the key problems that novice learners experience. In this proposed framework, a sequence of activities has been developed to facilitate understanding of the requirements, solutions and incremental modelling. An example is provided illustrating how the framework could be used to incorporate visualization and gaming elements into a Systems Analysis classroom; therefore, improving motivation and learning. Through this work, a greater understanding of the approach to teaching modelling within the computer science classroom will be provided, as well as a framework to guide future teaching activities