Identification of all steady states in large networks by logical analysis

The goal of generalized logical analysis is to model complex biological systems, especially so-called regulatory systems, such as genetic networks. This theory is mainly characterized by its capacity to find all the steady states of a given system and the functional positive and negative circuits, which generate multistationarity and a cycle in the state sequence graph, respectively. So far, this has been achieved by exhaustive enumeration, which severely limits the size of the systems that can be analysed. In this paper, we introduce a mathematical function, called image function, which allows the calculation of the value of the logical parameter associated with a logical variable depending on the state of the system. Thus the state table of the system is represented analytically. We then show how all steady states can be derived as solutions to a system of steady-state equations. Constraint programming, a recent method for solving constraint satisfaction problems, is applied for that purpose. To illustrate the potential of our approach, we present results from computer experiments carried out on very large randomly-generated systems (graphs) with hundreds, or even thousands, of interacting components, and show that these systems can be solved using moderate computing time. Moreover, we illustrate the approach through two published applications, one of which concerns the computation times of all steady states for a large genetic network.     

Towards computing with proteins

Can proteins be used as computational devices to address difficult computational problems? In recent years there has been much interest in biological computing, that is, building a general purpose computer from biological molecules. Most of the current efforts are based on DNA because of its ability to self‐hybridize. The exquisite selectivity and specificity of complex protein‐based networks motivated us to suggest that similar principles can be used to devise biological systems that will be able to directly implement any logical circuit as a parallel asynchronous computation. Such devices, powered by ATP molecules, would be able to perform, for medical applications, digital computation with natural interface to biological input conditions. We discuss how to design protein molecules that would serve as the basic computational element by functioning as a NAND logical gate, utilizing DNA tags for recognition, and phosphorylation and exonuclease reactions for information processing. A solution of these elements could carry out effective computation. Finally, the model and its robustness to errors were tested in a computer simulation. Proteins 2006. © 2006 Wiley‐Liss, Inc.     

The universal fuzzy logical framework of neural circuits and its application in modeling primary visual cortex

Analytical study of large-scale nonlinear neural circuits is a difficult task. Here we analyze the function of neural systems by probing the fuzzy logical framework of the neural cells’ dynamical equations. Although there is a close relation between the theories of fuzzy logical systems and neural systems and many papers investigate this subject, most investigations focus on finding new functions of neural systems by hybridizing fuzzy logical and neural system. In this paper, the fuzzy logical framework of neural cells is used to understand the nonlinear dynamic attributes of a common neural system by abstracting the fuzzy logical framework of a neural cell. Our analysis enables the educated design of network models for classes of computation. As an example, a recurrent network model of the primary visual cortex has been built and tested using this approach.     

The universal fuzzy logical framework of neural cir-cuits and its application in modeling primary visual cortex

Analytical study of large-scale nonlinear neural circuits is a difficult task. Here we analyze the function of neural systems by probing the fuzzy logical framework of the neural cells' dynamical equations. Al- though there is a close relation between the theories of fuzzy logical systems and neural systems and many papers investigate this subject, most investigations focus on finding new functions of neural systems by hybridizing fuzzy logical and neural system. In this paper, the fuzzy logical framework of neural cells is used to understand the nonlinear dynamic attributes of a common neural system by abstracting the fuzzy logical framework of a neural cell. Our analysis enables the educated design of network models for classes of computation. As an example, a recurrent network model of the primary visual cortex has been built and tested using this approach.     

A New Design of Mental State Classification for Subject Independent BCI Systems

BackgroundBrain Computer Interface (BCI) systems have been widely used to develop sustainable assistive technology for people suffering from neurological impairments. A major limitation of current BCI systems is that they are based on Subject-dependent (SD) concept. The SD based BCI system is time consuming and inconvenient for physical or mental disables people and also not suitable for limited computer resources. In order to overcome these problems, recently subject-independent (SI) based BCI concept has been introduced to identify mental states of motor disabled people but the expected outcome of the SI based BCI has not been achieved yet. Hence this paper intends to present an efficient scheme for SI based BCI system. The goal of this research is to develop a method for classifying mental states which can be used by any user. For attaining this target, this study employs a supervised spatial filtering method with four types of feature extraction methods including Katz Fractal Dimension, Sub band Energy, Log Variance and Root Mean Square (RMS) and finally the obtained features are used as input to Linear Discriminant Analysis (LDA) classification model for identifying mental states for SI BCI system.ResultsThe performance of the proposed design is evaluated in several ways such as considering different time window length; different frequency bands; different number of channels. The mean classification accuracy using Katz feature is 84.35% which is the maximum output compare to other features that outperforms the existing methods.ConclusionsOur proposed design will help to make a new technology for development of real-time SI based BCI systems that can be more supportive for the motor disabled patients.     

The bacteriorhodopsin model membrane system as a prototype molecular computing element

The quest for more sophisticated integrated circuits to overcome the limitation of currently available silicon integrated circuits has led to the proposal of using biological molecules as computational elements by computer scientists and engineers. While the theoretical aspect of this possibility has been pursued by computer scientists, the research and development of experimental prototypes have not been pursued with an equal intensity. In this survey, we make an attempt to examine model membrane systems that incorporate the protein pigment bacteriorhodopsin which is found in Halobacterium halobium. This system was chosen for several reasons. The pigment/membrane system is sufficiently simple and stable for rigorous quantitative study, yet at the same time sufficiently complex in molecular structure to permit alteration of this structure in an attempt to manipulate the photosignal. Several methods of forming the pigment/membrane assembly are described and the potential application to biochip design is discussed. Experimental data using these membranes and measured by a tunable voltage clamp method are presented along with a theoretical analysis based on the Gouy-Chapman diffuse double layer theory to illustrate the usefulness of this approach. It is shown that detailed layouts of the pigment/membrane assembly as well as external loading conditions can modify the time course of the photosignal in a predictable manner. Some problems that may arise in the actual implementation and manufacturing, as well as the use of existing technology in protein chemistry, immunology, and recombinant DNA technology are discussed.     

A model management systems approach to manufacturing systems design

Manufacturing systems design involves the solution of a complex series of interrelated problems. This complexity will increase in the future as manufacturing practices change to meet increased global competition. Research within manufacturing systems design has mainly been focused on finding improved models for solving particular problems, or extending existing modeling techniques. This has resulted in numerous modeling tools being available to support manufacturing systems design. However, little research work has been carried out into consolidating the existing theories and models. As a result, a large body of this work has not been applied in industry. Model management has evolved as a research area which investigates methods for storing, modifying, and manipulating models. This article describes a prototype model management system for manufacturing systems design. The objective here is not to develop “another” decision support system for manufacturing design, but to illustrate, through the development of a prototype system, a number of key ideas of how concepts from the area of model management systems can be used to support manufacturing systems design. The prototype model management system utilizes the structured modeling framework and uses an extended version of the structured modeling language. An important aspect of the prototype model management system is the incorporation of the model development task, thus allowing the system to be easily updated and adapted. The prototype system was evaluated using a range of queueing network models for manufacturing systems design.     

Time course equations of the amount of substance in a linear compartmental system and their computerized derivation

In this contribution, we present the symbolic time course equations corresponding to a general model of a linear compartmental system, closed or open, with or without traps and with zero input. The steady state equations are obtained easily from the transient phase equations by setting the time --> infinity. Special attention has been given to the open systems, for which an exhaustive kinetic analysis has been developed to obtain important properties. Besides, the results have been particularized to open systems without traps and an alternative expression for the distribution function of exit times has been provided. We have implemented a versatile computer program, that is easy to use and with a user-friendly format of the input of data and the output of results. This computer program allows the user to obtain all the information necessary to derive the symbolic time course equations for closed or open systems as well as for the derivation of the distribution function of exit times.     

Stochastic computer model of cellular microtubule dynamics

A computer model of the system of microtubules has been developed to study the mechanisms of action of various factors on this system. The model describes the process of polymerization/depolymerization of microtubules as a set of chemical reactions with certain rate constants using a stochastic approach. Microtubules are visualized in the program field, which makes the model visual. The program imitates the dynamics and structure of the system of cellular microtubules with great, reliability. The parameters generated by the model correlate with the corresponding parameters of microtubules in living cells. We are going to develop this approach to modeling microtubules and similar structures to bring them into a better accord with living systems and to study the influence of various factors on these systems.     

Computer system for definition of the quantitative geometry of musculature from CT images

The computer system for quantitative determination of musculoskeletal geometry from computer tomography (CT) images has been developed. The computer system processes series of CT images to obtain three-dimensional (3D) model of bony structures where the effective muscle fibres can be interactively defined. Presented computer system has flexible modular structure and is suitable also for educational purposes.     

Mathematical formulation of Leibnizian world: a theory of individual-whole or interior-exterior reflective systems

A world model, suggested by Leibniz's monadology, is formulated as a mathematical axiomatic system. The purpose of this world model is to provide a general scheme for describing a system of individuals having consciousness or internal worlds that communicate with each other and make a unified whole world, and moreover, the latter is reflected into the respective internal worlds and appears as an external world. Examples of such monadological structure of interior-exterior (or individual-whole) reflection can be observed in bio- or socio-systems and recently in computer networks. Moreover, a most elemental version of this structure can be found in the basic level of quantum physics. The model not only gives a prototype of monadological systems but also has an evolutionary ability to produce a hierarchy of monadological systems, which are interpreted as corresponding to various levels of consciousness.     

Chemical reactions and membranes: A macroscopic basis for active transport II. Non-linear aspects

The physical principles that material and charge are conserved provide a basis for the design of a membrane capable of performing active ion transport in which the connection between “metabolic energy” input and the ion transport process itself is electrical rather than material. Molecular interactions between components in this system are irrelevant to its function. A second model built on the same principles performs active ion transport in a statically symmetrical membrane. The basis of its operation is a weakly stable unsymmetrical concentration profile arising from an enzyme-catalyzed reaction occurring within the membrane. The function of this membrane is irreversibly terminated (“killed”) by interference either with intramembrane concentration gradients or with the reactions which maintain them. Hence, any attempt to study this system by breaking it apart destroys the basis of its function. The existence of these models reveals the logical insufficiency of the molecular biologist's approach to understanding the basis of active transport: Neither the experimental techniques for structure determination (disruption, purification, characterization, and reconstitution) nor the fundamental question of that discipline (What is the molecular connection between &*|… ?) of the molecular biologist are applicable to the study or interpretation of these model systems. While the model systems are artificial, they incorporate only widely applicable concepts of physical chemistry and biochemical kinetics. The is no reason for excluding such mechanisms in natural membrane transport systems. If they are present, then more effective strategies of investigation will be required.     

A deductive database system PACADE for analyzing 3-D and secondary structures of protein

We have developed a deductive database system PACADE for analyzing3-D and secondary structures of protein. The PA CADE systemconsists of a relational database created from Protein DataBank and a deductive engine DEE based on logic programming.It has the following features: (1) The system has an inferencemechanism. This means by which users can easily write and checkbiological hypotheses using logical and declarative rules insteadof procedural programs. (2) The relational database of the PACADE system stores data on bath 3-D and secondwy structuresof protein. The integration of this two level structure makesfeasible an abstract representation of the protein structure.We describe herein the design, functions, and implementationof this PACADE system.     

Model for a population-based microbial oscillator

Genetic oscillators are a major theme of interest in the emerging field of synthetic biology. Until recently, most work has been carried out using intra-cellular oscillators, but this approach restricts the broader applicability of such systems. Motivated by a desire to develop large-scale, spatially distributed cell-based computational systems, we present an initial design for a population-level oscillator which uses three different bacterial strains. Our system is based on the client-server model familiar to computer science, and uses quorum sensing for communication between nodes. Importantly, it is robust to perturbation and noise. We present the results of extensive in silico simulation tests, which confirm the feasibility of our design.     

Improving the performance of I/O-intensive applications on clusters of workstations

Load balancing in a workstation-based cluster system has been investigated extensively, mainly focusing on the effective usage of global CPU and memory resources. However, if a significant portion of applications running in the system is I/O-intensive, traditional load balancing policies can cause system performance to decrease substantially. In this paper, two I/O-aware load-balancing schemes, referred to as IOCM and WAL-PM, are presented to improve the overall performance of a cluster system with a general and practical workload including I/O activities. The proposed schemes dynamically detect I/O load imbalance of nodes in a cluster, and determine whether to migrate some I/O load from overloaded nodes to other less- or under-loaded nodes. The current running jobs are eligible to be migrated in WAL-PM only if overall performance improves. Besides balancing I/O load, the scheme judiciously takes into account both CPU and memory load sharing in the system, thereby maintaining the same level of performance as existing schemes when I/O load is low or well balanced. Extensive trace-driven simulations for both synthetic and real I/O-intensive applications show that: (1) Compared with existing schemes that only consider CPU and memory, the proposed schemes improve the performance with respect to mean slowdown by up to a factor of 20; (2) When compared to the existing approaches that only consider I/O with non-preemptive job migrations, the proposed schemes achieve improvements in mean slowdown by up to a factor of 10; (3) Under CPU-memory intensive workloads, our scheme improves the performance over the existing approaches that only consider I/O by up to 47.5%. Xiao Qin received the BSc and MSc degrees in computer science from Huazhong University of Science and Technology in 1992 and 1999, respectively. He received the PhD degree in computer science from the University of Nebraska-Lincoln in 2004. Currently, he is an assistant professor in the department of computer science at the New Mexico Institute of Mining and Technology. His research interests include parallel and distributed systems, storage systems, real-time computing, performance evaluation, and fault-tolerance. He served on program committees of international conferences like CLUSTER, ICPP, and IPCCC. During 2000–2001, he was on the editorial board of The IEEE Distributed System Online. He is a member of the IEEE. Hong Jiang received the B.Sc. degree in Computer Engineering in 1982 from Huazhong University of Science and Technology, Wuhan, China; the M.A.Sc. degree in Computer Engineering in 1987 from the University of Toronto, Toronto, Canada; and the PhD degree in Computer Science in 1991 from the Texas A&M University, College Station, Texas, USA. Since August 1991 he has been at the University of Nebraska-Lincoln, Lincoln, Nebraska, USA, where he is Associate Professor and Vice Chair in the Department of Computer Science and Engineering. His present research interests are computer architecture, parallel/distributed computing, computer storage systems and parallel I/O, performance evaluation, middleware, networking, and computational engineering. He has over 70 publications in major journals and international Conferences in these areas and his research has been supported by NSF, DOD and the State of Nebraska. Dr. Jiang is a Member of ACM, the IEEE Computer Society, and the ACM SIGARCH and ACM SIGCOMM. Yifeng Zhu received the B.E. degree in Electrical Engineering from Huazhong University of Science and Technology in 1998 and the M.S. degree in computer science from University of Nebraska Lincoln (UNL) in 2002. Currently he is working towards his Ph.D. degree in the department of computer science and engineering at UNL. His main fields of research interests are parallel I/O, networked storage, parallel scheduling, and cluster computing. He is a student member of IEEE. David Swanson received a Ph.D. in physical (computational) chemistry at the University of Nebraska-Lincoln (UNL) in 1995, after which he worked as an NSF-NATO postdoctoral fellow at the Technical University of Wroclaw, Poland, in 1996, and subsequently as a National Research Council Research Associate at the Naval Research Laboratory in Washington, DC, from 1997–1998. In early 1999 he returned to UNL where he has coordinated the Research Computing Facility and currently serves as an Assistant Research Professor in the Department of Computer Science and Engineering. The Office of Naval Research, the National Science Foundation, and the State of Nebraska have supported his research in areas such as large-scale parallel simulation and distributed systems.     

A systems approach to morphogenesis in Arabidopsis thaliana: I. AGNS database

In systems biology, study of a complex and multicomponent system, such as morphogenesis, comprises accumulation of data on morphogenetic processes in databases, classification and logical analysis of this information, and computer simulation of the processes in question using the data accumulated and the results of their analysis. This paper describes realization of the first steps in a systems study of morphogenesis (annotating research papers, compiling information in a database, data systematization, and their logical analysis) by the example of Arabidopsis thaliana, a model object in plant molecular biology. The database AGNS (Arabidopsis GeneNet Supplementary; http://wwwmgs.bionet.nsc.ru/agns) contains the experimentally confirmed information from published papers on specific features of gene expression and phenotypes of wild-type, mutant, and transgenic A. thaliana plants. AGNS queries and logical data analysis with the aid of specially developed software makes it possible to model various morphogenetic processes from gene expression to functioning of gene networks and their contribution to the development of certain traits.

     

Expression of Mycobacterium tuberculosis Rv1991c using an arabinose-inducible promoter demonstrates its role as a toxin

Conditional gene expression systems are useful tools for studying the role of essential or toxic gene products in bacterial systems. There is a paucity of such systems available for use in the mycobacteria. The utility of the Escherichia coli arabinose-inducible system was looked into, since it is tightly controlled in response to the presence of arabinose and glucose. It was demonstrated that the P(BAD) promoter can be used to express heterologous genes in Mycobacterium smegmatis. Expression of a lacZ reporter gene demonstrated that promoter activity was inducible in response to the presence of glucose, but only on solid medium. This system was utilized to study the functional consequences of expressing one member of a putative toxin-antitoxin pair (Rv1991c). Rv1991c has homology with a number of bacterial toxins, including ChpK, MazF and PemK. A potential antitoxin gene has been identified, adjacent to Rv1991c in the genome, which was coexpressed with the toxin. Expression of the toxin alone inhibited the growth of E. coli, whereas coexpression with the antitoxin did not. Expression of Rv1991c also led to a marked reduction of cell viability in M. smegmatis, confirming its role as a potent toxin.