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Biomedical subjects

Herbert M Sauro

Publications and source records attributed to Herbert M Sauro.

12 recordsLinked to original sources

Supporting the SBML layout extension.

MOTIVATION: Researchers studying large or complex biochemical networks would benefit from the ability to automatically create lucid visualizations and store them in a portable and widely accepted format. SUMMARY: Two modules, SBMLSupportLayout and SBWAutoLayout, support reading, creating, manipulating and writing layout information for biochemical models. SBMLSupportLayout can read, update, add and render model layout information. SBWAutoLayout can automatically layout models, graphically manipulate model layout and generate layout information for models without layout information. AVAILABILITY: SBMLSupportLayout and SBWAutoLayout are distributed with the Systems Biology Workbench (SBW), which can be downloaded from http://www.sys-bio.org. Additionally, their visualization and layout capabilities are available online at http://www.sys-bio.org/Layout. Both modules run on Win32, Linux and the Mac OS X version is forthcoming.

Algorithms↗

Transcriptional dynamics of the embryonic stem cell switch.

Recent ChIP experiments of human and mouse embryonic stem cells have elucidated the architecture of the transcriptional regulatory circuitry responsible for cell determination, which involves the transcription factors OCT4, SOX2, and NANOG. In addition to regulating each other through feedback loops, these genes also regulate downstream target genes involved in the maintenance and differentiation of embryonic stem cells. A search for the OCT4-SOX2-NANOG network motif in other species reveals that it is unique to mammals. With a kinetic modeling approach, we ascribe function to the observed OCT4-SOX2-NANOG network by making plausible assumptions about the interactions between the transcription factors at the gene promoter binding sites and RNA polymerase (RNAP), at each of the three genes as well as at the target genes. We identify a bistable switch in the network, which arises due to several positive feedback loops, and is switched on/off by input environmental signals. The switch stabilizes the expression levels of the three genes, and through their regulatory roles on the downstream target genes, leads to a binary decision: when OCT4, SOX2, and NANOG are expressed and the switch is on, the self-renewal genes are on and the differentiation genes are off. The opposite holds when the switch is off. The model is extremely robust to parameter changes. In addition to providing a self-consistent picture of the transcriptional circuit, the model generates several predictions. Increasing the binding strength of NANOG to OCT4 and SOX2, or increasing its basal transcriptional rate, leads to an irreversible bistable switch: the switch remains on even when the activating signal is removed. Hence, the stem cell can be manipulated to be self-renewing without the requirement of input signals. We also suggest tests that could discriminate between a variety of feedforward regulation architectures of the target genes by OCT4, SOX2, and NANOG.

Animals↗

Oscillatory dynamics arising from competitive inhibition and multisite phosphorylation.

There have been a growing number of observations of oscillating protein levels (p53 and NFkB) in eukaryotic signalling pathways. This has resulted in a renewed interest in the mechanism by which such oscillations might occur. Recent computational work has shown that a multisite phosphorylation mechanism such as that found in the MAPK cascade can theoretically exhibit bistability. The bistable behavior was shown to arise from sequestration and saturation mechanisms for the enzymes that catalyse the multisite phosphorylation cycle. These effects generate the positive feedback necessary for bistability. In this paper we describe two kinds of oscillatory dynamics which can occur in a network by which, both use such bistable multisite phosphorylated cycles. In the first example, the fully phosphorylated form of the phosphorylated cycle represses the production of the kinase, which carries out the phosphorylation of the unphosphorylated states of the cycle. The dynamics of this system leads to a relaxation oscillator. In the second example, we consider a cascade of two cycles, in which the fully phosphorylated form of the kinase, in the first cycle, phosphorylates the unphosphorylated forms in the second cycle. A feedback loop, by which the fully phosphorylated form of the second cycle inhibits the kinase step in the first cycle is also present. In this case we obtain a ring oscillator. Both these networks illustrate the versatility of the multisite bistable network.

Animals↗

Conservation analysis of large biochemical networks.

MOTIVATION: Large biochemical networks pose a unique challenge from the point of view of evaluating conservation laws. The computational problem in most cases exceeds the capability of available software tools, often resulting in inaccurate computation of the number and form of conserved cycles. Such errors have profound effects on subsequent calculations, particularly in the evaluation of the Jacobian which is a critical quantity in many other calculations. The goal of this paper is to outline a new algorithm that is computationally efficient and robust at extracting the correct conservation laws for very large biochemical networks. RESULTS: We show that our algorithm can perform the conservation analysis of large biochemical networks, and can evaluate the correct conserved cycles when compared with other similar software tools. Biochemical simulators such as Jarnac and COPASI are successful at extracting only a subset of the conservation laws that our algorithm can. This is illustrated with examples for some large networks which show the advantages of our method.

Algorithms↗

Bifurcation discovery tool.

MOTIVATION: Biochemical networks often yield interesting behavior such as switching, oscillation and chaotic dynamics. This article describes a tool that is capable of searching for bifurcation points in arbitrary ODE-based reaction networks by directing the user to regions in the parameter space, where such interesting dynamical behavior can be observed. RESULTS: We have implemented a genetic algorithm that searches for Hopf bifurcations, turning points and bistable switches. The software is implemented as a Systems Biology Workbench (SBW) enabled module and accepts the standard SBML model format. The interface permits a user to choose the parameters to be searched, admissible parameter ranges, and the nature of the bifurcation to be sought. The tool will return the parameter values for the model for which the particular behavior is observed. AVAILABILITY: The software, tutorial manual and test models are available for download at the following website: http:/www.sys-bio.org/ under the bifurcation link. The software is an open source and licensed under BSD.

Algorithms↗

The SBW-MATLAB interface.

SUMMARY: The SBW-MATLAB Interface allows MATLAB users to take advantage of the wide variety of tools available through SBW, the Systems Biology Workbench (Sauro et al. (2003) OMICS, 7, 355-372). It also enables MATLAB users to themselves create SBW-enabled tools which can be freely distributed.

Computer Communication Networks↗

Preliminary studies on the in silico evolution of biochemical networks.

Due to the variety and importance of roles performed by signalling networks, understanding their function and evolution is of great interest. Signalling networks allow organisms to process and react to changes in their internal and external environment. Current estimates suggest that two to three percent of all genomes code for proteins involved in signalling networks. The study of signalling networks is hindered by the complexities of the networks and difficulties in ascribing function to form. For example, a very complex dense network might comprise eighty or more densely connected proteins. In the majority of cases there is very little understanding of how these networks process signals. Unlike in electronics, where there is a broad practical and theoretical understanding of how to construct devices that can process almost any kind of signal, in biological signalling networks there is no equivalent theory. Part of the problem stems from the fact that in most cases it is unknown what particular signal processing circuits would look like in a biological form. This paper describes the evolutionary methods used to generate networks with particular signal- and computational-processing capabilities. The techniques involved are described, and the approach is illustrated by evolving computational circuits such as multiplication, radicals and logarithmic functions. The experiments also illustrate the evolution of modularity within biochemical reaction networks.

Biochemistry↗

Conservation analysis in biochemical networks: computational issues for software writers.

Large scale genomic studies are generating significant amounts of data on the structure of cellular networks. This is in contrast to kinetic data, which is frequently absent, unreliable or fragmentary. There is, therefore, a desire by many in the community to investigate the potential rewards of analyzing the more readily available topological data. This brief review is concerned with a particular property of biological networks, namely structural conservations (e.g. moiety conserved cycles). There has been much discussion in the literature on these cycles but a review on the computational issues related to conserved cycles has been missing. This review is concerned with the detection and characterization of conservation relations in arbitrary networks and related issues, which impinge on simulation simulation software writers. This review will not address flux balance constraints or small-world type analyses in any significant detail.

Biochemical Phenomena↗

Quantitative analysis of signaling networks.

The response of biological cells to environmental change is coordinated by protein-based signaling networks. These networks are to be found in both prokaryotes and eukaryotes. In eukaryotes, the signaling networks can be highly complex, some networks comprising of 60 or more proteins. The fundamental motif that has been found in all signaling networks is the protein phosphorylation/dephosphorylation cycle--the cascade cycle. At this time, the computational function of many of the signaling networks is poorly understood. However, it is clear that it is possible to construct a huge variety of control and computational circuits, both analog and digital from combinations of the cascade cycle. In this review, we will summarize the great versatility of the simple cascade cycle as a computational unit and towards the end give two examples, one prokaryotic chemotaxis circuit and the other, the eukaryotic MAPK cascade.

Animals↗

Sensitivity analysis of stoichiometric networks: an extension of metabolic control analysis to non-steady state trajectories.

A sensitivity analysis of general stoichiometric networks is considered. The results are presented as a generalization of Metabolic Control Analysis, which has been concerned primarily with system sensitivities at steady state. An expression for time-varying sensitivity coefficients is given and the Summation and Connectivity Theorems are generalized. The results are compared to previous treatments. The analysis is accompanied by a discussion of the computation of the sensitivity coefficients and an application to a model of phototransduction.

Animals↗

Next generation simulation tools: the Systems Biology Workbench and BioSPICE integration.

Researchers in quantitative systems biology make use of a large number of different software packages for modelling, analysis, visualization, and general data manipulation. In this paper, we describe the Systems Biology Workbench (SBW), a software framework that allows heterogeneous application components--written in diverse programming languages and running on different platforms--to communicate and use each others' capabilities via a fast binary encoded-message system. Our goal was to create a simple, high performance, opensource software infrastructure which is easy to implement and understand. SBW enables applications (potentially running on separate, distributed computers) to communicate via a simple network protocol. The interfaces to the system are encapsulated in client-side libraries that we provide for different programming languages. We describe in this paper the SBW architecture, a selection of current modules, including Jarnac, JDesigner, and SBWMeta-tool, and the close integration of SBW into BioSPICE, which enables both frameworks to share tools and compliment and strengthen each others capabilities.

Biochemical Phenomena↗