arXiv subjects

Herbert M Sauro

Publications and source records attributed to Herbert M Sauro.

7 recordsLinked to original sources

arXiv2026

DigiPhen: a new paradigm for building predictive models of biological systems

Reengineered biological systems have the potential to revolutionize chemical and material production, enhance critical mineral recovery, serve as threat sensors and improve human health. Unfortunately, the extreme complexity of organisms has made it difficult to achieve this potential in all but the simplest cases. Recent technological advances, however, have provided a foundation for solving this problem. Here, we describe a capability for accelerating the reengineering of cells by providing accurate predictions of the impact of genetic or environmental changes on cell phenotype. This digital phenome platform (DigiPhen) consists of integrated experimental, analytical and modeling workflows for building a digital representation of microbial or plant systems. It is designed around an expanding set of interchangeable, interconnecting software and experimental modules that can accurately represent the mechanistic determinants of phenotype. The DigiPhen platform will systematically collect data on cell composition, spatial organization, metabolic pathways and regulatory networks in a semi-autonomous fashion and use this information to build modular, multi-scale models of biological systems. These models will be used to predict molecular and environmental changes needed for producing desired biological outcomes. DigiPhen is intended to be the heart of community research campaigns that will meet the immediate needs of individual researchers while fulfilling long-term goals of the scientific community. Altogether, the DigiPhen platform represents a new paradigm for building predictive models of biological systems.

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arXiv2025

Alias4SBML: A Python Package for Generating Alias Nodes in SBML Models

Interpreting biological networks becomes challenging when molecular components, such as genes or proteins, participate in numerous interactions, resulting in densely connected regions and overlapping interactions that obscure functional relationships and biological insights. To address this, we introduce Alias4SBML, a Python package that enhances SBML model visualizations by generating alias nodes-duplicate representations of highly connected molecular components-to redistribute interactions and reduce visual congestion. Applying Alias4SBML to the SBML models, including one with 59 species and 41 reactions and another with 701 species and 505 reactions, demonstrated significant improvements in readability, with edge length reductions of up to 50.88 %. Our approach preserves the structural integrity of the network while facilitating clearer interpretation of complex biological systems, offering a flexible and scalable solution for visualizing biological models more efficiently.

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arXiv2024

Computing the Frequency Response of Biochemical Networks: A Python module

In this paper, a set of Python methods is described that can be used to compute the frequency response of an arbitrary biochemical network given any input and output. Models can be provided in standard SBML or Antimony format. The code takes into account any conserved moieties so that this software can be used to also study signaling networks where moiety cycles are common. A utility method is also provided to make it easy to plot standard Bode plots from the generated results. The code also takes into account the possibility that the phase shift could exceed 180 degrees which can result in ugly discontinuities in the Bode plot. In the paper, some of the theory behind the method is provided as well as some commentary on the code and several illustrative examples to show the code in operation. Illustrative examples include linear reaction chains of varying lengths and the effect of negative feedback on the frequency response. Software License: MIT Open Source Availability: The code is available from https://github.com/sys-bio/frequencyResponse.

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arXiv2024

An Update to the SBML Human-Readable Antimony Language

Antimony is a high-level, human-readable text-based language designed for defining and sharing models in the systems biology community. It enables scientists to describe biochemical networks and systems using a simple and intuitive syntax. It allows users to easily create, modify, and distribute reproducible computational models. By allowing the concise representation of complex biological processes, Antimony enhances collaborative efforts, improves reproducibility, and accelerates the iterative development of models in systems biology. This paper provides an update to the Antimony language since it was introduced in 2009. In particular, we highlight new annotation features, support for flux balance analysis, a new rateOf method, support for probability distributions and uncertainty, named stochiometries, and algebraic rules. Antimony is also now distributed as a C/C++ library, together with python and Julia bindings, as well as a JavaScript version for use within a web browser. Availability: https://github.com/sys-bio/antimony.

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arXiv2024

A Simple Comparison of Biochemical Systems Theory and Metabolic Control Analysis

This paper explores some basic concepts of Biochemical Systems Theory (BST) and Metabolic Control Analysis (MCA), two frameworks developed to understand the behavior of biochemical networks. Initially introduced by Savageau, BST focuses on system stability and employs power laws in modeling biochemical systems. On the other hand, MCA, pioneered by authors such as Kacser and Burns and Heinrich and Rapoport, emphasizes linearization of the governing equations and describes relationships (known as theorems) between different measures. Despite apparent differences, both frameworks are shown to be equivalent in many respects. Through a simple example of a linear chain, the paper demonstrates how BST and MCA yield identical results when analyzing steady-state behavior and logarithmic gains within biochemical pathways. This comparative analysis highlights the interchangeability of concepts such as kinetic orders, elasticities and other logarithmic gains.

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arXiv2021

SimpleSBML: A Python package for creating, editing, and interrogating SBML models: Version 2.0

In this technical report, we describe a new version of SimpleSBML which provides an easier to use interface to python-libSBML allowing users of Python to more easily construct, edit, and inspect SBML based models. The most commonly used package for constructing SBML models in Python is python-libSBML based on the C/C++ library libSBML. python-libSBML is a comprehensive library with a large range of options but can be difficult for new users to learn and requires long scripts to create even the simplest models. Inspecting existing SBML models can also be difficult due to the complexity of the underlying object model. Instead, we present SimpleSBML, a package that allows users to add and inspect species, parameters, reactions, events, and rules to a libSBML model with only one command for each. Models can be exported to SBML format, and SBML files can be imported and converted to SimpleSBML commands making it very easy to edit the original SBML model. In the new version, a range of `get' methods is provided that allows users to inspect existing SBML models without having to understand the underlying object model used by libSBML.

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arXiv2007

MAPK Cascades as Feedback Amplifiers

Interconvertible enzyme cascades, exemplified by the mitogen activated protein kinase (MAPK) cascade, are a frequent mechanism in signal transduction pathways. There has been much speculation as to the role of these pathways, and how their structure is related to their function. A common conclusion is that the cascades serve to amplify biochemical signals so that a single bound ligand molecule might produce a multitude of second messengers. Some recent work has focused on a particular feature present in some MAPK pathways -- a negative feedback loop which spans the length of the cascade. This is a feature that is shared by a man-made engineering device, the feedback amplifier. We propose a novel interpretation: that by wrapping a feedback loop around an amplifier, these cascades may be acting as biochemical feedback amplifiers which imparts i) increased robustness with respect to internal perturbations; ii) a linear graded response over an extended operating range; iii) insulation from external perturbation, resulting in functional modularization. We also report on the growing list of experimental evidence which supports a graded response of MAPK with respect to Epidermal Growth Factor. This evidence supports our hypothesis that in these circumstances MAPK cascade, may be acting as a feedback amplifier.

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