A graphical notation to describe the logical interactions of biological pathways (original) (raw)
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Pathway Logic: Helping Biologists to Organize and Understand Pathway Information
2005
Abstract: Pathway Logic [1-3] is an application of techniques fromformal methods to the modeling and analysis of signaltransduction networks in mammalian cells. Thesesignaling network models are developed using Maude[4,5], a symbolic language founded on rewriting logic[6]. Network elements (reactions) are represented asrewrite rules. Models can be queried (analyzed) usingthe execution, search and model-checking tools of theMaude system. Collections of rules and initial states ofinterest form a...
Pathway logic: symbolic analysis of biological signaling
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing, 2002
The genomic sequencing of hundreds of organisms including homo sapiens, and the exponential growth in gene expression and proteomic data for many species has revolutionized research in biology. However, the computational analysis of these burgeoning datasets has been hampered by the sparse successes in combinations of data sources, representations, and algorithms. Here we propose the application of symbolic toolsets from the formal methods community to problems of biological interest, particularly signaling pathways, and more specifically mammalian mitogenic and stress responsive pathways. The results of formal symbolic analysis with extremely efficient representations of biological networks provide insights with potential biological impact. In particular, novel hypotheses may be generated which could lead to wet lab validation of new signaling possibilities. We demonstrate the graphic representation of the results of formal analysis of pathways, including navigational abilities, an...
Ten simple rules for creating reusable pathway models for computational analysis and visualization
PLOS Computational Biology, 2021
Pathway models are an effective way to capture and share our current understanding of biological processes. A pathway model is defined here as a set of interactions among biological entities (e.g., proteins and metabolites) relevant to a particular context, curated and organized to illustrate a particular process. Properly modeled pathways can be used in the analysis and visualization of diverse types of omics and other biomedical data [1,2]. The modeling process involves taking our knowledge about biological pathways-however messy and incompleteand encoding it in standardized data formats that can be shared, reused, and synthesized with other knowledge in accordance with the Findable, Accessible, Interoperable, and Reusable (FAIR) principles [3]. The rules presented here serve as an introduction and guide to the pathway modeling process, leveraging freely available tools and resources. Biological pathway information is often conveyed as published figures, and rules for better figures, in general, are also relevant when producing pathway models [4]. However, pathway models are more than just figures. In addition to providing an intuitive depiction of a biological process that is easy to understand for humans, they also provide relevant annotations and metadata to be processed by computers. Similarly, rules for network visualizations can be applied to pathway models [5], but the distinct context, layout, and usage of pathway models necessitate specific guidelines and rules. Pathway models are described with specific languages, such as the Systems Biology Graphical Notation (SBGN) [6], the Systems Biology Markup Language (SBML) [7], the Biological Pathway Exchange (BioPAX) format [8], the Graphical Pathway Markup Language (GPML) [9], and many more. Here, we describe a set of rules for constructing pathway models to optimize their use both as graphical representations for human consumption and as FAIR resources for computational analysis. The rules range from reusability and dissemination (Rules 1, 9, and 10), intuitive visual concepts (Rules 2, 7, and 8), to enabling computational analysis (Rules 3 to 6). We hope that these rules provide a simple framework for pathway model curators who want to create (re)usable resources for the scientific community.
A graphical notation for biochemical networks
BIOSILICO, 2003
A solid definition and comprehensive graphical representation of biological networks is essential for efficient and accurate dissemination of information on biological models. Several proposals have already been made toward this aim.The most well known representation of this kind is a molecular interaction map, or 'Kohn Map'. However, although the molecular interaction map is a well-defined and compact notation, there are several drawbacks, such as difficulties in intuitive understanding of temporal changes of reactions and additional complexities arising from particular graphical representations. This article proposes several improvements to the molecular interaction map, as well as the use of the 'process diagram' to help understand temporal sequences of reactions. www.drugdiscoverytoday.com REVIEWS PERSPECTIVE w 176
Bioinformatics, 2011
Many models and analysis of signaling pathways have been proposed. However, neither of them takes into account that a biological pathway is not a fixed system, but instead it depends on the organism, tissue and cell type as well as on physiological, pathological and experimental conditions. Results: The Biological Connection Markup Language (BCML) is a format to describe, annotate and visualize pathways. BCML is able to store multiple information, permitting a selective view of the pathway as it exists and/or behave in specific organisms, tissues and cells. Furthermore, BCML can be automatically converted into data formats suitable for analysis and into a fully SBGN-compliant graphical representation, making it an important tool that can be used by both computational biologists and 'wet lab' scientists. Availability and implementation: The XML schema and the BCML software suite are freely available under the LGPL for download at http://bcml.dc-atlas.net. They are implemented in Java and supported on MS Windows, Linux and OS X. Contact:
Systems Biology Graphical Notation: Process Description language Level 1 Version 2.0
Journal of Integrative Bioinformatics, 2019
The Systems Biology Graphical Notation (SBGN) is an international community effort that aims to standardise the visualisation of pathways and networks for readers with diverse scientific backgrounds as well as to support an efficient and accurate exchange of biological knowledge between disparate research communities, industry, and other players in systems biology. SBGN comprises the three languages Entity Relationship, Activity Flow, and Process Description (PD) to cover biological and biochemical systems at distinct levels of detail. PD is closest to metabolic and regulatory pathways found in biological literature and textbooks. Its well-defined semantics offer a superior precision in expressing biological knowledge. PD represents mechanistic and temporal dependencies of biological interactions and transformations as a graph. Its different types of nodes include entity pools (e.g. metabolites, proteins, genes and complexes) and processes (e.g. reactions, associations and influences). The edges describe relationships between the nodes (e.g. consumption, production, stimulation and
Lecture Notes in Computer Science, 2011
For a long time biologists have used visual representations of biochemical networks to gain a quick overview of important structural properties. Recently SBGN, the Systems Biology Graphical Notation, has been developed to standardise the way in which such graphical maps are drawn in order to facilitate the exchange of information. Its qualitative Process Description (SBGN-PD) diagrams are based on an implicit Process Flow Abstraction (PFA) that can also be used to construct quantitative representations, which facilitate automated analyses of the system. Here we explicitly describe the PFA that underpins SBGN-PD and define attributes for SBGN-PD glyphs that make it possible to capture the quantitative details of a biochemical reaction network. Such quantitative details can be used to automatically generate an executable model. To facilitate this, we developed a textual representation for SBGN-PD called "SBGNtext" and implemented SBGNtext2BioPEPA, a tool that demonstrates how Bio-PEPA models can be generated automatically from SBGNtext. Bio-PEPA is a process algebra that was designed for implementing quantitative models of concurrent biochemical reaction systems. The scheme developed here is general and can be easily adapted to other output formalisms. To illustrate the intended workflow, we model the metabolic pathway of the cholesterol synthesis. We use this to compute the statin dosage response of the flux through the cholesterol pathway for different concentrations of the enzyme HMGCR that is inhibited by statin.
Modelling the Structure and Dynamics of Biological Pathways
PLOS Biology, 2016
There is a need for formalised diagrams that both summarise current biological pathway knowledge and support modelling approaches that explain and predict their behaviour. Here, we present a new, freely available modelling framework that includes a biologistfriendly pathway modelling language (mEPN), a simple but sophisticated method to support model parameterisation using available biological information; a stochastic flow algorithm that simulates the dynamics of pathway activity; and a 3-D visualisation engine that aids understanding of the complexities of a system's dynamics. We present example pathway models that illustrate of the power of approach to depict a diverse range of systems.
Using process diagrams for the graphical representation of biological networks
2005
With the increased interest in understanding biological networks, such as protein-protein interaction networks and gene regulatory networks, methods for representing and communicating such networks in both human-and machine-readable form have become increasingly important. Although there has been significant progress in machine-readable representation of networks, as exemplified by the Systems Biology Mark-up Language (SBML) (http://www.sbml.org) issues in humanreadable representation have been largely ignored. This article discusses human-readable diagrammatic representations and proposes a set of notations that enhances the formality and richness of the information represented. The process diagram is a fully state transition-based diagram that can be translated into machine-readable forms such as SBML in a straightforward way. It is supported by CellDesigner, a diagrammatic network editing software (http://www.celldesigner.org/), and has been used to represent a variety of networks of various sizes (from only a few components to several hundred components).