The visual display of regulatory information and networks

Semantic Path-Based Learning for Review Volume Prediction

Graphs offer a natural abstraction for modeling complex real-world systems where entities are represented as nodes and edges encode relations between them. In such networks, entities may share common or similar attributes and may be connected by paths through multiple attribute modalities. In this work, we present an approach that uses semantically meaningful, bimodal random walks on real-world heterogeneous networks to extract correlations between nodes and bring together nodes with shared or similar attributes. An attention-based mechanism is used to combine multiple attribute-specific representations in a late fusion setup. We focus on a real-world network formed by restaurants and their shared attributes and evaluate performance on predicting the number of reviews a restaurant receives, a strong proxy for popularity. Our results demonstrate the rich expressiveness of such representations in predicting review volume and the ability of an attention-based model to selectively combine individual representations for maximum predictive power on the chosen downstream task.

Communicating Structure and Function in Synthetic Biology Diagrams

Biological engineers often find it useful to communicate using diagrams. These diagrams can include information both about the structure of the nucleic acid sequences they are engineering and about the functional relationships between features of these sequences and/or other molecular species. A number of conventions and practices have begun to emerge within synthetic biology for creating such diagrams, and the Synthetic Biology Open Language Visual (SBOL Visual) has been developed as a standard to organize, systematize, and extend such conventions in order to produce a coherent visual language. Here, we describe SBOL Visual version 2, which expands previous diagram standards to include new functional interactions, categories of molecular species, support for families of glyph variants, and the ability to indicate modular structure and mappings between elements of a system. SBOL Visual 2 also clarifies a number of requirements and best practices, significantly expands the collection of glyphs available to describe genetic features, and can be readily applied using a wide variety of software tools, both general and bespoke.

CySBGN: a Cytoscape plug-in to integrate SBGN maps

Background

A standard graphical notation is essential to facilitate exchange of network representations of biological processes. Towards this end, the Systems Biology Graphical Notation (SBGN) has been proposed, and it is already supported by a number of tools. However, support for SBGN in Cytoscape, one of the most widely used platforms in biology to visualise and analyse networks, is limited, and in particular it is not possible to import SBGN diagrams.

Results

We have developed CySBGN, a Cytoscape plug-in that extends the use of Cytoscape visualisation and analysis features to SBGN maps. CySBGN adds support for Cytoscape users to visualize any of the three complementary SBGN languages: Process Description, Entity Relationship, and Activity Flow. The interoperability with other tools (CySBML plug-in and Systems Biology Format Converter) was also established allowing an automated generation of SBGN diagrams based on previously imported SBML models. The plug-in was tested using a suite of 53 different test cases that covers almost all possible entities, shapes, and connections. A rendering comparison with other tools that support SBGN was performed. To illustrate the interoperability with other Cytoscape functionalities, we present two analysis examples, shortest path calculation, and motif identification in a metabolic network.

Conclusions

CySBGN imports, modifies and analyzes SBGN diagrams in Cytoscape, and thus allows the application of the large palette of tools and plug-ins in this platform to networks and pathways in SBGN format.

The Systems Biology Graphical Notation

Circuit diagrams and Unified Modeling Language diagrams are just two examples of standard visual languages that help accelerate work by promoting regularity, removing ambiguity and enabling software tool support for communication of complex information. Ironically, despite having one of the highest ratios of graphical to textual information, biology still lacks standard graphical notations. The recent deluge of biological knowledge makes addressing this deficit a pressing concern. Toward this goal, we present the Systems Biology Graphical Notation (SBGN), a visual language developed by a community of biochemists, modelers and computer scientists. SBGN consists of three complementary languages: process diagram, entity relationship diagram and activity flow diagram. Together they enable scientists to represent networks of biochemical interactions in a standard, unambiguous way. We believe that SBGN will foster efficient and accurate representation, visualization, storage, exchange and reuse of information on all kinds of biological knowledge, from gene regulation, to metabolism, to cellular signaling.

Semantics of multimodal network models

A multimodal network (MMN) is a novel graph-theoretic formalism designed to capture the structure of biological networks and to represent relationships derived from multiple biological databases. MMNs generalize the standard notions of graphs and hypergraphs, which are the bases of current diagrammatic representations of biological phenomena, and incorporate the concept of mode. Each vertex of an MMN is a biological entity, a biot, while each modal hyperedge is a typed relationship, where the type is given by the mode of the hyperedge. The semantics of each modal hyperedge e is given through denotational semantics, where a valuation function fe defines the relationship among the values of the vertices incident on e. The meaning of an MMN is denoted in terms of the semantics of a hyperedge sequence. A companion paper defines MMNs and concentrates on the structural aspects of MMNs. This paper develops MMN denotational semantics when used as a representation of the semantics of biological networks and discusses applications of MMNs in managing complex biological data.

Multimodal networks: structure and operations

A multimodal network (MMN) is a novel graph-theoretic formalism designed to capture the structure of biological networks and to represent relationships derived from multiple biological databases. MMNs generalize the standard notions of graphs and hypergraphs, which are the bases of current diagrammatic representations of biological phenomena and incorporate the concept of mode. Each vertex of an MMN is a biological entity, a biot, while each modal hyperedge is a typed relationship, where the type is given by the mode of the hyperedge. The current paper defines MMNs and concentrates on the structural aspects of MMNs. A companion paper develops MMNs as a representation of the semantics of biological networks and discusses applications of the MMNs in managing complex biological data. The MMN model has been implemented in a database system containing multiple kinds of biological networks.

Presenting and exploring biological pathways with PathVisio

Background

Biological pathways are a useful abstraction of biological concepts, and software tools to deal with pathway diagrams can help biological research. PathVisio is a new visualization tool for biological pathways that mimics the popular GenMAPP tool with a completely new Java implementation that allows better integration with other open source projects. The GenMAPP MAPP file format is replaced by GPML, a new XML file format that provides seamless exchange of graphical pathway information among multiple programs.

Results

PathVisio can be combined with other bioinformatics tools to open up three possible uses: visual compilation of biological knowledge, interpretation of high-throughput expression datasets, and computational augmentation of pathways with interaction information. PathVisio is open source software and available at .

Conclusion

PathVisio is a graphical editor for biological pathways, with flexibility and ease of use as primary goals.

The galectin family and digestive disease

The soluble-type lectins or galectins constitute a family of proteins defined by shared consensus amino acid sequence and affinity for beta-galactose-containing oligosaccharides. These molecules are widely distributed in the animal kingdom; to date, 15 mammalian galectins have been described but more are likely to be discovered. These proteins are involved in many biological processes including cell-cell and cell-matrix adhesion, growth regulation, signaling, and cytokine secretion. Over the last decade, a vast amount of reports has shown the importance of several galectins in the development and progression of malignancies in the digestive tract, mainly colorectal cancers. More recent data indicate that some of these molecules are also involved in inflammatory bowel diseases. This review focuses on the current knowledge of galectin expression and putative functions in the oesophagus, stomach, small intestine, and colon. It also highlights that the rapid accumulation of research data promises future scenarios in which individual members of the galectin family and/or their ligands will be used as diagnostic and therapeutic modalities for neoplastic as well as inflammatory disorders. However, the concretization of these potential modalities requires substantial improvements in terms of standardization of galectin expression evaluation together with prospective validation of the present data.

Incremental and unifying modelling formalism for biological interaction networks

Background

An appropriate choice of the modeling formalism from the broad range of existing ones may be crucial for efficiently describing and analyzing biological systems.

Results

We propose a new unifying and incremental formalism for the representation and modeling of biological interaction networks. This formalism allows automated translations into other formalisms, thus enabling a thorough study of the dynamic properties of a biological system. As a first illustration, we propose a translation into the R. Thomas' multivalued logical formalism which provides a possible semantics; a methodology for constructing such models is presented on a classical benchmark: the λ phage genetic switch. We also show how to extract from our model a classical ODE description of the dynamics of a system.

Conclusion

This approach provides an additional level of description between the biological and mathematical ones. It yields, on the one hand, a knowledge expression in a form which is intuitive for biologists and, on the other hand, its representation in a formal and structured way.

Tools for visually exploring biological networks

Many tools exist for visually exploring biological networks including well-known examples such as Cytoscape, VisANT, Pathway Studio and Patika. These systems play a key role in the development of integrative biology, systems biology and integrative bioinformatics. The trend in the development of these tools is to go beyond 'static' representations of cellular state, towards a more dynamic model of cellular processes through the incorporation of gene expression data, subcellular localization information and time-dependent behavior. We provide a comprehensive review of the relative advantages and disadvantages of existing systems with two goals in mind: to aid researchers in efficiently identifying the appropriate existing tools for data visualization; to describe the necessary and realistic goals for the next generation of visualization tools. In view of the first goal, we provide in the Supplementary Material a systematic comparison of more than 35 existing tools in terms of over 25 different features.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Network visualization and network analysis

Network analysis of living systems is an essential component of contemporary systems biology. It is targeted at assemblance of mutual dependences between interacting systems elements into an integrated view of whole-system functioning. In the following chapter we describe the existing classification of what is referred to as biological networks and show how complex interdependencies in biological systems can be represented in a simpler form of network graphs. Further structural analysis of the assembled biological network allows getting knowledge on the functioning of the entire biological system. Such aspects of network structure as connectivity of network elements and connectivity degree distribution, degree of node centralities, clustering coefficient, network diameter and average path length are touched. Networks are analyzed as static entities, or the dynamical behavior of underlying biological systems may be considered. The description of mathematical and computational approaches for determining the dynamics of regulatory networks is provided. Causality as another characteristic feature of a dynamically functioning biosystem can be also accessed in the reconstruction of biological networks; we give the examples of how this integration is accomplished. Further questions about network dynamics and evolution can be approached by means of network comparison. Network analysis gives rise to new global hypotheses on systems functionality and reductionist findings of novel molecular interactions, based on the reliability of network reconstructions, which has to be tested in the subsequent experiments. We provide a collection of useful links to be used for the analysis of biological networks.

Molecular interaction maps of bioregulatory networks: a general rubric for systems biology

A standard for bioregulatory network diagrams is urgently needed in the same way that circuit diagrams are needed in electronics. Several graphical notations have been proposed, but none has become standard. We have prepared many detailed bioregulatory network diagrams using the molecular interaction map (MIM) notation, and we now feel confident that it is suitable as a standard. Here, we describe the MIM notation formally and discuss its merits relative to alternative proposals. We show by simple examples how to denote all of the molecular interactions commonly found in bioregulatory networks. There are two forms of MIM diagrams. "Heuristic" MIMs present the repertoire of interactions possible for molecules that are colocalized in time and place. "Explicit" MIMs define particular models (derived from heuristic MIMs) for computer simulation. We show also how pathways or processes can be highlighted on a canonical heuristic MIM. Drawing a MIM diagram, adhering to the rules of notation, imposes a logical discipline that sharpens one's understanding of the structure and function of a network.

Using process diagrams for the graphical representation of biological networks

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 human-readable 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).

A comprehensive pathway map of epidermal growth factor receptor signaling

The epidermal growth factor receptor (EGFR) signaling pathway is one of the most important pathways that regulate growth, survival, proliferation, and differentiation in mammalian cells. Reflecting this importance, it is one of the best-investigated signaling systems, both experimentally and computationally, and several computational models have been developed for dynamic analysis. A map of molecular interactions of the EGFR signaling system is a valuable resource for research in this area. In this paper, we present a comprehensive pathway map of EGFR signaling and other related pathways. The map reveals that the overall architecture of the pathway is a bow-tie (or hourglass) structure with several feedback loops. The map is created using CellDesigner software that enables us to graphically represent interactions using a well-defined and consistent graphical notation, and to store it in Systems Biology Markup Language (SBML).

Molecular interaction maps--a diagrammatic graphical language for bioregulatory networks

Molecular interaction maps (MIMs) use a clear, accurate, and versatile graphical language to depict complex biological processes. Here, we discuss the main features of the MIM language and its potential uses. MIMs can be used as database resources and simulation guides, and can serve to generate new hypotheses regarding the roles of specific molecules in the bioregulatory networks that control progression through the cell cycle, differentiation, and cell death.

VisANT: an online visualization and analysis tool for biological interaction data

Background

New techniques for determining relationships between biomolecules of all types – genes, proteins, noncoding DNA, metabolites and small molecules – are now making a substantial contribution to the widely discussed explosion of facts about the cell. The data generated by these techniques promote a picture of the cell as an interconnected information network, with molecular components linked with one another in topologies that can encode and represent many features of cellular function. This networked view of biology brings the potential for systematic understanding of living molecular systems.

Results

We present VisANT, an application for integrating biomolecular interaction data into a cohesive, graphical interface. This software features a multi-tiered architecture for data flexibility, separating back-end modules for data retrieval from a front-end visualization and analysis package. VisANT is a freely available, open-source tool for researchers, and offers an online interface for a large range of published data sets on biomolecular interactions, including those entered by users. This system is integrated with standard databases for organized annotation, including GenBank, KEGG and SwissProt. VisANT is a Java-based, platform-independent tool suitable for a wide range of biological applications, including studies of pathways, gene regulation and systems biology.

Conclusion

VisANT has been developed to provide interactive visual mining of biological interaction data sets. The new software provides a general tool for mining and visualizing such data in the context of sequence, pathway, structure, and associated annotations. Interaction and predicted association data can be combined, overlaid, manipulated and analyzed using a variety of built-in functions. VisANT is available at .

CADLIVE for constructing a large-scale biochemical network based on a simulation-directed notation and its application to yeast cell cycle

The further understanding of the mechanisms of gene regulatory networks requires comprehensive tools for both the representation of complicated signal transduction pathways and the in silico identification of genomic signals that govern the regulation of gene expression. Consequently, sophisticated notation must be developed to represent the signal transduction pathways in a form that can be readily processed by both computers and humans. We propose the regulator-reaction equations combined with detailed attributes including the associated cellular component, molecular function, and biological process and present the simulation-directed graphical notation that is derived from modification of Kohn's method. We have developed the software suite, CADLIVE (Computer-Aided Design of LIVing systEms), which features a graphical user interface (GUI) to edit large-scale maps of complicated signal transduction pathways using a conventional XML-based representation. The regulator-reaction equations represent not only mechanistic reactions, but also semantic models containing ambiguous and incomplete processes. In order to demonstrate the feasibility of CADLIVE, we constructed a detailed map of the budding yeast cell cycle, which consists of 184 molecules and 152 reactions, in a really compact space. CADLIVE enables one to look at the whole view of a large-scale map, to integrate postgenomic data into the map, and to computationally simulate the signal transduction pathways, which greatly facilitates exploring novel or unexpected interactions.

Survival pathways regulating the apoptosis induced by tumour necrosis factor-alpha in primary cultured bovine endothelial cells

The aim of the present study was to identify biochemical pathways driving the resistance of endothelial cells to apoptosis induced by tumour necrosis factor-alpha (TNF). (1) Although nuclear factor-kappa B (NF-kappaB) was activated by TNF, its inhibition by MG-132 failed to sensitize these cells. (2) The activation of protein kinase C (PKC) by phorbol ester completely abolished the TNF-induced cell death. (3) The phosphatidylinositol 3-kinase (PI3K) inhibitor wortmannin (Wo) triggered apoptosis and enhanced the TNF-induced cell death. (4) The MEK inhibitor PD98059 did not affect the TNF-induced apoptotic process. (5) The p38 is activated by TNF and its inhibition by SB203580 sensitized the cells to TNF. This is correlated with the inhibition of phosphorylation of heat-shock protein of 27 kDa (HSP27). These results indicate that TNF activates NF-kappaB, which does not drive any anti-apoptotic response, and p38, which plays an anti-apoptotic function probably through HSP27 phosphorylation. Moreover, PKC and PI3K are involved in the control of survival pathways.

Cross signaling, cell specificity, and physiology

The literature on intracellular signal transduction presents a confusing picture: every regulatory factor appears to be regulated by all signal transduction cascades and to regulate all cell processes. This contrasts with the known exquisite specificity of action of extracellular signals in different cell types in vivo. The confusion of the in vitro literature is shown to arise from several causes: the inevitable artifacts inherent in reductionism, the arguments used to establish causal effect relationships, the use of less than adequate models (cell lines, transfections, acellular systems, etc.), and the implicit assumption that networks of regulations are universal whereas they are in fact cell and stage specific. Cell specificity results from the existence in any cell type of a unique set of proteins and their isoforms at each level of signal transduction cascades, from the space structure of their components, from their combinatorial logic at each level, from the presence of modulators of signal transduction proteins and of modulators of modulators, from the time structure of extracellular signals and of their transduction, and from quantitative differences of expression of similar sets of factors.

The role of cyclic AMP and its effect on protein kinase A in the mitogenic action of thyrotropin on the thyroid cell

Cyclic AMP has been shown to inhibit cell proliferation in many cell types and to activate it in some. The latter has been recognized only lately, thanks in large part to studies on the regulation of thyroid cell proliferation in dog thyroid cells. The steps that led to this conclusion are outlined. Thyrotropin activates cyclic accumulation in thyroid cells of all the studied species and also phospholipase C in human cells. It activates directly cell proliferation in rat cell lines, dog, and human thyroid cells but not in bovine or pig cells. The action of cyclic AMP is responsible for the proliferative effect of TSH. It accounts for several human diseases: congenital hyperthyroidism, autonomous adenomas, and Graves' disease; and, by default, for hypothyroidism by TSH receptor defect. Cyclic AMP proliferative action requires the activation of protein kinase A, but this effect is not sufficient to explain it. Cyclic AMP action also requires the permissive effect of IGF-1 or insulin through their receptors, mostly as a consequence of PI3 kinase activation. The mechanism of these effects at the level of cyclin and cyclin-dependent protein kinases involves an induction of cyclin D3 by IGF-1 and the cyclic AMP-elicited generation and activation of the cyclin D3-CDK4 complex.

A new approach to decoding life: systems biology

Systems biology studies biological systems by systematically perturbing them (biologically, genetically, or chemically); monitoring the gene, protein, and informational pathway responses; integrating these data; and ultimately, formulating mathematical models that describe the structure of the system and its response to individual perturbations. The emergence of systems biology is described, as are several examples of specific systems approaches.

Synthetic cell biology

Synthesis of data into formal models of cellular function is rapidly becoming a necessary industry. The complexity of the interactions among cellular constituents and the quantity of data about these interactions hinders the ability to predict how cells will respond to perturbation and how they can be engineered for industrial or medical purposes. Models provide a systematic framework to describe and analyze these complex systems. In the past few years, models have begun to have an impact on mainstream biology by creating deeper insight into the design rules of cellular signal processing, providing a basis for rational engineering of cells, and for resolving debates about the root causes of certain cellular behaviors. This review covers some of the recent work and challenges in developing these "synthetic cell" models and their growing practical applications.

Regulation of thyroid cell proliferation by TSH and other factors: a critical evaluation of in vitro models

TSH via cAMP, and various growth factors, in cooperation with insulin or IGF-I stimulate cell cycle progression and proliferation in various thyrocyte culture systems, including rat thyroid cell lines (FRTL-5, WRT, PC Cl3) and primary cultures of rat, dog, sheep and human thyroid. The available data on cell signaling cascades, cell cycle kinetics, and cell cycle-regulatory proteins are thoroughly and critically reviewed in these experimental systems. In most FRTL-5 cells, TSH (cAMP) merely acts as a priming/competence factor amplifying PI3K and MAPK pathway activation and DNA synthesis elicited by insulin/IGF-I. In WRT cells, TSH and insulin/IGF-I can independently activate Ras and PI3K pathways and DNA synthesis. In dog thyroid primary cultures, TSH (cAMP) does not activate Ras and PI3K, and cAMP must be continuously elevated by TSH to directly control the progression through G(1) phase. This effect is exerted, at least in part, via the cAMP-dependent activation of the required cyclin D3, itself synthesized in response to insulin/IGF-I. This and other discrepancies show that the mechanistic logics of cell cycle stimulation by cAMP profoundly diverge in these different in vitro models of the same cell. Therefore, although these different thyrocyte systems constitute interesting models of the wide diversity of possible mechanisms of cAMP-dependent proliferation in various cell types, extrapolation of in vitro mechanistic data to TSH-dependent goitrogenesis in man can only be accepted in the cases where independent validation is provided.