Cell4D: a general purpose spatial stochastic simulator for cellular pathways.

BACKGROUND: With the generation of vast compendia of biological datasets, the challenge is how best to interpret 'omics data alongside biochemical and other small-scale experiments to gain meaningful biological insights. Key to this challenge are computational methods that enable domain-users to generate novel hypotheses that can be used to guide future experiments. Of particular interest are flexible modeling platforms, capable of simulating a diverse range of biological systems with low barriers of adoption to those with limited computational expertise. RESULTS: We introduce Cell4D, a spatial-temporal modeling platform combining a robust simulation engine with integrated graphics visualization, a model design editor, and an underlying XML data model capable of capturing a variety of cellular functions. Cell4D provides an interactive visualization mode, allowing intuitive feedback on model behavior and exploration of novel hypotheses, together with a non-graphics mode, compatible with high performance cloud compute solutions, to facilitate generation of statistical data. To demonstrate the flexibility and effectiveness of Cell4D, we investigate the dynamics of CEACAM1 localization in T-cell activation. We confirm the importance of Ca2+ microdomains in activating calmodulin and highlight a key role of activated calmodulin on the surface expression of CEACAM1. We further show how lymphocyte-specific protein tyrosine kinase can help regulate this cell surface expression and exploit spatial modeling features of Cell4D to test the hypothesis that lipid rafts regulate clustering of CEACAM1 to promote trans-binding to neighbouring cells. CONCLUSIONS: Through demonstrating its ability to test and generate hypotheses, Cell4D represents an effective tool to help integrate knowledge across diverse, large and small-scale datasets.

Hyperscape: visualization for complex biological networks.

MOTIVATION: Network biology has emerged as a powerful tool to uncover the organizational properties of living systems through the application of graph theoretic approaches. However, due to limitations in underlying data models and visualization software, knowledge relating to large molecular assemblies and biologically active fragments is poorly represented. RESULTS: Here, we demonstrate a novel hypergraph implementation that better captures hierarchical structures, using components of elastic fibers and chromatin modification as models. These reveal unprecedented views of the biology of these systems, demonstrating the unique capacity of hypergraphs to resolve overlaps and uncover new insights into the subfunctionalization of variant complexes. AVAILABILITY AND IMPLEMENTATION: Hyperscape is available as a web application at http://www.compsysbio.org/hyperscape. Source code, examples and a tutorial are freely available under a GNU license. CONTACTS: john.parkinson@utoronto.ca or graham.cromar@gmail.com SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Toward a systems level view of the ECM and related proteins: a framework for the systematic definition and analysis of biological systems.

Advances in high throughput 'omic technologies are starting to provide unprecedented insights into how components of biological systems are organized and interact. Key to exploiting these datasets is the definition of the components that comprise the system of interest. Although a variety of knowledge bases exist that capture such information, a major challenge is determining how these resources may be best utilized. Here we present a systematic curation strategy to define a systems-level view of the human extracellular matrix (ECM)--a three-dimensional meshwork of proteins and polysaccharides that impart structure and mechanical stability to tissues. Employing our curation strategy we define a set of 357 proteins that represent core components of the ECM, together with an additional 524 genes that mediate related functional roles, and construct a map of their physical interactions. Topological properties help identify modules of functionally related proteins, including those involved in cell adhesion, bone formation and blood clotting. Because of its major role in cell adhesion, proliferation and morphogenesis, defects in the ECM have been implicated in cancer, atherosclerosis, asthma, fibrosis, and arthritis. We use MeSH annotations to identify modules enriched for specific disease terms that aid to strengthen existing as well as predict novel gene-disease associations. Mapping expression and conservation data onto the network reveal modules evolved in parallel to convey tissue-specific functionality on otherwise broadly expressed units. In addition to demonstrating an effective workflow for defining biological systems, this study crystallizes our current knowledge surrounding the organization of the ECM.

Toxoplasma infection in male mice alters dopamine-sensitive behaviors and host gene expression patterns associated with neuropsychiatric disease.

During chronic infection, the single celled parasite, Toxoplasma gondii, can migrate to the brain where it has been associated with altered dopamine function and the capacity to modulate host behavior, increasing risk of neurocognitive disorders. Here we explore alterations in dopamine-related behavior in a new mouse model based on stimulant (cocaine)-induced hyperactivity. In combination with cocaine, infection resulted in heightened sensorimotor deficits and impairment in prepulse inhibition response, which are commonly disrupted in neuropsychiatric conditions. To identify molecular pathways in the brain affected by chronic T. gondii infection, we investigated patterns of gene expression. As expected, infection was associated with an enrichment of genes associated with general immune response pathways, that otherwise limits statistical power to identify more informative pathways. To overcome this limitation and focus on pathways of neurological relevance, we developed a novel context enrichment approach that relies on a customized ontology. Applying this approach, we identified genes that exhibited unexpected patterns of expression arising from the combination of cocaine exposure and infection. These include sets of genes which exhibited dampened response to cocaine in infected mice, suggesting a possible mechanism for some observed behaviors and a neuroprotective effect that may be advantageous to parasite persistence. This model offers a powerful new approach to dissect the molecular pathways by which T. gondii infection contributes to neurocognitive disorders.

PhyloPro2.0: a database for the dynamic exploration of phylogenetically conserved proteins and their domain architectures across the Eukarya.

PhyloPro is a database and accompanying web-based application for the construction and exploration of phylogenetic profiles across the Eukarya. In this update article, we present six major new developments in PhyloPro: (i) integration of Pfam-A domain predictions for all proteins; (ii) new summary heatmaps and detailed level views of domain conservation; (iii) an interactive, network-based visualization tool for exploration of domain architectures and their conservation; (iv) ability to browse based on protein functional categories (GOSlim); (v) improvements to the web interface to enhance drill down capability from the heatmap view; and (vi) improved coverage including 164 eukaryotes and 12 reference species. In addition, we provide improved support for downloading data and images in a variety of formats. Among the existing tools available for phylogenetic profiles, PhyloPro provides several innovative domain-based features including a novel domain adjacency visualization tool. These are designed to allow the user to identify and compare proteins with similar domain architectures across species and thus develop hypotheses about the evolution of lineage-specific trajectories. Database URL: http://www.compsysbio.org/phylopro/.