UNLABELLED: MATLAB is popular in biological research for creating and simulating models that use ordinary differential equations (ODEs). However, sharing or using these models outside of MATLAB is often problematic. A community standard such as Systems Biology Markup Language (SBML) can serve as a neutral exchange format, but translating models from MATLAB to SBML can be challenging-especially for legacy models not written with translation in mind. We developed MOCCASIN (Model ODE Converter for Creating Automated SBML INteroperability) to help. MOCCASIN can convert ODE-based MATLAB models of biochemical reaction networks into the SBML format. AVAILABILITY AND IMPLEMENTATION: MOCCASIN is available under the terms of the LGPL 2.1 license (http://www.gnu.org/licenses/lgpl-2.1.html). Source code, binaries and test cases can be freely obtained from https://github.com/sbmlteam/moccasin CONTACT: : [email protected] SUPPLEMENTARY INFORMATION: More information is available at https://github.com/sbmlteam/moccasin.

BACKGROUND: H1N1 influenza viruses were responsible for the 1918 pandemic that caused millions of deaths worldwide and the 2009 pandemic that caused approximately twenty thousand deaths. The cellular response to such virus infections involves extensive genetic reprogramming resulting in an antiviral state that is critical to infection control. Identifying the underlying transcriptional network driving these changes, and how this program is altered by virally-encoded immune antagonists, is a fundamental challenge in systems immunology. RESULTS: Genome-wide gene expression patterns were measured in human monocyte-derived dendritic cells (DCs) infected in vitro with seasonal H1N1 influenza A/New Caledonia/20/1999. To provide a mechanistic explanation for the timing of gene expression changes over the first 12 hours post-infection, we developed a statistically rigorous enrichment approach integrating genome-wide expression kinetics and time-dependent promoter analysis. Our approach, TIme-Dependent Activity Linker (TIDAL), generates a regulatory network that connects transcription factors associated with each temporal phase of the response into a coherent linked cascade. TIDAL infers 12 transcription factors and 32 regulatory connections that drive the antiviral response to influenza. To demonstrate the generality of this approach, TIDAL was also used to generate a network for the DC response to measles infection. The software implementation of TIDAL is freely available at http://tsb.mssm.edu/primeportal/?q=tidal_prog. CONCLUSIONS: We apply TIDAL to reconstruct the transcriptional programs activated in monocyte-derived human dendritic cells in response to influenza and measles infections. The application of this time-centric network reconstruction method in each case produces a single transcriptional cascade that recapitulates the known biology of the response with high precision and recall, in addition to identifying potentially novel antiviral factors. The ability to reconstruct antiviral networks with TIDAL enables comparative analysis of antiviral responses, such as the differences between pandemic and seasonal influenza infections.

Life depends on the capacity of individual cells to respond effectively to cues about their changing internal and external environments. Cellular decision making and responses are orchestrated by complex molecular networks consisting of entities such as proteins or RNAs connected by interactions such as activation or synthesis. Information contained in primary databases and in the experimental literature relevant to these networks is so extensive and rapidly growing that it is increasingly difficult to integrate. As an aid to theoretical and experimental research, it is convenient to distill the inferences contained in the experimental literature and databases into knowledgebases that consist of annotated representations of biological pathways. Pathway building has been performed by individual groups studying a network of interest (e.g., Kitano's group who assembled an immune signaling pathway [1]) as well as by large bioinformatics consortia (e.g., the Reactome Project [2]) and commercial entities (e.g., Ingenuity Systems). Pathway building is the process of identifying and integrating the entities, interactions, and associated annotations, and populating the knowledgebase. Pathway construction can have either a data-driven objective (DDO) or a knowledge-driven objective (KDO). Data-driven pathway construction is used to generate relationship information of genes or proteins identified in a specific experiment such as a microarray study. Knowledge-driven pathway construction entails development of a detailed pathway knowledgebase for particular domains of interest, such as a cell type, disease, or system. To help researchers get their bearings in this field, in the subsequent sections we provide a brief, practical orientation to existing knowledgebases and to the methods of pathway construction and analysis.

BACKGROUND: Cellular processes depend on the function of intracellular molecular networks. The curation of the literature relevant to specific biological pathways is important for many theoretical and experimental research teams and communities. No current tool supports web publication or hosting of user-developed large scale annotated pathway diagrams. Sharing via web publication is needed to allow real-time access to the current literature pathway knowledge-base, both privately within a research team or publicly among the outside research community. Web publication also facilitates team and/or community input into the curation process while allowing centralized control of the curation and validation process. We have developed new tool to address these needs. Biological Pathway Publisher (BioPP) is a software suite for converting CellDesigner Systems Biology Markup Language (CD-SBML) formatted pathways into a web viewable format. The BioPP suite is available for private use and for depositing knowledge-bases into a newly created public repository. RESULTS: BioPP suite is a web-based application that allows pathway knowledge-bases stored in CD-SBML to be web published with an easily navigated user interface. The BioPP suite consists of four interrelated elements: a pathway publisher, an upload web-interface, a pathway repository for user-deposited knowledge-bases and a pathway navigator. Users have the option to convert their CD-SBML files to HTML for restricted use or to allow their knowledge-base to be web-accessible to the scientific community. All entities in all knowledge-bases in the repository are linked to public database entries as well as to a newly created public wiki which provides a discussion forum. CONCLUSION: BioPP tools and the public repository facilitate sharing of pathway knowledge-bases and interactive curation for research teams and scientific communities. BioPP suite is accessible at http://tsb.mssm.edu/pathwayPublisher/broadcast/