Cytoscape: the network visualization tool for GenomeSpace workflows.

Modern genomic analysis often requires workflows incorporating multiple best-of-breed tools. GenomeSpace is a web-based visual workbench that combines a selection of these tools with mechanisms that create data flows between them. One such tool is Cytoscape 3, a popular application that enables analysis and visualization of graph-oriented genomic networks. As Cytoscape runs on the desktop, and not in a web browser, integrating it into GenomeSpace required special care in creating a seamless user experience and enabling appropriate data flows. In this paper, we present the design and operation of the Cytoscape GenomeSpace app, which accomplishes this integration, thereby providing critical analysis and visualization functionality for GenomeSpace users. It has been downloaded over 850 times since the release of its first version in September, 2013

Biological Network Exploration with Cytoscape 3

Cytoscape is one of the most popular open‐source software tools for the visual exploration of biomedical networks composed of protein, gene, and other types of interactions. It offers researchers a versatile and interactive visualization interface for exploring complex biological interconnections supported by diverse annotation and experimental data, thereby facilitating research tasks such as predicting gene function and constructing pathways. Cytoscape provides core functionality to load, visualize, search, filter, and save networks, and hundreds of Apps extend this functionality to address specific research needs. The latest generation of Cytoscape (version 3.0 and later) has substantial improvements in function, user interface, and performance relative to previous versions. This protocol aims to jump‐start new users with specific protocols for basic Cytoscape functions, such as installing Cytoscape and Cytoscape Apps, loading data, visualizing and navigating the networks, visualizing network associated data (attributes), and identifying clusters. It also highlights new features that benefit experienced users. Curr. Protoc. Bioinform. 47:8.13.1‐8.13.24. © 2014 by John Wiley & Sons, Inc.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/143619/1/cpbi0813.pd

aMatReader: Importing adjacency matrices via Cytoscape Automation [version 1; referees: 2 approved]

Adjacency matrices are useful for storing pairwise interaction data, such as correlations between gene pairs in a pathway or similarities between genes and conditions. The aMatReader app enables users to import one or multiple adjacency matrix files into Cytoscape, where each file represents an edge attribute in a network. Our goal was to import the diverse adjacency matrix formats produced by existing scripts and libraries written in R, MATLAB, and Python, and facilitate importing that data into Cytoscape. To accelerate the import process, aMatReader attempts to predict matrix import parameters by analyzing the first two lines of the file. We also exposed CyREST endpoints to allow researchers to import network matrix data directly into Cytoscape from their language of choice. Many analysis tools deal with networks in the form of an adjacency matrix, and exposing the aMatReader API to automation users enables scripts to transfer those networks directly into Cytoscape with little effort

aMatReader: Importing adjacency matrices via Cytoscape Automation [version 2; referees: 2 approved]

Adjacency matrices are useful for storing pairwise interaction data, such as correlations between gene pairs in a pathway or similarities between genes and conditions. The aMatReader app enables users to import one or multiple adjacency matrix files into Cytoscape, where each file represents an edge attribute in a network. Our goal was to import the diverse adjacency matrix formats produced by existing scripts and libraries written in R, MATLAB, and Python, and facilitate importing that data into Cytoscape. To accelerate the import process, aMatReader attempts to predict matrix import parameters by analyzing the first two lines of the file. We also exposed CyREST endpoints to allow researchers to import network matrix data directly into Cytoscape from their language of choice. Many analysis tools deal with networks in the form of an adjacency matrix, and exposing the aMatReader API to automation users enables scripts to transfer those networks directly into Cytoscape with little effort

Copycat Layout: Network layout alignment via Cytoscape Automation [version 2; referees: 2 approved]

The copycatLayout app is a network-based visual differential analysis tool that improves upon the existing layoutSaver app and is delivered pre-installed with Cytoscape, beginning with v3.6.0. LayoutSaver cloned a network layout by mapping node locations from one network to another based on node attribute values, but failed to clone view scale and location, and provided no means of identifying which nodes were successfully mapped between networks. Copycat addresses these issues and provides additional layout options. With the advent of Cytoscape Automation (packaged in Cytoscape v3.6.0), researchers can utilize the Copycat layout and its output in workflows written in their language of choice by using only a few simple REST calls. Copycat enables researchers to visually compare groups of homologous genes, generate network comparison images for publications, and quickly identify differences between similar networks at a glance without leaving their script. With a few extra REST calls, scripts can discover nodes present in one network but not in the other, which can feed into more complex analyses (e.g., modifying mismatched nodes based on new data, then re-running the layout to highlight additional network changes)

The Security imaginary: Explaining military isomorphism

This article proposes the notion of a security imaginary as a heuristic tool for exploring military isomorphism (the phenomenon that weapons and military strategies begin to look the same across the world) at a time when the US model of defence transformation is being adopted by an increasing number of countries. Built on a critical constructivist foundation, the security-imaginary approach is contrasted with rationalist and neo-institutionalist ways of explaining military diffusion and emulation. Merging cultural and constructivist themes, the article offers a ‘strong cultural’ argument to explain why a country would emulate a foreign military model and how this model is constituted in and comes to constitute a society’s security imaginary.Web of Scienc

Integrative genomic analysis by interoperation of bioinformatics tools in GenomeSpace

Integrative analysis of multiple data types to address complex biomedical questions requires the use of multiple software tools in concert and remains an enormous challenge for most of the biomedical research community. Here we introduce GenomeSpace (http://www.genomespace.org), a cloud-based, cooperative community resource. Seeded as a collaboration of six of the most popular genomics analysis tools, GenomeSpace now supports the streamlined interaction of 20 bioinformatics tools and data resources. To facilitate the ability of non-programming users’ to leverage GenomeSpace in integrative analysis, it offers a growing set of ‘recipes’, short workflows involving a few tools and steps to guide investigators through high utility analysis tasks

Policy driven development : SOA evolvability through late binding

Software maintenance is a significant cost driver in the value proposition of large scale software systems such as cyberinfrastructures (CIs) - it is often the longest and most expensive phase of software production. Because software maintenance and delivery cycles are often long and risky, stakeholder requirements are often not realized in timeframes meaningful to stakeholders. Such delays impair software system value due to lost opportunities, costs exceeding benefits, and stakeholder disenfranchisement. As a solution, my dissertation proposes a new methodology called Policy Driven Design (PDD), which enables the composition of stakeholder requirements onto an unprepared application at runtime. PDD models an application as a collection of base workflows that implement stakeholder requirements. It defines a policy as a decision that chooses amongst alternative workflows - stakeholder requirements can be expressed and realized as policies injected into a base workflow. An important source of delays under existing methodologies is early binding, which occurs when requirements (as policies) are integrated into applications during design and coding phases, often causing entanglement and scattering at both abstract and coding levels, and resulting in delays and mis- implementations. PDD introduces late binding as the injection of requirements (as policies) into running systems without incurring traditional development risks and delays. PDD policies are expressed using Domain Specific Languages tailored to requirement domains, thereby enabling stakeholders to participate directly in defining, vetting, and evolving policies. To demonstrate and evaluate PDD, I designed and implemented a successful real world cyberinfrastructure (PALMS-CI) using PDD principles. PALMS' late binding demonstrated policy injection with acceptable overhead in common cases. Its workflow support proved effective in significantly reducing entanglement and scattering, and its DSL support demonstrated stakeholder enfranchisement resulting in quick and accurate requirement realization. PDD leverages Aspect Oriented Software Design (AOSD) and Service Oriented Architecture (SOA) principles, and contributes : * a SOA foundation for policy definition and injection, * a family of policy languages that enable programmer/ stakeholder collaboration, * a working cyberinfrastructure that realizes PDD and serves as a platform for future development. Given the intensifying contradiction between greater system complexity, increasing stakeholder demands, and shorter delivery timeframes, PDD uncovers a low cost route to high valu