FNV: Light-weight Flash-based network and pathway viewer
ABSTRACT Network diagrams are commonly used to visualize biochemical pathways by displaying the relationships between genes, proteins, mRNAs, microRNAs, metabolites, regulatory DNA elements, diseases, viruses and drugs. While there are several currently available web-based pathway viewers, there is still room for improvement. To this end, we have developed a flash-based network viewer (FNV) for the visualization of small to moderately sized biological networks and pathways.
Written in Adobe ActionScript 3.0, the viewer accepts simple Extensible Markup Language (XML) formatted input files to display pathways in vector graphics on any web-page providing flexible layout options, interactivity with the user through tool tips, hyperlinks and the ability to rearrange nodes on the screen. FNV was utilized as a component in several web-based systems, namely Genes2Networks, Lists2Networks, KEA, ChEA and PathwayGenerator. In addition, FVN can be used to embed pathways inside pdf files for the communication of pathways in soft publication materials.
FNV is available for use and download along with the supporting documentation and sample networks at http://www.maayanlab.net/FNV.
Full-textDOI: · Available from: Avi Ma'ayan, Apr 10, 2014
- SourceAvailable from: Johannes Tuikkala
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- "Conventionally, these layout algorithms are specifically designed for a particular network type, such as gene regulatory networks or signalling pathways [11,12], metabolic pathways or biochemical networks [13-15], or phylogenetic networks . Algorithmic solutions have also been introduced for specific network topologies, such as drawing fragmented networks , grid layouts , or detailed visualization of small networks . However, there exists no universal layout solution, and therefore a practical strategy involves trying out multiple layout algorithms a number of times to see which one best arranges a given network [6,20]. "
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ABSTRACT: Coexpression analysis is a powerful, widely used methodology for the investigation of underlying patterns in gene expression data. This "guilt-by-association" approach aims to find groups of genes with closely correlated expression profiles. Observation of consistent correlations across phenotypically diverse samples indicates that these genes have a shared function. We have recently described the application of weighted gene coexpression network analysis (WGCNA) to a 295 sample production CHO cell line microarray dataset and elucidated groups of genes related to growth rate and cell-specific productivity (Qp). In this study, we present the CHO gene coexpression database (CGCDB), a web-based system, designed specifically for researchers in the CHO community to provide user-friendly access to these gene-gene coexpression patterns. In addition to correlation between genes, the direct correlations between probesets and either growth rate or Qp are provided. Results are presented to the user via an interactive network diagram and in a downloadable tabular format. It is hoped that this resource will allow researchers to prioritize cell line engineering and/or biomarker candidates to enhance CHO-based cell culture for the production of biotherapeutics. Availability: www.cgcdb.org.Biotechnology and Bioengineering 06/2012; 109(6):1368-70. DOI:10.1002/bit.24416 · 4.13 Impact Factor
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