BMTK: a toolkit for determining modules in biological bipartite networks

Background: Module detection is widely used to analyze and visualize biological networks. A number of methods and tools have been developed to achieve it. Meanwhile, bipartite module detection is also very useful for mining and analyzing bipartite biological networks and a few methods have been developed for it. However, there is few user-friendly toolkit for this task. Methods: To this end, we develop an online web toolkit BMTK, which implements seven existing methods. Results: BMTK provides a uniform operation platform and visualization function, standardizes input and output format, and improves algorithmic structure to enhance computing speed. We also apply this toolkit onto a drug-target bipartite network to demonstrate its effectiveness. Conclusions: BMTK will be a powerful tool for detecting bipartite modules in diverse bipartite biological networks. Availability: The web application is freely accessible at the website of Zhang lab.     

PATIKAmad: putting microarray data into pathway context

High-throughput experiments, most significantly DNA microarrays, provide us with system-scale profiles. Connecting these data with existing biological networks poses a formidable challenge to uncover facts about a cell's proteome. Studies and tools with this purpose are limited to networks with simple structure, such as protein-protein interaction graphs, or do not go much beyond than simply displaying values on the network. We have built a microarray data analysis tool, named PATIKAmad, which can be used to associate microarray data with the pathway models in mechanistic detail, and provides facilities for visualization, clustering, querying, and navigation of biological graphs related with loaded microarray experiments. PATIKAmad is freely available to noncommercial users as a new module of PATIKAweb at http://web.patika.org.     

Enabling dynamic network analysis through visualization in TVNViewer

ABSTRACT: BACKGROUND: Many biological processes are context-dependent or temporally specific. As a result, relationships between molecular constituents evolve across time and environments. While cutting-edge machine learning techniques can recover these networks, exploring and interpreting the rewiring behavior is challenging. Information visualization shines in this type of exploratory analysis, motivating the development of TVNViewer (http://sailing.cs.cmu.edu/tvnviewer), a visualization tool for dynamic network analysis. RESULTS: In this paper, we demonstrate visualization techniques for dynamic network analysis by using TVNViewer to analyze yeast cell cycle and breast cancer progression datasets. CONCLUSIONS: TVNViewer is a powerful new visualization tool for the analysis of biological networks that change across time or space.     

GLay: community structure analysis of biological networks

SUMMARY: GLay provides Cytoscape users an assorted collection of versatile community structure algorithms and graph layout functions for network clustering and structured visualization. High performance is achieved by dynamically linking highly optimized C functions to the Cytoscape JAVA program, which makes GLay especially suitable for decomposition, display and exploratory analysis of large biological networks. AVAILABILITY: http://brainarray.mbni.med.umich.edu/glay/.     

MetaNetter: inference and visualization of high-resolution metabolomic networks

SUMMARY: We present a Cytoscape plugin for the inference and visualization of networks from high-resolution mass spectrometry metabolomic data. The software also provides access to basic topological analysis. This open source, multi-platform software has been successfully used to interpret metabolomic experiments and will enable others using filtered, high mass accuracy mass spectrometric data sets to build and analyse networks. AVAILABILITY: http://compbio.dcs.gla.ac.uk/fabien/abinitio/abinitio.html     

MAVisto: a tool for the exploration of network motifs

SUMMARY: MAVisto is a tool for the exploration of motifs in biological networks. It provides a flexible motif search algorithm and different views for the analysis and visualization of network motifs. These views help to explore interesting motifs: the frequency of motif occurrences can be compared with randomized networks, a list of motifs along with information about structure and number of occurrences depending on the reuse of network elements shows potentially interesting motifs, a motif fingerprint reveals the overall distribution of motifs of a given size and the distribution of a particular motif in the network can be visualized using an advanced layout algorithm. AVAILABILITY: MAVisto is platform independent and available free of charge as a Java webstart application at http://mavisto.ipk-gatersleben.de/ CONTACT: schwoebb@ipk-gatersleben.de SUPPLEMENTARY INFORMATION: Can be found at http://mavisto.ipk-gatersleben.de/     

AVIS: AJAX viewer of interactive signaling networks

MOTIVATION: Increasing complexity of cell signaling network maps requires sophisticated visualization technologies. Simple web-based visualization tools can allow for improved data presentation and collaboration. Researchers studying cell signaling would benefit from having the ability to embed dynamic cell signaling maps in web pages. SUMMARY: AVIS is a Google gadget compatible web-based viewer of interactive cell signaling networks. AVIS is an implementation of AJAX (Asynchronous JavaScript with XML) with the usage of the libraries GraphViz, ImageMagic (PerlMagic) and overLib. AVIS provides web-based visualization of text-based signaling networks with dynamical zooming, panning and linking capabilities. AVIS is a cross-platform web-based tool that can be used to visualize network maps as embedded objects in any web page. AVIS was implemented for visualization of PathwayGenerator, a tool that displays over 4000 automatically generated mammalian cell signaling maps; NodeNeighborhood a tool to visualize first and second interacting neighbors of yeast and mammalian proteins; and for Genes2Networks, a tool to connect lists of genes and protein using background protein interaction networks. AVAILABILITY: A demo page of AVIS and links to applications and distributions can be found at http://actin.pharm.mssm.edu/AVIS2. Detailed instructions for using and configuring AVIS can be found in the user manual at http://actin.pharm.mssm.edu/AVIS2/manual.pdf.     

MetNetGE: interactive views of biological networks and ontologies

Background  

Linking high-throughput experimental data with biological networks is a key step for understanding complex biological systems. Currently, visualization tools for large metabolic networks often result in a dense web of connections that is difficult to interpret biologically. The MetNetGE application organizes and visualizes biological networks in a meaningful way to improve performance and biological interpretability.     

PiNGO: a Cytoscape plugin to find candidate genes in biological networks

PiNGO is a tool to screen biological networks for candidate genes, i.e. genes predicted to be involved in a biological process of interest. The user can narrow the search to genes with particular known functions or exclude genes belonging to particular functional classes. PiNGO provides support for a wide range of organisms and Gene Ontology classification schemes, and it can easily be customized for other organisms and functional classifications. PiNGO is implemented as a plugin for Cytoscape, a popular network visualization platform. AVAILABILITY: PiNGO is distributed as an open-source Java package under the GNU General Public License (http://www.gnu.org/), and can be downloaded via the Cytoscape plugin manager. A detailed user guide and tutorial are available on the PiNGO website (http://www.psb.ugent.be/esb/PiNGO.     

structureViz: linking Cytoscape and UCSF Chimera

structureViz is a Cytoscape plug-in that links the visualization of biological networks provided by Cytoscape with the visualization and analysis of macromolecular structures and sequences provided by UCSF Chimera. When combined with Cytoscape and Chimera, structureViz provides the first tool that links these two critical aspects of computational analysis in a straightforward manner. structureViz includes commands to open structures in Chimera and align them using Chimera's sequence-structure analysis tools. When a structure is opened, structureViz provides an alternative interface to Chimera: the Cytoscape Molecular Structure Navigator. This interface uses a tree-based paradigm to allow users to select and affect the display of models, chains and residues, mostly through the use of context menus.     

NetMatch: a Cytoscape plugin for searching biological networks

NetMatch is a Cytoscape plugin which allows searching biological networks for subcomponents matching a given query. Queries may be approximate in the sense that certain parts of the subgraph-query may be left unspecified. To make the query creation process easy, a drawing tool is provided. Cytoscape is a bioinformatics software platform for the visualization and analysis of biological networks. AVAILABILITY: The full package, a tutorial and associated examples are available at the following web sites: http://alpha.dmi.unict.it/~ctnyu/netmatch.html, http://baderlab.org/Software/NetMatch.     

A perspective for biomedical data integration: Design of databases for flow cytometry

Background

Biological signaling pathways that govern cellular physiology form an intricate web of tightly regulated interlocking processes. Data on these regulatory networks are accumulating at an unprecedented pace. The assimilation, visualization and interpretation of these data have become a major challenge in biological research, and once met, will greatly boost our ability to understand cell functioning on a systems level.

Results

To cope with this challenge, we are developing the SPIKE knowledge-base of signaling pathways. SPIKE contains three main software components: 1) A database (DB) of biological signaling pathways. Carefully curated information from the literature and data from large public sources constitute distinct tiers of the DB. 2) A visualization package that allows interactive graphic representations of regulatory interactions stored in the DB and superposition of functional genomic and proteomic data on the maps. 3) An algorithmic inference engine that analyzes the networks for novel functional interplays between network components. SPIKE is designed and implemented as a community tool and therefore provides a user-friendly interface that allows registered users to upload data to SPIKE DB. Our vision is that the DB will be populated by a distributed and highly collaborative effort undertaken by multiple groups in the research community, where each group contributes data in its field of expertise.

Conclusion

The integrated capabilities of SPIKE make it a powerful platform for the analysis of signaling networks and the integration of knowledge on such networks with omics data.     

LucidDraw: Efficiently visualizing complex biochemical networks within MATLAB

Background  

Biochemical networks play an essential role in systems biology. Rapidly growing network data and versatile research activities call for convenient visualization tools to aid intuitively perceiving abstract structures of networks and gaining insights into the functional implications of networks. There are various kinds of network visualization software, but they are usually not adequate for visual analysis of complex biological networks mainly because of the two reasons: 1) most existing drawing methods suitable for biochemical networks have high computation loads and can hardly achieve near real-time visualization; 2) available network visualization tools are designed for working in certain network modeling platforms, so they are not convenient for general analyses due to lack of broader range of readily accessible numerical utilities.     

Data-dependent visualization of biological networks in the web-browser with NDExEdit

Networks are a common methodology used to capture increasingly complex associations between biological entities. They serve as a resource of biological knowledge for bioinformatics analyses, and also comprise the subsequent results. However, the interpretation of biological networks is challenging and requires suitable visualizations dependent on the contained information. The most prominent software in the field for the visualization of biological networks is Cytoscape, a desktop modeling environment also including many features for analysis.A further challenge when working with networks is their distribution. Within a typical collaborative workflow, even slight changes of the network data force one to repeat the visualization step as well. Also, just minor adjustments to the visual representation not only need the networks to be transferred back and forth. Collaboration on the same resources requires specific infrastructure to avoid redundancies, or worse, the corruption of the data. A well-established solution is provided by the NDEx platform where users can upload a network, share it with selected colleagues or make it publicly available.NDExEdit is a web-based application where simple changes can be made to biological networks within the browser, and which does not require installation. With our tool, plain networks can be enhanced easily for further usage in presentations and publications. Since the network data is only stored locally within the web browser, users can edit their private networks without concerns of unintentional publication. The web tool is designed to conform to the Cytoscape Exchange (CX) format as a data model, which is used for the data transmission by both tools, Cytoscape and NDEx. Therefore the modified network can be directly exported to the NDEx platform or saved as a compatible CX file, additionally to standard image formats like PNG and JPEG.     

Cluster Viz:集成于Cytoscape的聚类可视化插件

生物网络中的聚类分析是功能模块识别及蛋白质功能预测的重要方法,聚类结果的可视化对于快速有效地分析生物网络结构也具有重要作用。通过分析生物网络显示和分析平台Cytoscape的架构,设计了一个使用方便的聚类分析和显示插件ClusterViz。这是一个可扩展的聚类算法的集成平台,可以不断增加其中的聚类算法,并对不同算法的结果进行比较分析,目前已实现了三种典型的算法实例。该插件能够成为蛋白质相互作用网络机理研究的一个有效工具。