CellBrowser is a web-based application that allows researchers to easily model, integrate, visualize and analyze biological networks. CellBrowser implements several networks and functional analysis, more and new analysis are easily integrated through the plugin framework developed. Some of the main features implemented include: importing local or remote files (most common formats are supported), loading attributes files for nodes and edges that allow researchers to filter and select subnetworks, several layouts available through Graphviz package, an analysis plugin framework to easily extend the core functionality, an user registration to save and store sessions remotely so users can work from several computers, ...

CellBrowser is implemented using HTML5 and SVG open standards, thus it runs in modern web browsers without any other plugin or technology such as Flash or Java Applets. Therefore, no installation or updates is needed, all computation is executed in our servers and biological data is taken from CellBase web services, so users can build up their networks from Reactome or IntAct data, or visualize rich widgets containing many relevant information about genes or proteins such as miRNA, TFBS or mutations. This architecture makes CellBrowser easily embeddable in any web application such as RENATO.


CellBrowser has been designed with these goals in mind:

  • 100% web-based using open standards such as HTML5 and SVG. No plugins or other technologies such as Flash or Java Applets are needed
  • to provide an user account registration that allow researchers to save their networks and analysis in the cloud, therefore data and analysis are available anywhere
  • some analysis can make an exhaustive use of CPU so all analysis are run in remote servers using a queue
  • to develop an application for modern mobile devices like tablets
  • to easily integrate and create biological networks, this is achieved by consuming CellBase web services which contain mos relevant biological information such as Ensembl core, Reactome, IntAct, Uniprot, miRNAs, TFBS, mutations, ...
  • allow researchers to load attributes data for nodes and edges, thus users can filter and select part of the networks
  • to develop an analysis plugin framework that will allow researchers to develop and integrate new analysis
  • to provide to the community with a web-based, open and embeddable solution to visualize biological networks, so researchers can focus in their analysis and methodologies
  • to license the code as GPLv2 and open the source code to the community through a Gitorius server

Why CellBrowser?

Most modern applications are being developed following the new cloud paradigm. Typical desktop applications lack of many interesting features that new technologies can offer. CellBrowser has been developed following this new paradigm, data and analysis lies in the cloud, meanwhile client application runs in the web browser.

This approach has some benefits when compared to other desktop solutions like Cytoscape: users are always updated and no local installation is needed, they can save session in the cloud and open in any other computer or mobile device, users can share data and work collaboratively, is very easy to integrate CellBrowser in a web page, everything is run in a remote server o cloud so users must not worry about high CPU analysis, ...


In the Tutorial you will learn how to use CellBrowser web application. Tutorial covers main functionality such as:
  • creating an account
  • user interface functionality
  • importing an existing network
  • how to build a custom network
  • importing an attribute file
  • running analysis plugins

A worked example has been developed...

Analysis plugins

A plugin framework has been developed to be able to add new analysis to CellBrowser. A complete plugin list can be found here Plugins. Analysis are mainly developed by us, but third-party developers are invited to add more plugins. Plugins have been organized into four categories:
  • Import: these plugins will permit researchers to import a network from a local or remote file, most common formats are allowed such us SIF. Users can also import Reactome networks.
  • Network analysis: these plugins will permit researchers to analyze network characteristics as topological parameters, to calculate dijkstra algorithm and to obtain the network cellular localization of the molecules as others network analysis plugins.
  • Functional Enrichment: these plugins will be related to analyze the functions that are represented in the network using Gene Ontology as reference and other databases as human gene-disease databases.
  • Pathway-based analysis: this section will contain the plugins related to KEGG pathways information.