Main logo
tutorial arrow
Create your own tool library
Bookmark tools and put favorites into folders to find them easily.



Unifies scientific workflows with graph databases for selecting relevant genes according to the evaluated biological systems. GeNNet is an integrated transcriptome analysis platform that includes pre-loaded biological data, pre-processes raw microarray data and conducts a series of analyses including normalization, differential expression inference, clusterization and geneset enrichment analysis. This platform integrates the analytical process of transcriptome data with graph database. It provides a comprehensive set of tools that would otherwise be challenging for non-expert users to install and use.

User report

tutorial arrow
Vote up tools and offer feedback
Give value to tools and make your expertise visible
Give your feedback on this tool
Sign up for free to join and share with the community

0 user reviews

0 user reviews

No review has been posted.

GeNNet forum

tutorial arrow
Communicate with other users
Participate in the forum to get support for using tools. Ask questions about technical specifications.
Take part in the discussion
Sign up for free to ask question and share your advices

No open topic.

GeNNet classification

GeNNet specifications

Software type:
Restrictions to use:
Programming languages:
Computer skills:
Command line interface
Operating system:
GNU General Public License version 3.0

GeNNet distribution


tutorial arrow
Upload and version your source code
Get a DOI for each update to improve tool traceability. Archive your releases so the community can easily visualize progress on your work.
Facilitate your tool traceability
Sign up for free to upload your code and get a DOI

No versioning.


GeNNet support



tutorial arrow
Promote your skills
Define all the tasks you managed and assign your profile the appropriate badges. Become an active member.
Promote your work
Sign up for free to badge your contributorship



National Institute of Cancer (INCA), Rio de Janeiro, Brazil; National Laboratory for Scientific Computing (LNCC), Petrópolis, Brazil; Oswaldo Cruz Foundation (Fiocruz), Rio de Janeiro, Brazil

Funding source(s)

This work has been supported by CAPES (Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior) and CNPq (Conselho Nacional de Desenvolvimento Cientfico e Tecnologico) funding.

Link to literature

By using OMICtools you acknowledge that you have read and accepted the terms of the end user license agreement.