biorover logo             BioRover extracts relationship between genes, diseases and species from over 600 million sentences. These sentences are obtained from mover 20 million published articles.  



BioRover takes a gene or disease name as input and generated a list of related disease or genes. Related genes and diseases are extracted by identifying gene and disease named entities from sentences. A dictionary-based disease name tagger was developed to identify disease entities and gene names were identified using a machine-learning based tagger. BioRover also allows users to filter results based on sentence modalities negation and speculation, and genetic and epigenetic factors such as mutation, methylation, and phosphorylation. Negation and speculation are identified using a machine learning-based tagger.

Supporting this project

The most important requirement for the success of this project is availability of articles published without copyright restrictions, in other words, open access articles. The best way to support this project would be to publish your articles though one of the open access journals. A list of open access journals can be found at -


  More Questions? Email medicalfiguresearch <at> gmail <dot> com
Search powered by Lucene. Developed and hosted at UWM
This page might NOT be displayed correctly in Internet Explorer