KnetMiner - Intelligent search and visualisation of connected data to explain complex traits and diseases [article]

Keywan Hassani-Pak, Ajit Singh, Marco Brandizi, Joseph Hearnshaw, Andrew L Phillips, John H Doonan, Christopher Rawlings
2020 biorxiv/medrxiv   pre-print
Generating new ideas and scientific hypotheses is often the result of extensive literature and database reviews, overlaid with scientists' own novel data and a creative process of making connections that were not made before. We have developed software and resources to guide this technically challenging process and to make biological knowledge discovery quicker and easier for researchers. KnetMiner is a modern web-based resource that helps scientists mine the myriad of databases and datasets
more » ... t describe an organism's biology to present links between relevant pieces of information, such as genes, biological pathways, phenotypes and publications, providing leads for scientists who are investigating the molecular basis of a particular trait or disease. The KnetMiner tool ecosystem consists of open-source software to build, search, visualise, and manage biological knowledge in the form of knowledge graphs. KnetMiner can be easily developed and deployed for any species with a sequenced genome to provide a sophisticated search over connected data. Here, we describe the main design principles behind KnetMiner and demonstrate its utility with use-cases related to gene-trait discovery and candidate gene prioritization. KnetMiner is available at
doi:10.1101/2020.04.02.017004 fatcat:infoxkiv7fdchcivkmj4nnlpei