What is

KnetMiner is a gene discovery platform that helps scientists search large volumes of scientific literature and bioscience knowledge to unveil links between the genetic and biological properties of complex, polygenic traits and diseases. It allows users to effectively integrate, search, visualise and share biological knowledge in an accessible, transparent, yet concise format that can be easily interrogated to generate new insights. The KnetMiner tools and resources can be readily applied to a wide range of organisms, datasets and use cases.

We support your journey from data to insights

With a set of mature software products for gene discovery and knowledge mining across species

Collaborative knowledge discovery

A collaboration platform for scientists to curate & share biological knowledge n...

Intelligent search of connected data

Sophisticated search engine for traversing complex biological information to fin...

Life knowledge at your fingertips

A BioJS component for the interactive visualization of biological knowledge netw...

Connecting the dots in life science data

Powerful platform to integrate & connect large volumes of biological information...

FAIR Knowledge Graphs for AI

Programmatic access for developers and data scientists to our FAIR knowledge gra...

Watch how it works

KnetMiner is a unique gene and gene network discovery platform powered by an integrated knowledge graph. It is used by scientists to better understand complex traits and identify novel candidate genes.

Free Resources

Developed as part of publicly funded initiatives to address sustainable development goals to transform our world.


With the wealth of genomic resources now available in wheat, having one place where we can query relationships across datasets and species is hugely important. With KnetMiner we can now visualise and access these relationships in a consistent and quick manner, meaning that our work on important agronomic traits is accelerated.

Prof Cristobal Uauy

John Innes Centre

Knetminer turns the predicted contents of genomes into a galaxy of knowns and unknowns that can be easily explored in infinite ways.

Prof Kim Hammond-Kosack

Rothamsted Research

I now train my students and collaborators how to extract data from NASA GeneLab and then feed into KnetMiner to understand the function of candidate genes in relation to spaceflight related stresses such as radiation and micro-gravity.

Dr Richard Barker

NASA, University of Wisconsin

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