KnetMiner: a comprehensive approach for supporting evidence-based gene discovery and complex trait analysis across species

A - Papers appearing in refereed journals

Hassani-Pak, K., Singh, A., Brandizi, M., Hearnshaw, J., Parsons, J. D., Amberkar, S., Phillips, A. L., Doonan, J. H. and Rawlings, C. J. 2021. KnetMiner: a comprehensive approach for supporting evidence-based gene discovery and complex trait analysis across species. Plant Biotechnology Journal. https://doi.org/10.1111/pbi.13583

AuthorsHassani-Pak, K., Singh, A., Brandizi, M., Hearnshaw, J., Parsons, J. D., Amberkar, S., Phillips, A. L., Doonan, J. H. and Rawlings, C. J.
Abstract

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 a comprehensive approach to guide this technically challenging data integration task and to make knowledge discovery and hypotheses generation easier for plant and crop researchers. KnetMiner can digest large volumes of scientific literature and biological research to find and visualise links between the genetic and biological properties of complex traits and diseases. Here we report the main design principles behind KnetMiner and provide use cases for mining public datasets to identify unknown links between traits such grain colour and pre-harvest sprouting in Triticum aestivum, as well as, an evidence-based approach to identify candidate genes under an Arabidopsis thaliana petal size QTL. We have developed KnetMiner knowledge graphs and applications for a range of species including plants, crops and pathogens. KnetMiner is the first open-source gene discovery platform that can leverage genome-scale knowledge graphs, generate evidence-based biological networks and be deployed for any species with a sequenced genome. KnetMiner is available at http://knetminer.org.

KeywordsKnowledge graph; Interactive knowledge discovery; Exploratory data mining; Omics data integration; Candidate gene prioritization; Information visualisation; Systems biology
Year of Publication2021
JournalPlant Biotechnology Journal
Digital Object Identifier (DOI)https://doi.org/10.1111/pbi.13583
Web address (URL)https://onlinelibrary.wiley.com/doi/10.1111/pbi.13583
Open accessPublished as ‘gold’ (paid) open access
FunderBiotechnology and Biological Sciences Research Council
Funder project or codeDFW - Designing Future Wheat - Work package 4 (WP4) - Data access and analysis
DiseaseNetMiner - A novel tool for mining integrated biological networks of host and pathogen interaction
From data to knowledge / the ONDEX System for integrating Life Sciences data sources
BB/J004464/1
Publisher's version
Accepted author manuscript
Supplemental file
Output statusPublished
Publication dates
Online22 Mar 2021
Publication process dates
Accepted16 Mar 2021
PublisherWiley
ISSN1467-7644

Permalink - https://repository.rothamsted.ac.uk/item/98214/knetminer-a-comprehensive-approach-for-supporting-evidence-based-gene-discovery-and-complex-trait-analysis-across-species

7 total views
3 total downloads
2 views this month
1 downloads this month
Download files as zip