2020
DOI: 10.1101/2020.04.02.017004
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KnetMiner: a comprehensive approach for supporting evidence-based gene discovery and complex trait analysis across species

Abstract: 12Generating new ideas and scientific hypotheses is often the result of extensive literature and 13 database reviews, overlaid with scientists' own novel data and a creative process of making 14 connections that were not made before. We have developed a comprehensive approach to guide 15 this technically challenging data integration task and to make knowledge discovery and 16 hypotheses generation easier for plant and crop researchers. KnetMiner can digest large volumes 17 of scientific literature and biologic… Show more

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Cited by 23 publications
(23 citation statements)
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References 49 publications
(45 reference statements)
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“…Our WGCNA co-expression network and GO enrichment data has been integrated with the wheat knowledge network [ 132 ] to make it publicly accessible in a larger biological context and to make it searchable through the KnetMiner web application (http://knetminer.rothamsted.ac.uk; [ 133 ]. KnetMiner can be searched with keywords (incl.…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…Our WGCNA co-expression network and GO enrichment data has been integrated with the wheat knowledge network [ 132 ] to make it publicly accessible in a larger biological context and to make it searchable through the KnetMiner web application (http://knetminer.rothamsted.ac.uk; [ 133 ]. KnetMiner can be searched with keywords (incl.…”
Section: Resultsmentioning
confidence: 99%
“…The term ‘weight value’ in the input files for Cytoscape refers to the connection strength between two nodes (genes) in terms of correlation value obtained from the topological overlap matrices (TOM). The co-expression network data has also been integrated with the wheat knowledge network [ 132 ] to make it publicly accessible through the KnetMiner web application (http://knetminer.rothamsted.ac.uk; [ 133 ]. The data was semantically modelled as nodes of type Gene, Co-Expression-Module, Co-Expression-Study, GOterm; connected by relations of type part-of and enriched.…”
Section: Methodsmentioning
confidence: 99%
“…For this, the identification of candidate genes that are expressed in drought-stress conditions is a major strategy, and genomic technologies such as microarray and transcriptomic analyses have been useful in the identification of these genes [ 101 , 128 ]. These technologies include new strategies in the identification of candidate genes associated with important agronomic traits in species with genome sequencing that have been developed as novel in-silico platforms for gene discovery and that help scientists to identify candidate genes through the knowledge available in genetic databases and public information, allowing candidate gene prioritization [ 129 ]. Although the advance of genomic technology has allowed the identification of QTLs for drought tolerance, this information has been underutilized in the generation of new cultivars with drought tolerance [ 113 ].…”
Section: Methods and Approaches To Improve Crop Tolerance To Drougmentioning
confidence: 99%
“…Several efforts have constructed KGs by ingesting and transforming scientific literature, 34,35 some with a few additional types of data also included, such as confirmed case and mortality data; 36 clinical information, drug trial, and sequencing data; 37 drug, drug trial and genome sequence data; 38 diseases, chemicals, and genes 39 . Other KG efforts ingest a wider array of data, including diseases, genes, proteins and their structural data, drugs, and drug side effects; 40 pathways, proteins, genes, drugs, diseases, anatomical terms, phenotypes, microbiome; 41 genes, proteins, diseases, phenotypes, genome sequences; 42,43 geographic, viral genes, genes and proteins. 44 Several projects have focused specifically on integrating a wide variety of COVID-19 data to create KGs to investigate drug repurposing.…”
Section: Comparison With Similar Projectsmentioning
confidence: 99%