ArticlePlant biotechnology journal2021
KnetMiner: a comprehensive approach for supporting evidence-based gene discovery and complex trait analysis across species.
Article in Plant biotechnology journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 67 papers.
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Who cites it
67 citing papers in PubMed.
- From knowledge graph to topological data analysis: a novel framework to analyze gene regulatory networks for tomato-multi-pathogen interactions.The New phytologist · 2026Article
- Multi-locus GWAS to unravel the genetic architecture of grain iron, zinc and protein contents in wheat (Triticum aestivum L.) genotypes evaluated over multiple locations and years.BMC plant biology · 2026Article
- From chaos to clarity: schema-constrained AI for auditable biomedical evidence extraction from full-text PDFs.BMC medical research methodology · 2026Article
- Unlocking the genetic control of early seedling resistance to wheat powdery mildew through microphenomics.Pest management science · 2026Article
- Cross-residual knowledge graph learning for robust multi-trait gene-trait prioritization in rice.Frontiers in plant science · 2026Article
- Genetic dissection of the root system architecture QTLome and its relationship with early shoot development, breeding and adaptation in durum wheat.The plant genome · 2025Article
- Genetic Control of Grain Protein and Gluten Content: Winter vs. Spring Wheat.International journal of molecular sciences · 2025Article
- AgroLD: a knowledge graph for the plant sciences.BMC genomic data · 2025Article
- GWAS and haplotype analysis reveal the intricate interplay of hormones in rice seed germination under hypoxic conditions.3 Biotech · 2025Article
- Comprehensive analysis of genomic loci associated with glaucousness in wheat (Physiology and molecular biology of plants : an international journal of functional plant biology · 2025Article
- Integrating Artificial Intelligence in Next-Generation Sequencing: Advances, Challenges, and Future Directions.Current issues in molecular biology · 2025Review
- Accelerating crop improvement via integration of transcriptome-based network biology and genome editing.Planta · 2025Review
- White paper: standards for handling and analyzing plant pan-genomes.F1000Research · 2025Review
- Identification of universal grass genes and estimates of their monocot-/commelinid-/grass-specificity.Bioinformatics advances · 2025Article
- A conserved fungal Knr4/Smi1 protein is crucial for maintaining cell wall stress tolerance and host plant pathogenesis.PLoS pathogens · 2025Article
- Genome-wide association analysis of grain iron and zinc in rice grown under agroclimatic sites with contrasting soil iron status.Frontiers in plant science · 2025Article
- Comprehensive approaches to design efficient gRNA for SDN1-CRISPR/Cas9 genome editing in wheat.Frontiers in genome editing · 2025Article
- Lipidomics-based association study reveals genomic signatures of anti-cancer qualities of pigmented rice sprouts.Frontiers in plant science · 2025Article
- Genome-Wide Association Mapping of Macronutrient Mineral Accumulation in Wheat (Plants (Basel, Switzerland) · 2024Article
- AutoXAI4Omics: an automated explainable AI tool for omics and tabular data.Briefings in bioinformatics · 2024Article
7 more citing papers are in PubMed but not listed here.
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Authors and funding
9 authors.
Funding
Abstract
The generation of new ideas and scientific hypotheses is often the result of extensive literature and database searches, but, with the growing wealth of public and private knowledge, the process of searching diverse and interconnected data to generate new insights into genes, gene networks, traits and diseases is becoming both more complex and more time-consuming. To guide this technically challenging data integration task and to make gene discovery and hypotheses generation easier for researchers, we have developed a comprehensive software package called KnetMiner which is open-source and containerized for easy use. KnetMiner is an integrated, intelligent, interactive gene and gene network discovery platform that supports scientists explore and understand the biological stories of complex traits and diseases across species. It features fast algorithms for generating rich interactive gene networks and prioritizing candidate genes based on knowledge mining approaches. KnetMiner is used in many plant science institutions and has been adopted by several plant breeding organizations to accelerate gene discovery. The software is generic and customizable and can therefore be readily applied to new species and data types; for example, it has been applied to pest insects and fungal pathogens; and most recently repurposed to support COVID-19 research. Here, we give an overview of the main approaches behind KnetMiner and we report plant-centric case studies for identifying genes, gene networks and trait relationships in Triticum aestivum (bread wheat), as well as, an evidence-based approach to rank candidate genes under a large Arabidopsis thaliana QTL. KnetMiner is available at: https://knetminer.org.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.