Publications Archives - KnetMiner

Our Publications

Selected Citations

Molero et al. (2022). Exotic alleles contribute to heat tolerance in wheat under field conditions. bioRxiv.

Morales et al. (2022). Breedbase: a digital ecosystem for modern plant breeding. Oxford Academic's G3.

Condorelli et al. (2022). Genome Wide Association Study Uncovers the QTLome for Osmotic Adjustment and Related Drought Adaptive Traits in Durum Wheat. genes.

Sharma et al. (2022). Genome-wide identification, characterization and expression analysis of the BRI1 gene family in Triticum aestivum L.. Plant Biotechnology Reports.

Urban et al. (2021). PHI-base in 2022: a multi-species phenotype database for Pathogen–Host Interactions. Oxford Academic's Nucleic Acids Research.

Williamson et al. (2021). Data management challenges for artificial intelligence in plant and agricultural research. F1000.

Joynson et al. (2021). Uncovering candidate genes involved in photosynthetic capacity using unexplored genetic variation in Spring Wheat. Plant Biotechnology Journal.

Shao et al. (2021). Apical-root apoplastic acidification affects cell wall extensibility in wheat under salinity stress. Physiologia Plantarum.

Mawkhiew et al. (2021). Gene-to-trait knowledge graphs show association of plant photoreceptors with physiological and developmental processes that can confer agronomic benefits. Genetic Resources and Crop Evolution.

Matthew Hutson (2020). Artificial-intelligence tools aim to tame the coronavirus literature. Nature.

Harrington et al. (2020). The Wheat GENIE3 Network Provides Biologically-Relevant Information in Polyploid Wheat. G3: GENES, GENOMES, GENETICS

Adamski et al. (2020). A roadmap for gene functional characterisation in crops with large genomes: Lessons from polyploid wheat. eLife.

Lyra et al. (2020). Gene-based mapping of trehalose biosynthetic pathway genes reveals association with source- and sink-related yield traits in a spring wheat panel. bioRxiv

Rosero et al. (2020). A Dual Strategy of Breeding for Drought Tolerance and Introducing Drought-Tolerant, Underutilized Crops into Production Systems to Enhance Their Resilience to Water Deficiency. Plants

Mukhtar et al. (2020). Analysis and Evaluation of COVID-19 Web Applications for Health Professionals: Challenges and Opportunities. Healthcare.

Emebiri et al. (2020). Synthetic hexaploid wheat as a source of novel genetic loci for aluminium tolerance. Euphytica.

Alabdullah et al. (2019). A Co-Expression Network in Hexaploid Wheat Reveals Mostly Balanced Expression and Lack of Significant Gene Loss of Homeologous Meiotic Genes Upon Polyploidization. Frontiers in Plant Science.

Lab publications

Brandizi et al. (2022). Integrative Data Analysis and Exploratory Data Mining in Biological Knowledge Graphs. Integrative Bioinformatics. Springer, Singapore.

Hassani-Pak et al. (2021). KnetMiner: a comprehensive approach for supporting evidence-based gene discovery and complex trait analysis across species. Plant Biotechnology Journal

Hearnshaw et al. (2021). Organizing knowledge to enable faster data interpretation in COVID-19 research. F1000Research

Brandizi et al. (2018). Getting the best of Linked Data and Property Graphs: rdf2neo and the KnetMiner Use Case. SWAT4LS Paper Proceedings.

Brandizi et al. (2018). Towards FAIRer Biological Knowledge Networks Using a Hybrid Linked Data and Graph Database Approach. Journal of Integrative Bioinformatics.

Singh et al. (2018). KnetMaps: a BioJS component to visualize biological knowledge networks. F1000 Research.

Hassani-Pak K and Rawlings C. (2017). Knowledge Discovery in Biological Databases for Revealing Candidate Genes Linked to Complex Phenotypes. Journal of Integrative Bioinformatics.

Hassani-Pak et al. (2016). Developing integrated crop knowledge networks to advance candidate gene discovery. Applied & Translational Genomics.

Lysenko et al. (2011). Assessing the functional coherence of modules found in multiple-evidence networks from Arabidopsis. BMC Bioinformatics.

Hassani-Pak et al. (2010). Enhancing Data Integration with Text Analysis to Find Proteins Implicated in Plant Stress Response. Journal of Integrative Bioinformatics.

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