ReviewBriefings in functional genomics2026
Bioinformatics insights into plant genomic imprinting: approaches, challenges, and future perspectives.
Review in Briefings in functional genomics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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4 authors.
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Abstract
Genomic imprinting is an epigenetic occurrence that results in the expression of alleles specific to the parent of origin, plays pivotal roles in plant development, stress adaptation, and agronomic trait regulation. While imprinting has been intensively investigated in model plants (e.g. Arabidopsis, maize, and rice), its dynamic regulatory mechanisms and evolutionary implications remain enigmatic. Recent advances in bioinformatics-including single-cell omics, machine learning, and deep learning-have revolutionized the identification, functional annotation, and network modeling of imprinted genes. This review not only provides a detailed summary of the identification, functions and regulatory mechanisms of plant imprinted genes, but also systematically summarizes methodologies for studying plant genomic imprinting, highlights challenges in multi-omics data integration, and envisions artificial intelligence-driven strategies for epigenetic breeding.
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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 Socratic graph.