ReviewPlants (Basel, Switzerland)2024
Harnessing Multi-Omics Strategies and Bioinformatics Innovations for Advancing Soybean Improvement: A Comprehensive Review.
Review in Plants (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed.
- Integrating multi-omics with regular analyses to elucidate the effects of ZnO nanomaterials on improving soybean quality.Bioresources and bioprocessing · 2026Article
- Advancing Soybean Improvement: Multi-Omics Strategies, Cutting-Edge Techniques, and Bioinformatics Innovations.Plants (Basel, Switzerland) · 2026Article
- Improved Cultivars and the Application of Combined Fertilizer Improve the Grain Yield and the Nitrogen Uptake and Utilization in Continuously Cropped Soybean (Plants (Basel, Switzerland) · 2026Article
- Harnessing multi-omics and genome-editing technologies for climate-resilient agriculture: bridging AI-driven insights with sustainable crop improvement.Plant molecular biology · 2025Review
- CRISPR/Cas-Mediated Optimization of Soybean Shoot Architecture for Enhanced Yield.International journal of molecular sciences · 2025Review
- Multi-omics approaches: transforming the landscape of natural product isolation.Functional & integrative genomics · 2025Review
- Integrative Approaches to Soybean Resilience, Productivity, and Utility: A Review of Genomics, Computational Modeling, and Economic Viability.Plants (Basel, Switzerland) · 2025Review
- Integrated transcriptomic and metabolomic analysis reveals developmental stage-specific molecular responses to phosphorus deficiency in soybean.Frontiers in plant science · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Soybean improvement has entered a new era with the advent of multi-omics strategies and bioinformatics innovations, enabling more precise and efficient breeding practices. This comprehensive review examines the application of multi-omics approaches in soybean-encompassing genomics, transcriptomics, proteomics, metabolomics, epigenomics, and phenomics. We first explore pre-breeding and genomic selection as tools that have laid the groundwork for advanced trait improvement. Subsequently, we dig into the specific contributions of each -omics field, highlighting how bioinformatics tools and resources have facilitated the generation and integration of multifaceted data. The review emphasizes the power of integrating multi-omics datasets to elucidate complex traits and drive the development of superior soybean cultivars. Emerging trends, including novel computational techniques and high-throughput technologies, are discussed in the context of their potential to revolutionize soybean breeding. Finally, we address the challenges associated with multi-omics integration and propose future directions to overcome these hurdles, aiming to accelerate the pace of soybean improvement. This review serves as a crucial resource for researchers and breeders seeking to leverage multi-omics strategies for enhanced soybean productivity and resilience.
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Identifiers
What OpenQuestion holds
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.