ArticleFrontiers in genetics2021
Using Network-Based Machine Learning to Predict Transcription Factors Involved in Drought Resistance.
Article in Frontiers in genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 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
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Who cites it
21 citing papers in PubMed, 43 citations in OpenAlex.
- SPIRAL: A versatile online single time-point circadian analysis platform for rice.Science advances · 2026Article
- Machine Learning-Guided Stress Atlases Reveal Co-Expression Rewiring and Divergent Cellular Deployment of Abiotic Stress Programs in Rice and Wheat.International journal of molecular sciences · 2026Article
- Expression profiles of transcription factors and aquaporins suggest putative roles in rubber biosynthesis regulation and drought stress adaptation in guayule.Scientific reports · 2026Article
- The emerging impact of CRISPR and gene editing on global crop improvement.Transgenic research · 2026Review
- Membrane stability under heat stress: molecular signaling, lipid remodeling, and defense mechanisms in plants.Plant cell reports · 2026Review
- Benchmarking ensemble and deep learning models for drought-responsive gene prioritisation in rice using multi-omics data.PloS one · 2026Article
- Recent Advances and Application of Machine Learning for Protein-Protein Interaction Prediction in Rice: Challenges and Future Perspectives.Proteomes · 2025Review
- Molecular Breeding for Abiotic Stress Tolerance in Crops: Recent Developments and Future Prospectives.International journal of molecular sciences · 2025Review
- Core Perturbomes ofPathogens (Basel, Switzerland) · 2025Article
- The Rice-Microbe Nexus: Unlocking Productivity Through Soil Science.Rice (New York, N.Y.) · 2025Review
- Universal features of alternative splicing and the regulatory roles of transcription factors in this process under diverse environmental stimuli in rice.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- Using supervised machine-learning approaches to understand abiotic stress tolerance and design resilient crops.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2025Review
- Mapping stress memory: genetic and epigenetic insights into combined drought and heat tolerance in barley.Plant cell reports · 2025Article
- Accelerating crop improvement via integration of transcriptome-based network biology and genome editing.Planta · 2025Review
- Review
- TCOD: an integrated resource for tropical crops.Nucleic acids research · 2024Article
- Current views of drought research: experimental methods, adaptation mechanisms and regulatory strategies.Frontiers in plant science · 2024Review
- Single-cell network biology characterizes cell type gene regulation for drug repurposing and phenotype prediction in Alzheimer's disease.PLoS computational biology · 2022Article
- New Data and New Features of the FunRiceGenes (Functionally Characterized Rice Genes) Database: 2021 Update.Rice (New York, N.Y.) · 2022Article
- DeepAProt: Deep learning based abiotic stress protein sequence classification and identification tool in cereals.Frontiers in plant science · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Gene regulatory networks underpin stress response pathways in plants. However, parsing these networks to prioritize key genes underlying a particular trait is challenging. Here, we have built the Gene Regulation and Association Network (GRAiN) of rice (
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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.