ReviewPlant communications2022
Exploiting plant transcriptomic databases: Resources, tools, and approaches.
Review in Plant communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
18 citing papers in PubMed, 38 citations in OpenAlex.
- Haplotype-resolved telomere-to-telomere assembly and haplotype-aware annotation pipeline enable high-quality reannotation of threeHorticulture research · 2026Article
- Constructing gene co-functional and co-regulatory networks from public transcriptomes using condition-specific ensemble co-expression.Nature communications · 2026Article
- Ribozyme-Enabled Tissue Specificity (RETS): A System for Precise Gene Expression without Specialized Promoters.ACS synthetic biology · 2026Article
- Elucidating design principles for Ribozyme-Enabled Tissue Specificity (RETS) to allow precise expression without specialized promoters.bioRxiv : the preprint server for biology · 2025Article
- Comparative Transcriptome Reveals Conserved Gene Expression in Reproductive Organs in Solanaceae.International journal of molecular sciences · 2025Article
- Simulation study of factors affecting the accuracy of transcriptome models under complex environments.Plant molecular biology · 2025Article
- Accelerating crop improvement via integration of transcriptome-based network biology and genome editing.Planta · 2025Review
- Genome-wide identification and analysis of phosphate utilization related genes (PURs) reveal their roles involved in low phosphate responses in Brassica napus L.BMC plant biology · 2025Article
- Integration of biological and information technologies to enhance plant autoluminescence.The Plant cell · 2024Article
- Foliar mycobiome remains unaltered under urban air-pollution but differentially express stress-related genes.Microbial ecology · 2024Article
- Integration of metabolomics and transcriptomics reveals the regulation mechanism of the phenylpropanoid biosynthesis pathway in insect resistance traits inHorticulture research · 2024Article
- Topological data analysis reveals a core gene expression backbone that defines form and function across flowering plants.PLoS biology · 2023Article
- The miRNA-mRNA Regulatory Modules ofInternational journal of molecular sciences · 2023Article
- From Classical to Modern Computational Approaches to Identify Key Genetic Regulatory Components in Plant Biology.International journal of molecular sciences · 2023Review
- Transcriptomic and metabolomic characterization of antibacterial activity ofFrontiers in plant science · 2023Article
- Multiomics Molecular Research into the Recalcitrant and OrphanInternational journal of molecular sciences · 2022Review
- Gene Co-Expression Network Tools and Databases for Crop Improvement.Plants (Basel, Switzerland) · 2022Review
- Expression-based machine learning models for predicting plant tissue identity.Applications in plant sciencesArticle
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
There are now more than 300 000 RNA sequencing samples available, stemming from thousands of experiments capturing gene expression in organs, tissues, developmental stages, and experimental treatments for hundreds of plant species. The expression data have great value, as they can be re-analyzed by others to ask and answer questions that go beyond the aims of the study that generated the data. Because gene expression provides essential clues to where and when a gene is active, the data provide powerful tools for predicting gene function, and comparative analyses allow us to study plant evolution from a new perspective. This review describes how we can gain new knowledge from gene expression profiles, expression specificities, co-expression networks, differential gene expression, and experiment correlation. We also introduce and demonstrate databases that provide user-friendly access to these tools.
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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.