ReviewPlants (Basel, Switzerland)2023
Integrated Molecular and Bioinformatics Approaches for Disease-Related Genes in Plants.
Review in Plants (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed, 16 citations in OpenAlex.
- Genomics in plant pathogen identification and control.Frontiers in plant science · 2025Review
- Genetic Databases and Gene Editing Tools for Enhancing Crop Resistance against Abiotic Stress.Biology · 2023Review
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 2 institutions in 2 countries.
Funding
Abstract
Modern plant pathology relies on bioinformatics approaches to create novel plant disease diagnostic tools. In recent years, a significant amount of biological data has been generated due to rapid developments in genomics and molecular biology techniques. The progress in the sequencing of agriculturally important crops has made it possible to develop a better understanding of plant-pathogen interactions and plant resistance. The availability of host-pathogen genome data offers effective assistance in retrieving, annotating, analyzing, and identifying the functional aspects for characterization at the gene and genome levels. Physical mapping facilitates the identification and isolation of several candidate resistance (R) genes from diverse plant species. A large number of genetic variations, such as disease-causing mutations in the genome, have been identified and characterized using bioinformatics tools, and these desirable mutations were exploited to develop disease resistance. Moreover, crop genome editing tools, namely the CRISPR (clustered regulatory interspaced short palindromic repeats)/Cas9 (CRISPR-associated) system, offer novel and efficient strategies for developing durable resistance. This review paper describes some aspects concerning the databases, tools, and techniques used to characterize resistance (R) genes for plant disease management.
Indexed as
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.