Identification and Analysis of Rice Yield-Related Candidate Genes by Walking on the Functional Network.

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

5 citing papers in PubMed, 8 citations in OpenAlex.

1. Accelerating crop improvement via integration of transcriptome-based network biology and genome editing.Planta · 2025
   Review
2. New insights into QTNs and potential candidate genes governing rice yield via a multi-model genome-wide association study.BMC plant biology · 2024
   Article
3. MILNP: Plant lncRNA-miRNA Interaction Prediction Based on Improved Linear Neighborhood Similarity and Label Propagation.Frontiers in plant science · 2022
   Article
4. Unraveling the genomic regions controlling the seed vigour index, root growth parameters and germination per cent in rice.PloS one · 2022
   Article
5. An efficient RGB-UAV-based platform for field almond tree phenotyping: 3-D architecture and flowering traits.Plant methods · 2019
   Article

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 1 country.

Funding

No grant is acknowledged in the PubMed record.

Abstract

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