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Updated: Feb 1, 2026

Author Spotlight: Streamlining Rice Breeding with CRISPR/Cas for Obtaining Optimal Phenotypic and Agronomic Traits
Published on: January 3, 2025
Identification and Analysis of Rice Yield-Related Candidate Genes by Walking on the Functional Network
Jing Jiang1, Fei Xing1, Chunyu Wang2
1School of Aerospace Engineering, Xiamen University, Xiamen, China.
Abstract:
Rice (Oryza sativa L.) is one of the most important staple foods in the world. It is possible to identify candidate genes associated with rice yield using the model of random walk with restart on a functional similarity network. We demonstrated the high performance of this approach by a five-fold cross-validation experiment, as well as the robustness of the parameter r. We also assessed the strength of associations between known seeds and candidate genes in the light of the results scores. The candidates ranking at the top of the results list were considered to be the most relevant rice yield-related genes. This study provides a valuable alternative for rice breeding and biology research. The relevant dataset and script can be downloaded at the website: http://lab.malab.cn/jj/rice.htm.
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