Artículos en revistas:
Identification and analysis of rice yield-related candidate genes by walking on the functional network
Identification and analysis of rice yield-related candidate genes by walking on the functional network
Año:2018
Áreas de investigación
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Inteligencia artificial
Datos
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Descripción
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| 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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Internacional
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Si |
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JCR del ISI
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Si |
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Título de la revista
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Frontiers in Plant Science |
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ISSN
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1664-462X |
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Factor de impacto JCR
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3,678 |
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Información de impacto
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Volumen
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DOI
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Número de revista
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Desde la página
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1 |
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Hasta la página
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9 |
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Mes
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SIN MES |
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Ranking
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Participantes
- Autor: Jing Jiang
- Autor: Fei Xing
- Autor: Chunyu Wang
- Autor: Xiangxiang Zeng . (UPM)
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
- Creador: Grupo de Investigación: Grupo de Inteligencia Artificial (LIA)
- Departamento: Inteligencia Artificial
S2i 2023 Observatorio de investigación @ UPM con la colaboración del Consejo Social UPM
Cofinanciación del MINECO en el marco del Programa INNPACTO (IPT-020000-2010-22)