The genetic architecture of heterochrony as a quantitative trait: lessons from a computational model.

Sun, Lidan; Sang, Mengmeng; Zheng, Chenfei; Wang, Dongyang; Shi, Hexin; Liu, Kaiyue; Guo, Yanfang; Cheng, Tangren; Zhang, Qixiang; Wu, Rongling

Sun, Lidan; Sang, Mengmeng; Zheng, Chenfei; Wang, Dongyang; Shi, Hexin; Liu, Kaiyue; Guo, Yanfang; Cheng, Tangren; Zhang, Qixiang; Wu, Rongling.

Affiliation

Sun L; Beijing Key Laboratory of Ornamental Plants Germplasm Innovation and Molecular Breeding, National Engineering Research Center for Floriculture at Beijing Forestry University.
Sang M; Computational Genetics in the Center for Computational Biology at Beijing Forestry University.
Zheng C; Computational Genetics in the Center for Computational Biology at Beijing Forestry University.
Wang D; Computational Biology Center for Computational Biology at Beijing Forestry University.
Shi H; Computational Biology Center for Computational Biology at Beijing Forestry University.
Liu K; Computational Biology Center for Computational Biology at Beijing Forestry University.
Guo Y; Computational Biology Center for Computational Biology at Beijing Forestry University.
Cheng T; National Engineering Research Center for Floriculture at Beijing Forestry University.
Zhang Q; National Engineering Research Center for Floriculture at Beijing Forestry University.
Wu R; Center for Computational Biology at Beijing Forestry University.

Brief Bioinform ; 19(6): 1430-1439, 2018 11 27.

Article in En | MEDLINE | ID: mdl-28575183

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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Computer Simulation / Quantitative Trait Loci Type of study: Prognostic_studies Limits: Animals Language: En Journal: Brief Bioinform Journal subject: BIOLOGIA / INFORMATICA MEDICA Year: 2018 Document type: Article

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