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Haksong Pak

Researcher at Zhejiang University

Publications -  8
Citations -  90

Haksong Pak is an academic researcher from Zhejiang University. The author has contributed to research in topics: Methyl jasmonate & Gene. The author has an hindex of 3, co-authored 7 publications receiving 54 citations. Previous affiliations of Haksong Pak include Kim Il-sung University.

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The effect of exogenous methyl jasmonate on the flowering time, floral organ morphology, and transcript levels of a group of genes implicated in the development of oilseed rape flowers ( Brassica napus L.)

TL;DR: The results demonstrated that the combined actions of the floral identity genes, specifically BnAP1, BNAP2, Bn AP3, BmAG1, and BnPI3, were responsible for causing the different kinds of flower abnormalities previously undescribed in oilseed rape.
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Sequence, expression divergence, and complementation of homologous ALCATRAZ loci in Brassica napus

TL;DR: The sequence and expression divergence between the homologous ALCATRAZ loci in Brassica napus, responsible for silique dehiscence, is shown and it is indicated that BnaC.ALC.a was detectable in the siliques of B. napus.
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Creation of male-sterile lines that can be restored to fertility by exogenous methyl jasmonate for the establishment of a two-line system for the hybrid production of rice (Oryza sativa L.)

TL;DR: Results showed the successful generation of male‐sterile lines through the silencing of OsOPR7, the orthologous gene of Arabidopsis OPR3, in a field crop, paving the way for the establishment of a two‐line system for rice hybrid production.
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Genome-wide association study reveals a patatin-like lipase relating to the reduction of seed oil content in Brassica napus

TL;DR: In this paper, the authors applied a genome-wide association study (GWAS) on seed oil content (SOC) in a collection of 290 core germplasm accessions and identified BnaC07g30920D, a patatin-like lipase (PTL) gene, that was associated with SOC.
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Prediction of heterosis in the recent rapeseed (Brassica napus) polyploid by pairing parental nucleotide sequences.

TL;DR: In this article, the authors applied the genomic selection (GS) strategy and developed models that significantly increase the predictability of heterosis by introducing the concept of a regional parental genetic-similarity index (PGSI) and reducing dimension in the calculation matrix in a machine learning approach.