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Kun-Hsiang Liu

Researcher at Harvard University

Publications -  5
Citations -  587

Kun-Hsiang Liu is an academic researcher from Harvard University. The author has contributed to research in topics: Phosphorylation & Mutant. The author has an hindex of 4, co-authored 5 publications receiving 372 citations. Previous affiliations of Kun-Hsiang Liu include Fujian Agriculture and Forestry University.

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Discovery of nitrate–CPK–NLP signalling in central nutrient–growth networks

TL;DR: This work reports unique Ca2+ signalling triggered by nitrate with live imaging of an ultrasensitive biosensor in Arabidopsis leaves and roots, which impair nitrate-stimulated system-wide shoot growth and root establishment.
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AGROBEST: an efficient Agrobacterium-mediated transient expression method for versatile gene function analyses in Arabidopsis seedlings

TL;DR: AGROBEST is a simple, fast, reliable, and robust transient expression system enabling high transient expression and transformation efficiency in Arabidopsis seedlings and offers a new way to dissect the molecular mechanisms involved in Agrobacterium-mediated DNA transfer.
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Dynamic Nutrient Signaling Networks in Plants.

TL;DR: In this paper, the authors review the multifaceted roles of sugar, nitrate, and phosphate as essential plant nutrients in controlling complex molecular and cellular mechanisms of dynamic signaling networks and highlight the dynamic nutrient, energy, growth, and stress signaling networks that orchestrate systemwide transcriptional, translational, and metabolic reprogramming, modulate growth and developmental programs, and respond to environmental cues.
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Primary nitrate responses mediated by calcium signalling and diverse protein phosphorylation

TL;DR: This review highlights recent findings that reveal key roles of cytosolic–nuclear calcium signalling and dynamic protein phosphorylation via diverse mechanisms in the primary nitrate response (PNR) and considers how phosphoproteomics approaches can contribute to the identification of putative regulatory protein kinases in the PNR.
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Targeted parallel sequencing of large genetically- defined genomic regions for identifying mutations in Arabidopsis

TL;DR: A streamlined method using parallel massive sequencing for mutant identification in which only targeted regions are sequenced, which is more cost-effective, straightforward enough to be easily done without specialized bioinformatics expertise, and reliable for identifying multiple mutations simultaneously.