scispace - formally typeset
D

David Kenigsbuch

Researcher at University of California, Los Angeles

Publications -  5
Citations -  498

David Kenigsbuch is an academic researcher from University of California, Los Angeles. The author has contributed to research in topics: Regulation of gene expression & Mutant. The author has an hindex of 3, co-authored 3 publications receiving 488 citations.

Papers
More filters
Journal ArticleDOI

A Myb-related transcription factor is involved in the phytochrome regulation of an Arabidopsis Lhcb gene.

TL;DR: It is concluded that the CCA1 protein is a key element in the functioning of the phytochrome signal transduction pathway leading to increased transcription of this Lhcb gene in Arabidopsis.
Journal ArticleDOI

A Region of the Arabidopsis Lhcb1*3 Promoter That Binds to CA-1 Activity Is Essential for High Expression and Phytochrome Regulation

TL;DR: It is concluded that information essential for both a high level of expression and phytochrome responsiveness is contained in a 27-bp region to which the CA-1 activity binds.
Journal ArticleDOI

A chimeric Lhcb::Nia gene: an inducible counter selection system for mutants in the phytochrome signal transduction pathway.

TL;DR: The construction of an inducible counter-selection system for mutants employing the enzyme nitrate reductase is reported, which should allow for the selection of mutants that are impaired in phytochrome regulation of the transcription of Lhcb genes.
Journal ArticleDOI

Hydroponic Agriculture and Microbial Safety of Vegetables: Promises, Challenges, and Solutions

TL;DR: In this article , a review summarizes the up-to-date knowledge regarding the microbial safety of hydroponically grown crops and discusses the role of the hydroponic system in reducing the microbial hazards for leafy and fruity crops as well as the potential risks for contamination by human pathogens.
Journal ArticleDOI

Novel fluorescence spectroscopy method coupled with N-PLS-R and PLS-DA models for the quantification of cannabinoids and the classification of cannabis cultivars.

TL;DR: In this paper , the performance of a novel fluorescence spectroscopy-based method coupled with N-way partial least squares regression (N-PLS-R) and partial least square discriminant analysis (PLSDA) models to replace the expensive chromatographic methods for preharvest cannabinoid quantification was evaluated.