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David Kenneth Berger

Researcher at University of Pretoria

Publications -  67
Citations -  1627

David Kenneth Berger is an academic researcher from University of Pretoria. The author has contributed to research in topics: Gene & Transcription (biology). The author has an hindex of 23, co-authored 67 publications receiving 1457 citations. Previous affiliations of David Kenneth Berger include University of Cape Town & University of California, Berkeley.

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SND2, a NAC transcription factor gene, regulates genes involved in secondary cell wall development in Arabidopsis fibres and increases fibre cell area in Eucalyptus

TL;DR: This study supports a function for SND2 in the regulation of cellulose and hemicellulose biosynthetic genes in addition of those involved in lignin polymerization and signalling in the secondary cell wall transcriptional network.
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Role of integration host factor in stimulating transcription from the σ54-dependent nifH promoter

TL;DR: With purified NTRC and the substitution construct, it is demonstrated that stimulation by IHF in a purified transcription system was comparable to that in a crude coupled transcription-translation system, indicating that the stimulation in the crude system could be accounted for by I HF.
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Activity of purified NIFA, a transcriptional activator of nitrogen fixation genes.

TL;DR: MBP-NIFA had a broader nucleotide specificity than NTRC, being able to utilize pyrimidine in addition to purine nucleoside triphosphates and bound to the upstream activation sequence for the nifHDK promoter, as assessed by DNAse I footprinting.
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The isolated catalytic domain of NIFA, a bacterial enhancer-binding protein, activates transcription in vitro: activation is inhibited by NIFL

TL;DR: It is reported that the isolated central domain of NIFA activates transcription in vitro and that this activation requires NTP with a hydrolyzable beta-gamma bond, as does activation by intact NIFA.
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Spillover effects in epidemiology: parameters, study designs and methodological considerations.

TL;DR: The most widely used spillover parameters reported in the empirical literature into a standard notation are classified and standardizing spillover parameter nomenclature and articulating the causal inference assumptions required to estimate spillovers are described.