What is she best known for?
The fields of study she is best known for:
Daphne Preuss mainly focuses on Arabidopsis, Pollen, Cell biology, Pollen tube and Genetics.
Gene covers Daphne Preuss research in Arabidopsis.
To a larger extent, she studies Botany with the aim of understanding Pollen.
Her research integrates issues of Ovule, Sperm, Gametophyte and Gynoecium in her study of Pollen tube.
In her research, Human fertilization is intimately related to Double fertilization, which falls under the overarching field of Gynoecium.
As a part of the same scientific family, Daphne Preuss mostly works in the field of Pollen hydration, focusing on Pollen adhesion and, on occasion, Pollen-pistil interaction and Callose.
Her most cited work include:
- Sequence and analysis of chromosome 2 of the plant Arabidopsis thaliana (706 citations)
- Pollen tube growth and guidance is regulated by POP2, an Arabidopsis gene that controls GABA levels. (410 citations)
- Pollen tube growth and guidance is regulated by POP2, an Arabidopsis gene that controls GABA levels. (410 citations)
What are the main themes of her work throughout her whole career to date?
Genetics, Arabidopsis, Pollen, Centromere and Pollen tube are her primary areas of study.
Daphne Preuss focuses mostly in the field of Arabidopsis, narrowing it down to matters related to Peptide sequence and, in some cases, Locus.
Her Pollen study integrates concerns from other disciplines, such as Biochemistry and Cell biology.
The concepts of her Centromere study are interwoven with issues in Transgene, Recombinant DNA, DNA, Transformed cell and Heterochromatin.
Her Pollen tube research includes elements of Ovule, Sperm and Gametophyte.
Her Sperm study combines topics from a wide range of disciplines, such as Ploidy and Gynoecium.
She most often published in these fields:
- Genetics (58.25%)
- Arabidopsis (42.72%)
- Pollen (31.07%)
What were the highlights of her more recent work (between 2007-2016)?
- Pollen (31.07%)
- Genetics (58.25%)
- Biochemistry (10.68%)
In recent papers she was focusing on the following fields of study:
Her primary areas of investigation include Pollen, Genetics, Biochemistry, Centromere and Botany.
Her Pollen research is multidisciplinary, relying on both Arabidopsis and Mutant.
Her studies deal with areas such as Arabidopsis thaliana and Genetic screen as well as Arabidopsis.
The various areas that Daphne Preuss examines in her Centromere study include Transformed cell, Plant cell, Homologous chromosome and Recombinant DNA.
Daphne Preuss is involved in the study of Botany that focuses on Pollen tube in particular.
Her Pollen tube research focuses on Ovule and how it relates to Biophysics.
Between 2007 and 2016, her most popular works were:
- CYP704B1 Is a Long-Chain Fatty Acid ω-Hydroxylase Essential for Sporopollenin Synthesis in Pollen of Arabidopsis (210 citations)
- LAP5 and LAP6 Encode Anther-Specific Proteins with Similarity to Chalcone Synthase Essential for Pollen Exine Development in Arabidopsis (152 citations)
- GABA accumulation causes cell elongation defects and a decrease in expression of genes encoding secreted and cell wall-related proteins in Arabidopsis thaliana. (86 citations)
In her most recent research, the most cited papers focused on:
The scientist’s investigation covers issues in Biochemistry, Pollen, Mutant, Sporopollenin and Arabidopsis.
As part of one scientific family, she deals mainly with the area of Biochemistry, narrowing it down to issues related to the Pollen tube, and often Brassicaceae, Lipid metabolism and Ovule.
The study incorporates disciplines such as Flavonoid biosynthesis, Stamen and Pollen exine formation in addition to Sporopollenin.
Her Arabidopsis research entails a greater understanding of Genetics.
Her biological study spans a wide range of topics, including Microarray analysis techniques, Gene expression, Regulation of gene expression and Cell biology.
Daphne Preuss has researched Pollen hydration in several fields, including Sexual reproduction, Immunology, Antigen, Germination and Sperm.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
