What is he best known for?
The fields of study he is best known for:
The scientist’s investigation covers issues in Cell biology, Embryonic stem cell, Abscisic acid, Induced pluripotent stem cell and Reprogramming.
Yang Zhao has included themes like Cell and Transcription factor, Gene, Cellular differentiation in his Cell biology study.
His Transcription factor study combines topics from a wide range of disciplines, such as Arabidopsis and Botany.
The concepts of his Embryonic stem cell study are interwoven with issues in Noggin and Cell type.
His studies deal with areas such as Kinase, Protein kinase A, Plant hormone, Phosphatase and Signal transduction as well as Abscisic acid.
Yang Zhao interconnects SOX2, Cell culture and Epigenetics in the investigation of issues within Induced pluripotent stem cell.
His most cited work include:
- Abscisic Acid Inhibits Type 2C Protein Phosphatases via the PYR/PYL Family of START Proteins (1734 citations)
- Pluripotent Stem Cells Induced from Mouse Somatic Cells by Small-Molecule Compounds (930 citations)
- Directed differentiation of human embryonic stem cells into functional hepatic cells. (571 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Cell biology, Abscisic acid, Arabidopsis, Signal transduction and Biochemistry.
Yang Zhao has researched Cell biology in several fields, including Reprogramming, Transcription factor, Mutant and Induced pluripotent stem cell.
His Reprogramming research is multidisciplinary, incorporating elements of SOX2, KLF4 and Somatic cell.
His Abscisic acid study also includes fields such as
- Phosphatase and related Plant hormone,
- Pyr1 which connect with Pyrabactin.
In his research, Senescence is intimately related to Botany, which falls under the overarching field of Arabidopsis.
Yang Zhao regularly ties together related areas like Phosphorylation in his Signal transduction studies.
He most often published in these fields:
- Cell biology (49.01%)
- Abscisic acid (34.44%)
- Arabidopsis (24.50%)
What were the highlights of his more recent work (between 2019-2021)?
- Cell biology (49.01%)
- Abscisic acid (34.44%)
- Plant growth (7.95%)
In recent papers he was focusing on the following fields of study:
Yang Zhao mainly focuses on Cell biology, Abscisic acid, Plant growth, Mutant and Germination.
In the subject of general Cell biology, his work in Signal transduction and Regenerative medicine is often linked to Re entrant, thereby combining diverse domains of study.
His Signal transduction research incorporates themes from Senescence, Kinase and Biosynthesis.
His Abscisic acid study frequently draws connections to adjacent fields such as Arabidopsis.
Many of his research projects under Arabidopsis are closely connected to Greening with Greening, tying the diverse disciplines of science together.
His Mutant research is multidisciplinary, relying on both Immune receptor, Gene expression and Cas9.
Between 2019 and 2021, his most popular works were:
- Abscisic acid dynamics, signaling, and functions in plants (110 citations)
- Abscisic acid dynamics, signaling, and functions in plants (110 citations)
- A RAF-SnRK2 kinase cascade mediates early osmotic stress signaling in higher plants (35 citations)
In his most recent research, the most cited papers focused on:
His primary areas of investigation include Abscisic acid, Cell biology, Germination, Plant growth and Signal transduction.
His Abscisic acid research is multidisciplinary, incorporating perspectives in Terminator and Arabidopsis thaliana, Pyr1.
The various areas that he examines in his Cell biology study include Human Induced Pluripotent Stem Cells, Calcium imaging and Directed differentiation.
His work carried out in the field of Germination brings together such families of science as Arabidopsis, ABI1 and Seedling.
The Plant growth study combines topics in areas such as Stress signaling, Senescence, Growth inhibition and Biosynthesis.
He combines subjects such as Osmotic pressure, Osmotic shock and Kinase, Protein kinase A with his study of Signal transduction.
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.
