What is she best known for?
The fields of study she is best known for:
- Gene
- Internal medicine
- Genetics
Beverly A. Rothermel spends much of her time researching Internal medicine, Endocrinology, Calcineurin, Myocyte and Cell biology.
In Endocrinology, she works on issues like FOXO1, which are connected to FOXO3.
Her Calcineurin research includes themes of Phosphatase, Gene expression, In vivo and Skeletal muscle.
The concepts of her Myocyte study are interwoven with issues in Myocardial infarction, Biochemistry, Heart failure and Regeneration.
The Cell biology study which covers Autophagy that intersects with Protein aggregation.
Her studies deal with areas such as Programmed cell death and Pathogenesis as well as Pressure overload.
Her most cited work include:
- Cardiac autophagy is a maladaptive response to hemodynamic stress (568 citations)
- Regulation of neonatal and adult mammalian heart regeneration by the miR-15 family (461 citations)
- The oxygen-rich postnatal environment induces cardiomyocyte cell-cycle arrest through DNA damage response. (394 citations)
What are the main themes of her work throughout her whole career to date?
Beverly A. Rothermel mainly focuses on Cell biology, Internal medicine, Endocrinology, Calcineurin and Autophagy.
Her studies link Programmed cell death with Cell biology.
Muscle hypertrophy, Heart failure, Myocyte and Pressure overload are the subjects of her Internal medicine studies.
In her study, FOXO3 is strongly linked to FOXO1, which falls under the umbrella field of Endocrinology.
Her Calcineurin research also works with subjects such as
- Phosphatase, which have a strong connection to Skeletal muscle,
- Transcription factor that connect with fields like Molecular biology and Transcription.
Her study looks at the relationship between Autophagy and fields such as Disease, as well as how they intersect with chemical problems.
She most often published in these fields:
- Cell biology (39.26%)
- Internal medicine (37.04%)
- Endocrinology (30.37%)
What were the highlights of her more recent work (between 2015-2021)?
- Cell biology (39.26%)
- Calcineurin (29.63%)
- Mitochondrion (17.78%)
In recent papers she was focusing on the following fields of study:
Her primary areas of study are Cell biology, Calcineurin, Mitochondrion, Internal medicine and Heart failure.
Her Cell biology study often links to related topics such as Knockout mouse.
Her study in the field of NFAT is also linked to topics like Dynamics.
Her Mitochondrion study combines topics from a wide range of disciplines, such as Unfolded protein response, Phosphatase, Programmed cell death and Homeostasis.
Her Internal medicine research is multidisciplinary, incorporating perspectives in Endocrinology and Cardiology.
Her Heart failure research incorporates themes from Autophagy, Mitophagy and Bioinformatics.
Between 2015 and 2021, her most popular works were:
- Mitochondrial dynamics, mitophagy and cardiovascular disease (182 citations)
- Beclin-1-dependent autophagy protects the heart during sepsis (97 citations)
- Inhibition of class I histone deacetylases blunts cardiac hypertrophy through TSC2-dependent mTOR repression (44 citations)
In her most recent research, the most cited papers focused on:
- Gene
- Genetics
- Internal medicine
Her primary areas of investigation include Cell biology, Autophagy, Bioinformatics, Heart failure and Mitochondrion.
Her research on Autophagy also deals with topics like
- Cardiac dysfunction which intersects with area such as Pathogenesis,
- Downregulation and upregulation together with Myocyte.
Her Bioinformatics course of study focuses on Diabetic cardiomyopathy and Muscle hypertrophy.
Beverly A. Rothermel has included themes like Protein kinase A, Phosphorylation, Unfolded protein response, Endoplasmic reticulum and Programmed cell death in her Mitochondrion study.
Her research integrates issues of Endocrinology and Internal medicine in her study of Cell growth.
Her NFAT and Calcineurin study in the realm of Internal medicine interacts with subjects such as TRPC.
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.
