What is he best known for?
The fields of study Paolo Ascenzi is best known for:
Much of his study explores Biochemistry relationship to Cysteine.
Borrowing concepts from Enzyme, he weaves in ideas under Cysteine.
His research on Enzyme frequently connects to adjacent areas such as Hemeprotein.
While working on this project, he studies both Hemeprotein and Heme.
He integrates many fields, such as Heme and Globin, in his works.
Paolo Ascenzi merges many fields, such as Globin and Neuroglobin, in his writings.
Paolo Ascenzi performs multidisciplinary study on Neuroglobin and Hemoglobin in his works.
Paolo Ascenzi undertakes interdisciplinary study in the fields of Hemoglobin and Myoglobin through his research.
His Myoglobin study often links to related topics such as Biochemistry.
His most cited work include:
- Human serum albumin: From bench to bedside (1142 citations)
- Estrogen Signaling Multiple Pathways to Impact Gene Transcription (486 citations)
- Structure–function relationship of estrogen receptor α and β: Impact on human health (432 citations)
What are the main themes of his work throughout his whole career to date
Paolo Ascenzi integrates Biochemistry with Cell biology in his study.
In his works, Paolo Ascenzi undertakes multidisciplinary study on Cell biology and Biochemistry.
He performs multidisciplinary study in Enzyme and Myoglobin in his work.
His work on Ferrous expands to the thematically related Organic chemistry.
He integrates many fields, such as Stereochemistry and Enzyme, in his works.
He merges Heme with Hemeprotein in his research.
Paolo Ascenzi conducts interdisciplinary study in the fields of Gene and Genetics through his works.
He integrates Genetics and Gene in his research.
In his works, he conducts interdisciplinary research on Receptor and Ligand (biochemistry).
Paolo Ascenzi most often published in these fields:
- Biochemistry (79.56%)
- Enzyme (61.56%)
- Organic chemistry (44.00%)
What were the highlights of his more recent work (between 2018-2022)?
- Biochemistry (72.73%)
- Enzyme (33.33%)
- Genetics (30.30%)
In recent works Paolo Ascenzi was focusing on the following fields of study:
Paolo Ascenzi regularly links together related areas like Human serum albumin in his Biochemistry studies.
Borrowing concepts from Myoglobin, Paolo Ascenzi weaves in ideas under Enzyme.
With his scientific publications, his incorporates both Genetics and Cancer research.
Paolo Ascenzi undertakes interdisciplinary study in the fields of Cancer research and Genetics through his works.
He performs integrative study on Gene and Computational biology in his works.
He performs multidisciplinary study in Cell biology and Gene in his work.
Many of his studies on Organic chemistry involve topics that are commonly interrelated, such as Dissociation (chemistry).
He regularly ties together related areas like Organic chemistry in his Dissociation (chemistry) studies.
He conducts interdisciplinary study in the fields of Heme and Hemeprotein through his research.
Between 2018 and 2022, his most popular works were:
- Role of proteolytic enzymes in the COVID-19 infection and promising therapeutic approaches (69 citations)
- Haptoglobin: From hemoglobin scavenging to human health (47 citations)
- Serum Albumin: A Multifaced Enzyme (47 citations)
In his most recent research, the most cited works focused on:
His Stage (stratigraphy) study deals with Paleontology intersecting with Context (archaeology).
His Context (archaeology) study frequently draws connections to other fields, such as Paleontology.
His work on Proteolytic enzymes expands to the thematically related Biochemistry.
Cell biology is closely attributed to Function (biology) in his work.
Paolo Ascenzi regularly links together related areas like Cell biology in his Function (biology) studies.
Paolo Ascenzi applies his multidisciplinary studies on Computational biology and DNA in his research.
Paolo Ascenzi connects DNA with Computational biology in his study.
He integrates several fields in his works, including Pathology and Radiology.
Paolo Ascenzi combines Radiology and Pathology in his studies.
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.
