What is he best known for?
The fields of study he is best known for:
Michael Koval mainly focuses on Cell biology, Intracellular, Endocytosis, Gap junction and Transfection.
Claudin is the focus of his Cell biology research.
Sphingomyelin is closely connected to Golgi apparatus in his research, which is encompassed under the umbrella topic of Intracellular.
His Endocytosis research includes elements of Phagocytosis, Drug delivery, Endothelium, ICAM-1 and Internalization.
His study looks at the intersection of Gap junction and topics like Cell signaling with Regulation of gene expression, Cell division, Gene expression, Cell and Cell culture.
In Transfection, he works on issues like In vitro, which are connected to Immunofluorescence, Membrane, Antiserum and Apposition.
His most cited work include:
- JAM-A regulates permeability and inflammation in the intestine in vivo. (344 citations)
- A novel endocytic pathway induced by clustering endothelial ICAM-1 or PECAM-1 (268 citations)
- Gap junctional communication modulates gene expression in osteoblastic cells (226 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Cell biology, Tight junction, Claudin, Lung and Connexin.
His studies in Cell biology integrate themes in fields like Transfection and Transmembrane protein.
His Tight junction study combines topics in areas such as Biophysics, Scaffold protein, Paracellular transport, Barrier function and Alveolar Epithelium.
Michael Koval works mostly in the field of Claudin, limiting it down to concerns involving Cell junction and, occasionally, Cell–cell interaction.
His Lung study incorporates themes from Immunology and Pathology.
His Connexin research integrates issues from Cell, Cell membrane, Plasma protein binding, Molecular biology and Transmembrane domain.
He most often published in these fields:
- Cell biology (62.80%)
- Tight junction (31.71%)
- Claudin (26.22%)
What were the highlights of his more recent work (between 2013-2021)?
- Cell biology (62.80%)
- Tight junction (31.71%)
- Claudin (26.22%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Cell biology, Tight junction, Claudin, Lung and Barrier function.
His research in Cell biology intersects with topics in Proinflammatory cytokine and Mitochondrial DNA.
His Tight junction research incorporates elements of Scaffold protein, Biophysics, Paracellular transport, Transmembrane protein and Alveolar Epithelium.
His study in Claudin is interdisciplinary in nature, drawing from both Occludin, Actin cytoskeleton, Cell junction, Molecular biology and Signal transduction.
He interconnects Immunology and Pathology in the investigation of issues within Lung.
His Barrier function research is multidisciplinary, incorporating elements of Inflammation, Junctional Adhesion Molecule A, Biochemistry and Asthma.
Between 2013 and 2021, his most popular works were:
- Claudins: Gatekeepers of lung epithelial function (85 citations)
- Mix and match: Investigating heteromeric and heterotypic gap junction channels in model systems and native tissues (71 citations)
- Proinflammatory cytokine-induced tight junction remodeling through dynamic self-assembly of claudins. (68 citations)
In his most recent research, the most cited papers focused on:
His primary areas of investigation include Cell biology, Claudin, Tight junction, Lung and Barrier function.
In most of his Cell biology studies, his work intersects topics such as Transmembrane protein.
His studies deal with areas such as Intestinal epithelium, Regulation of gene expression, Transcription factor and Cellular differentiation as well as Claudin.
He has included themes like Biophysics, Paracellular transport, Drug delivery, Integrin and Transdermal in his Tight junction study.
His Lung research is multidisciplinary, relying on both RNA and Immunology.
Michael Koval combines subjects such as Junctional Adhesion Molecule A and Biochemistry with his study of Barrier function.
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.
