What is he best known for?
The fields of study he is best known for:
- Enzyme
- Biochemistry
- Amino acid
The scientist’s investigation covers issues in Receptor, Melanocortin, Endocrinology, Internal medicine and Melanocortin receptor.
The Receptor study combines topics in areas such as Ventral tegmental area, Stereochemistry and Pharmacology.
His Melanocortin research is mostly focused on the topic Melanocortin 3 receptor.
His research on Endocrinology frequently links to adjacent areas such as Antagonist.
His work on Melanocyte-stimulating hormone, Anorectic and Adrenocorticotropic hormone as part of general Internal medicine research is frequently linked to Zona reticularis, thereby connecting diverse disciplines of science.
His Melanocortin receptor research incorporates elements of Biophysics and Radioligand.
His most cited work include:
- New aspects on the melanocortins and their receptors (294 citations)
- Loss of function mutations of the human melanocortin 1 receptor are common and are associated with red hair. (220 citations)
- Melanocortin receptors: perspectives for novel drugs. (172 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Receptor, Internal medicine, Melanocortin, Endocrinology and Biochemistry.
Jarl E. S. Wikberg has included themes like Molecular biology, Stereochemistry, Pharmacology and Cell biology in his Receptor study.
His work on Melanocortin receptor, Melanocortin 3 receptor and Melanocortins as part of general Melanocortin study is frequently connected to Melanocortin 1 receptor, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
His Melanocortin 3 receptor research is multidisciplinary, incorporating perspectives in Radioligand Assay, Enzyme-linked receptor and COS cells.
His study on Endocrinology is mostly dedicated to connecting different topics, such as Orexigenic.
His study looks at the relationship between Biochemistry and fields such as Dengue virus, as well as how they intersect with chemical problems.
He most often published in these fields:
- Receptor (36.44%)
- Internal medicine (29.78%)
- Melanocortin (29.78%)
What were the highlights of his more recent work (between 2012-2019)?
- Quantitative structure–activity relationship (6.67%)
- Computational biology (10.67%)
- Immunology (4.00%)
In recent papers he was focusing on the following fields of study:
Jarl E. S. Wikberg mainly investigates Quantitative structure–activity relationship, Computational biology, Immunology, Biochemistry and Phragmalin.
Jarl E. S. Wikberg combines subjects such as Drug, Drug repositioning, Decision tree, External validation and Drug discovery with his study of Computational biology.
Immunology is closely attributed to Melanocortin in his study.
Melanocortin is a subfield of Receptor that Jarl E. S. Wikberg studies.
His study focuses on the intersection of Biochemistry and fields such as Dengue virus with connections in the field of NS3, Substrate and Molecular biology.
Jarl E. S. Wikberg interconnects Sexual dysfunction, Stereochemistry, Semisynthesis and Neobeguea mahafalensis in the investigation of issues within Phragmalin.
Between 2012 and 2019, his most popular works were:
- Roles of d-Amino Acids on the Bioactivity of Host Defense Peptides (36 citations)
- HemoPred: a web server for predicting the hemolytic activity of peptides. (34 citations)
- A unified proteochemometric model for prediction of inhibition of cytochrome p450 isoforms. (31 citations)
In his most recent research, the most cited papers focused on:
- Enzyme
- Biochemistry
- Amino acid
His primary areas of investigation include Biochemistry, Web server, Data mining, Quantitative structure–activity relationship and Support vector machine.
His study in the field of Amino acid, D-amino acid and Innate immune system also crosses realms of Anticancer peptide and Broad spectrum.
His Data curation study in the realm of Data mining interacts with subjects such as Signature.
His Quantitative structure–activity relationship study combines topics in areas such as Acetylcholinesterase inhibitor, Acetylcholinesterase, Neuroscience, Cholinergic and Dementia.
His work in Support vector machine covers topics such as Decision tree which are related to areas like Computational biology and Genetics.
His work deals with themes such as Chemogenomics, Bioinformatics and Drug repositioning, which intersect with Computational biology.
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.
