What is he best known for?
The fields of study he is best known for:
- Enzyme
- Amino acid
- Biochemistry
Michael W. Pennington spends much of his time researching Potassium channel, Peptide, Pharmacology, Stichodactyla helianthus and Potassium channel blocker.
His research integrates issues of Toxin, Biochemistry and Cell biology in his study of Potassium channel.
The Peptide study combines topics in areas such as Amino acid, Stereochemistry and Venom.
His Pharmacology research incorporates themes from Experimental autoimmune encephalomyelitis, Endocrinology, Internal medicine and Channel blocker.
His Stichodactyla helianthus study integrates concerns from other disciplines, such as Cell culture, Autoimmunity and Flow cytometry.
Potassium channel blocker and Effector are frequently intertwined in his study.
His most cited work include:
- Kv1.3 channels are a therapeutic target for T cell-mediated autoimmune diseases (410 citations)
- K+ channels as targets for specific immunomodulation. (388 citations)
- The voltage-gated Kv1.3 K+ channel in effector memory T cells as new target for MS (366 citations)
What are the main themes of his work throughout his whole career to date?
Michael W. Pennington mainly focuses on Potassium channel, Peptide, Stereochemistry, Biochemistry and Stichodactyla helianthus.
His work carried out in the field of Potassium channel brings together such families of science as Toxin, Cell biology, Effector and Pharmacology.
In his study, Calcium signaling is strongly linked to Immunology, which falls under the umbrella field of Cell biology.
His Pharmacology research is multidisciplinary, incorporating perspectives in In vitro, Rheumatoid arthritis and Immune system.
His study explores the link between Peptide and topics such as Residue that cross with problems in Tyrosine.
In his research, Protease is intimately related to Cleavage, which falls under the overarching field of Stereochemistry.
He most often published in these fields:
- Potassium channel (36.76%)
- Peptide (30.88%)
- Stereochemistry (29.41%)
What were the highlights of his more recent work (between 2016-2020)?
- Potassium channel (36.76%)
- Pharmacology (15.44%)
- Peptide (30.88%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Potassium channel, Pharmacology, Peptide, Stereochemistry and Cell biology.
His work on BK channel as part of general Potassium channel study is frequently linked to Regulator, therefore connecting diverse disciplines of science.
His research in Pharmacology intersects with topics in Rheumatoid arthritis, Venom and Mechanism of action.
His Peptide study deals with Cysteine intersecting with Proteolysis, Sea anemone and Potassium channel blocker.
The various areas that he examines in his Stereochemistry study include Glycine and Chemical synthesis.
His Cell biology research includes themes of Microglia, Receptor, Integrin, Cell adhesion and In vivo.
Between 2016 and 2020, his most popular works were:
- Peptide therapeutics from venom: Current status and potential. (106 citations)
- Identification and therapeutic modulation of a pro-inflammatory subset of disease-associated-microglia in Alzheimer’s disease (90 citations)
- Insensitivity to pain induced by a potent selective closed-state Nav1.7 inhibitor (55 citations)
In his most recent research, the most cited papers focused on:
- Enzyme
- Amino acid
- Biochemistry
His primary scientific interests are in Pharmacology, Potassium channel, Neuroinflammation, Microglia and Cell biology.
His Pharmacology research is multidisciplinary, relying on both Venom and Peptide.
His study in Potassium channel is interdisciplinary in nature, drawing from both Protein kinase B, Phosphorylation, Integrin, Cell adhesion and KCNA3.
Michael W. Pennington has researched Neuroinflammation in several fields, including Transcriptome and Neuroscience.
His Microglia study deals with the bigger picture of Immunology.
His Cell biology research is multidisciplinary, incorporating elements of Fibroblast, Integrin alpha M, BK channel and T cell.
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.
