What is he best known for?
The fields of study he is best known for:
His primary areas of study are Biochemistry, Stereochemistry, Nitric oxide, Nitric oxide synthase and Heme.
His Biochemistry research incorporates themes from Nitration and Streptomyces.
His Stereochemistry study combines topics from a wide range of disciplines, such as Active site, Enzyme, Dimer, Sulfite and Nitrite reductase.
His Nitric oxide research is multidisciplinary, incorporating perspectives in Oxidative stress and Oxygenase.
In his research on the topic of Nitric oxide synthase, Oxidoreductase is strongly related with Peptide sequence.
His Heme study integrates concerns from other disciplines, such as Bacterial Physiological Phenomena, Monooxygenase, Reductase and Cofactor, Tetrahydrobiopterin.
His most cited work include:
- Structure of nitric oxide synthase oxygenase dimer with pterin and substrate. (558 citations)
- Structure of nitric oxide synthase oxygenase dimer with pterin and substrate. (558 citations)
- Structure of CheA, a Signal-Transducing Histidine Kinase (404 citations)
What are the main themes of his work throughout his whole career to date?
Brian R. Crane focuses on Biochemistry, Stereochemistry, Biophysics, Crystallography and Histidine kinase.
His Stereochemistry study combines topics in areas such as Oxidoreductase, Protein subunit, Active site, Dimer and Electron transfer.
His Biophysics research includes elements of Protein structure, Flagellum, HAMP domain and Flavin group.
The study incorporates disciplines such as Site-directed spin labeling and Azurin in addition to Crystallography.
His Histidine kinase research integrates issues from Thermotoga maritima, Chemotaxis and Kinase activity.
Brian R. Crane combines subjects such as Pterin and Heme with his study of Nitric oxide synthase.
He most often published in these fields:
- Biochemistry (37.11%)
- Stereochemistry (34.02%)
- Biophysics (24.23%)
What were the highlights of his more recent work (between 2014-2021)?
- Biophysics (24.23%)
- Histidine kinase (19.07%)
- Chemotaxis (14.95%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Biophysics, Histidine kinase, Chemotaxis, Flavin group and Stereochemistry.
His biological study spans a wide range of topics, including Flagellum and Biochemistry, Protein–protein interaction.
His work in the fields of Biochemistry, such as HAMP domain, Thermotoga maritima and Tetrahydrobiopterin, intersects with other areas such as Methyl-accepting chemotaxis protein.
He has included themes like Metalloprotein, Protein domain and Protein structure in his Histidine kinase study.
His research integrates issues of Protein subunit, Cytochrome c peroxidase, Active site, Hydrogen bond and Electron transfer in his study of Stereochemistry.
His work carried out in the field of Heme brings together such families of science as Oxygenase, Nitric oxide synthase, Nitric oxide, Arginine and Globin.
Between 2014 and 2021, his most popular works were:
- Signal transduction in light-oxygen-voltage receptors lacking the adduct-forming cysteine residue (49 citations)
- Co-Folding of a FliF-FliG Split Domain Forms the Basis of the MS:C Ring Interface within the Bacterial Flagellar Motor (34 citations)
- Assembly states of FliM and FliG within the flagellar switch complex. (28 citations)
In his most recent research, the most cited papers focused on:
Brian R. Crane mainly focuses on Biophysics, Flavin group, Flagellum, Timeless and Circadian clock.
Brian R. Crane interconnects Protein structure, Biochemistry, Histidine kinase and Thermotoga maritima in the investigation of issues within Biophysics.
Brian R. Crane studies Biochemistry, namely Chemotaxis.
His Flavin group research includes themes of Semiquinone and Cofactor.
His Semiquinone research is multidisciplinary, incorporating elements of Protonation and Stereochemistry.
His work on Conformational change is typically connected to Side chain as part of general Stereochemistry study, connecting several disciplines of science.
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.
