What is he best known for?
The fields of study he is best known for:
His primary scientific interests are in Biochemistry, Cell biology, Quercetin, Arabidopsis thaliana and Transcription factor.
Sjef Boeren focuses mostly in the field of Cell biology, narrowing it down to topics relating to Immune system and, in certain cases, Bacterial outer membrane and Mucin.
His Quercetin research is multidisciplinary, incorporating perspectives in Flavonoid, Adduct and Quinone methide, Quinone.
As part of the same scientific family, Sjef Boeren usually focuses on Arabidopsis thaliana, concentrating on Brassinosteroid and intersecting with Molecular biology, Zinc finger and Immunoprecipitation.
His Transcription factor research incorporates elements of Arabidopsis, Periclinal cell division, Cell division, Anatomy and Ectopic expression.
His study in DNA microarray is interdisciplinary in nature, drawing from both Proteome and Proteomics.
His most cited work include:
- Rules for optimization of biocatalysis in organic solvents (1405 citations)
- Characterization of MADS-domain transcription factor complexes in Arabidopsis flower development (325 citations)
- The Arabidopsis SOMATIC EMBRYOGENESIS RECEPTOR-LIKE KINASE1 protein complex includes BRASSINOSTEROID-INSENSITIVE1 (241 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Biochemistry, Proteome, Cell biology, Proteomics and Virology.
Much of his study explores Biochemistry relationship to Bacteria.
Sjef Boeren combines subjects such as Blood proteins, Genome, Breast milk and Microbiology with his study of Proteome.
In his study, Arabidopsis thaliana is strongly linked to Arabidopsis, which falls under the umbrella field of Cell biology.
His Proteomics research is multidisciplinary, incorporating elements of Tandem mass spectrometry and Computational biology.
His Virology research focuses on Gene and how it relates to Effector.
He most often published in these fields:
- Biochemistry (30.07%)
- Proteome (18.95%)
- Cell biology (11.76%)
What were the highlights of his more recent work (between 2017-2021)?
- Biochemistry (30.07%)
- Bacteria (6.54%)
- Proteome (18.95%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Biochemistry, Bacteria, Proteome, Milk Serum and Food science.
His study in Bacterial microcompartment, Propionate, Lactate dehydrogenase, Lactate permease and Butyrate falls under the purview of Biochemistry.
Sjef Boeren interconnects Thiosulfate, Sulfur, Sulfate and Glycan in the investigation of issues within Bacteria.
His Proteome study deals with Proteomics intersecting with Computational biology, Arginine and Mutant.
The Milk Serum study combines topics in areas such as Secretion, Lactoferrin, Blood proteins, Colostrum and Digestion.
His Function study is concerned with Cell biology in general.
Between 2017 and 2021, his most popular works were:
- POLAR-guided signalling complex assembly and localization drive asymmetric cell division (66 citations)
- Myofibrillar protein oxidation affects filament charges, aggregation and water-holding. (49 citations)
- Comparative proteome analysis of propionate degradation by Syntrophobacter fumaroxidans in pure culture and in coculture with methanogens. (23 citations)
In his most recent research, the most cited papers focused on:
His scientific interests lie mostly in Biochemistry, Bacteria, Streptococcus thermophilus, Proteome and Food science.
Sjef Boeren has included themes like Thiosulfate and Sulfate-reducing bacteria in his Biochemistry study.
His Bacteria research incorporates elements of Sulfurtransferase, Sulfite, Sulfur and Disproportionation.
The concepts of his Streptococcus thermophilus study are interwoven with issues in Metaproteomics, Biotechnology, Illumina dye sequencing and Shotgun metagenomics.
His work deals with themes such as Blood proteins, Colostrum, Digestion and Protease, which intersect with Proteome.
His studies deal with areas such as Lactoperoxidase and Denaturation as well as Food 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.
