What is he best known for?
The fields of study he is best known for:
Roland J. Siezen mostly deals with Biochemistry, Genetics, Genome, Peptide sequence and Lactococcus lactis.
His Biochemistry research is multidisciplinary, incorporating elements of Lantibiotics, Biophysics and Bacteria.
As part of his studies on Genetics, Roland J. Siezen often connects relevant areas like Mycobacterium tuberculosis.
His Genome research integrates issues from Lactobacillus plantarum, In silico and Computational biology.
His studies in Peptide sequence integrate themes in fields like Protein structure, Molecular biology, Subtilisin and Mutant.
His Lactococcus lactis research is multidisciplinary, incorporating perspectives in Plasmid, Restriction map, Replicon, Permease and Horizontal gene transfer.
His most cited work include:
- Complete genome sequence of Lactobacillus plantarum WCFS1 (1187 citations)
- Subtilases: the superfamily of subtilisin-like serine proteases. (794 citations)
- Characterization of the nisin gene cluster nisABTCIPR of Lactococcus lactis. Requirement of expression of the nisA and nisI genes for development of immunity (478 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Genetics, Biochemistry, Genome, Gene and Lactococcus lactis.
His Genetics study frequently intersects with other fields, such as Mycobacterium tuberculosis.
His Biochemistry research is multidisciplinary, relying on both Nisin, Lantibiotics and Bacteria.
Roland J. Siezen has included themes like Lactobacillus plantarum, Computational biology and Microbiology in his Genome study.
His study in the field of Niche adaptation, Conserved sequence, Phenotype and In silico also crosses realms of Prophage.
His Lactococcus lactis study combines topics in areas such as Molecular biology and Signal peptide.
He most often published in these fields:
- Genetics (40.21%)
- Biochemistry (35.05%)
- Genome (35.57%)
What were the highlights of his more recent work (between 2010-2020)?
- Genetics (40.21%)
- Genome (35.57%)
- Computational biology (19.59%)
In recent papers he was focusing on the following fields of study:
Roland J. Siezen focuses on Genetics, Genome, Computational biology, Microbiology and Gene.
As part of his studies on Genetics, he often connects relevant subjects like Mycobacterium tuberculosis.
He has included themes like Plasmid, DNA microarray and Bacteria in his Genome study.
His Computational biology research is multidisciplinary, incorporating perspectives in RefSeq and Metagenomics.
Roland J. Siezen has researched Microbiology in several fields, including Fermentation, Biochemistry, Gluten, Subtilisins and Lactic acid bacterium.
The various areas that Roland J. Siezen examines in his Biochemistry study include Cereus, Bacillus cereus and Microbial metabolism.
Between 2010 and 2020, his most popular works were:
- Genomic diversity and versatility of Lactobacillus plantarum, a natural metabolic engineer (165 citations)
- Inferring patient to patient transmission of Mycobacterium tuberculosis from whole genome sequencing data. (146 citations)
- Inferring patient to patient transmission of Mycobacterium tuberculosis from whole genome sequencing data. (146 citations)
In his most recent research, the most cited papers focused on:
Roland J. Siezen spends much of his time researching Genome, Genetics, Gene, Comparative genomics and Computational biology.
His Genome research includes elements of Plasmid and Lactobacillus plantarum.
His work on DNA microarray and Multiple sequence alignment is typically connected to Support vector machine, Cluster analysis and Markov chain as part of general Genetics study, connecting several disciplines of science.
In general Gene, his work in Niche adaptation and Virulence is often linked to Human health linking many areas of study.
Roland J. Siezen usually deals with Comparative genomics and limits it to topics linked to Phenotype and Strain and Proteomics.
His Computational biology research incorporates elements of Protein domain, Sequence analysis and Sequence alignment.
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