What is he best known for?
The fields of study he is best known for:
Pieter C. Dorrestein focuses on Biochemistry, Computational biology, Microbiome, Metagenomics and Mass spectrometry.
He studied Biochemistry and Bacillus subtilis that intersect with Streptomyces coelicolor.
Pieter C. Dorrestein has researched Computational biology in several fields, including Molecular networking, Metabolomics, Genomics, Tandem mass spectrum and Natural product.
His Molecular networking research incorporates elements of Drug discovery and Identification.
His Microbiome study integrates concerns from other disciplines, such as Antimicrobial peptides, Disease, Data science and Microbiology.
His Metagenomics research incorporates themes from Evolutionary biology, Molecular analysis and Systems biology.
His most cited work include:
- Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2 (2043 citations)
- Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking (1067 citations)
- Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking (1067 citations)
What are the main themes of his work throughout his whole career to date?
Pieter C. Dorrestein mainly focuses on Computational biology, Biochemistry, Microbiome, Mass spectrometry and Metabolomics.
As a part of the same scientific family, Pieter C. Dorrestein mostly works in the field of Computational biology, focusing on Molecular networking and, on occasion, Molecular network.
In Biochemistry, Pieter C. Dorrestein works on issues like Bacillus subtilis, which are connected to Microbiology.
Pieter C. Dorrestein combines subjects such as Metabolome, Disease, Data science and Metagenomics with his study of Microbiome.
His study ties his expertise on Combinatorial chemistry together with the subject of Mass spectrometry.
His studies deal with areas such as Metabolite, Gene and Bacteria as well as Metabolomics.
He most often published in these fields:
- Computational biology (27.15%)
- Biochemistry (24.23%)
- Microbiome (28.87%)
What were the highlights of his more recent work (between 2019-2021)?
- Microbiome (28.87%)
- Metabolomics (26.46%)
- Metabolome (19.24%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Microbiome, Metabolomics, Metabolome, Mass spectrometry and Computational biology.
His Microbiome study combines topics from a wide range of disciplines, such as Immunology, Data science and Metagenomics.
He interconnects Quorum sensing, Inflammatory bowel disease, Microorganism, Biochemistry and Streptomyces in the investigation of issues within Metabolomics.
His Biochemistry research integrates issues from Strain and Bacillus subtilis, Surfactin.
His work carried out in the field of Mass spectrometry brings together such families of science as Table, Visualization, Metadata and Molecular networking.
His studies in Computational biology integrate themes in fields like In silico, Gene, Identification and Genomics.
Between 2019 and 2021, his most popular works were:
- Global chemical effects of the microbiome include new bile-acid conjugations (62 citations)
- Global chemical effects of the microbiome include new bile-acid conjugations (62 citations)
- Feature-based molecular networking in the GNPS analysis environment. (61 citations)
In his most recent research, the most cited papers focused on:
Pieter C. Dorrestein mostly deals with Metabolomics, Microbiome, Mass spectrometry, Molecular networking and Metabolome.
The Metabolomics study combines topics in areas such as Peptide sequencing, Fragmentation, Tandem mass spectrometry and Computational biology.
His Computational biology research is multidisciplinary, relying on both De novo peptide sequencing, Human gut, Identification and Genomics.
His Microbiome research includes elements of Inflammatory bowel disease, Microbial composition, Cystic fibrosis and Bile acid.
His study in Mass spectrometry is interdisciplinary in nature, drawing from both Data mining and Resolution.
His Molecular networking research is multidisciplinary, incorporating elements of Chemical physics, Ion, Ionization and Tandem mass spectrum.
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