What is he best known for?
The fields of study he is best known for:
Stephen K. Burley focuses on Stereochemistry, Protein structure, Genetics, Biochemistry and Molecular biology.
He combines subjects such as Antiparallel, Crystallography, DNA, DNA-binding protein and van der Waals force with his study of Stereochemistry.
He interconnects Type VI secretion system, Biophysics, Computational biology and Gene in the investigation of issues within Protein structure.
His study in Genetics is interdisciplinary in nature, drawing from both Structural genomics and Data science.
Many of his studies involve connections with topics such as Antidote and Biochemistry.
His Molecular biology study integrates concerns from other disciplines, such as RNA, TATA box, Cell biology, EIF4E and Transcription.
His most cited work include:
- Weight-reducing effects of the plasma protein encoded by the obese gene. (4141 citations)
- Aromatic-aromatic interaction: a mechanism of protein structure stabilization (1902 citations)
- Co-crystal structure of the HNF-3/ fork head DNA-recognition motif resembles histone H5 (1062 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Biochemistry, Stereochemistry, Protein structure, Protein Data Bank and Crystallography.
His studies deal with areas such as Antiparallel, Crystal structure and Amidohydrolase, Enzyme, Active site as well as Stereochemistry.
A large part of his Protein structure studies is devoted to Structural genomics.
The Protein Data Bank study combines topics in areas such as World Wide Web, Computational biology, Protein Data Bank and Data science.
As a member of one scientific family, Stephen K. Burley mostly works in the field of Computational biology, focusing on Genetics and, on occasion, Cell biology.
His research in Protein Data Bank intersects with topics in Bioinformatics and Structural bioinformatics.
He most often published in these fields:
- Biochemistry (35.95%)
- Stereochemistry (28.68%)
- Protein structure (22.00%)
What were the highlights of his more recent work (between 2017-2021)?
- Protein Data Bank (20.24%)
- Protein Data Bank (20.04%)
- Computational biology (14.54%)
In recent papers he was focusing on the following fields of study:
His main research concerns Protein Data Bank, Protein Data Bank, Computational biology, World Wide Web and Severe acute respiratory syndrome coronavirus 2.
The concepts of his Protein Data Bank study are interwoven with issues in Metadata, External Data Representation, Structural biology, Biomedicine and Data science.
His research integrates issues of Macromolecular crystallography and Structural bioinformatics in his study of Protein Data Bank.
In Macromolecular crystallography, Stephen K. Burley works on issues like Crystallography, which are connected to Data dictionary.
Stephen K. Burley has included themes like Protein structure, Drug discovery and Molecular targets in his Computational biology study.
In his work, he performs multidisciplinary research in Protein structure and Human metabolism.
Between 2017 and 2021, his most popular works were:
- RCSB Protein Data Bank: biological macromolecular structures enabling research and education in fundamental biology, biomedicine, biotechnology and energy. (409 citations)
- Recon3D enables a three-dimensional view of gene variation in human metabolism. (229 citations)
- Recon3D enables a three-dimensional view of gene variation in human metabolism. (229 citations)
In his most recent research, the most cited papers focused on:
Stephen K. Burley mainly investigates Protein Data Bank, Protein Data Bank, Computational biology, Data science and Pose prediction.
His research ties Structural biology and Protein Data Bank together.
His Protein Data Bank study combines topics in areas such as Metadata, Macromolecular crystallography and Structural bioinformatics.
While the research belongs to areas of Metadata, Stephen K. Burley spends his time largely on the problem of Bioinformatics, intersecting his research to questions surrounding World Wide Web.
His studies in Macromolecular crystallography integrate themes in fields like Crystallography and Data dictionary.
He has researched Computational biology in several fields, including Metabolite, Variation, Human genome and Gene.
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