What is he best known for?
The fields of study he is best known for:
David Baker mostly deals with Protein structure, Crystallography, Computational biology, Protein structure prediction and Protein folding.
As part of one scientific family, he deals mainly with the area of Protein structure, narrowing it down to issues related to the Protein engineering, and often Nanotechnology.
His research integrates issues of Chemical physics, Algorithm and Side chain in his study of Crystallography.
His work carried out in the field of Computational biology brings together such families of science as Genetics, Binding site, Plasma protein binding and Protein family.
In his work, Computational chemistry is strongly intertwined with Biological system, which is a subfield of Protein structure prediction.
David Baker has researched Protein folding in several fields, including Folding and Protein tertiary structure.
His most cited work include:
- Protein Structure Prediction and Structural Genomics (1320 citations)
- Contact order, transition state placement and the refolding rates of single domain proteins (1285 citations)
- Design of a Novel Globular Protein Fold with Atomic-Level Accuracy (1281 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Protein structure, Computational biology, Crystallography, Immunology and Biochemistry.
His studies in Protein structure integrate themes in fields like Biophysics, Protein engineering and Protein folding.
Protein folding is often connected to Folding in his work.
His work deals with themes such as Genetics and Structural genomics, which intersect with Computational biology.
In most of his Immunology studies, his work intersects topics such as Central nervous system.
David Baker does research in Multiple sclerosis, focusing on Experimental autoimmune encephalomyelitis specifically.
He most often published in these fields:
- Protein structure (16.44%)
- Computational biology (14.27%)
- Crystallography (11.41%)
What were the highlights of his more recent work (between 2017-2021)?
- Protein design (9.12%)
- Computational biology (14.27%)
- Protein structure (16.44%)
In recent papers he was focusing on the following fields of study:
David Baker mainly investigates Protein design, Computational biology, Protein structure, Multiple sclerosis and Biophysics.
David Baker has included themes like Stability, Biological system and Energy landscape in his Protein design study.
His studies deal with areas such as Protein engineering, Artificial intelligence and Protein folding as well as Protein structure.
His Multiple sclerosis study introduces a deeper knowledge of Immunology.
Specifically, his work in Immunology is concerned with the study of Antibody.
As part of his studies on Biophysics, David Baker frequently links adjacent subjects like Membrane.
Between 2017 and 2021, his most popular works were:
- Improved protein structure prediction using predicted interresidue orientations (214 citations)
- Viral suppression and HIV transmission in serodiscordant male couples: an international, prospective, observational, cohort study (157 citations)
- TGF-β-Mediated Epithelial-Mesenchymal Transition and Cancer Metastasis (151 citations)
In his most recent research, the most cited papers focused on:
His scientific interests lie mostly in Protein structure, Protein design, Computational biology, Biophysics and Protein structure prediction.
His Protein structure research is multidisciplinary, relying on both Protein engineering, Protocol, Self assembling and Protein folding.
His Protein design research includes elements of Encoding, Stability, Energy landscape, Biological system and Beta sheet.
His research in Computational biology intersects with topics in Genome, Whole genome sequencing, Genomics, Function and DNA sequencing.
His Biophysics research incorporates themes from Cooperativity, Antibody, Neutralizing antibody, Antigen and Membrane.
The study incorporates disciplines such as Algorithm and A protein in addition to Protein structure prediction.
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.
