What is he best known for?
The fields of study he is best known for:
His main research concerns Dihedral angle, Protein structure prediction, Homology modeling, Statistical physics and Protein structure.
His Dihedral angle study combines topics in areas such as Conformational isomerism and Algorithm.
His Protein structure prediction research includes elements of Threading, Protein Data Bank and Artificial intelligence.
His biological study deals with issues like Crystallography, which deal with fields such as Protein fragment library and van der Waals force.
He combines subjects such as Solvent models and Thermodynamics with his study of Computational chemistry.
His Ab initio research includes themes of Solvation, Potential of mean force and Dipole.
His most cited work include:
- All-atom empirical potential for molecular modeling and dynamics studies of proteins. (10375 citations)
- PISCES: a protein sequence culling server (1349 citations)
- A graph-theory algorithm for rapid protein side-chain prediction (932 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Computational biology, Protein structure, Protein Data Bank, Bioinformatics and Biochemistry.
His work carried out in the field of Protein structure brings together such families of science as Crystallography, Peptide sequence and Stereochemistry.
The concepts of his Crystallography study are interwoven with issues in Dihedral angle, Conformational isomerism and Protein structure prediction.
Roland L. Dunbrack works mostly in the field of Protein structure prediction, limiting it down to topics relating to Homology modeling and, in certain cases, Algorithm and Data mining, as a part of the same area of interest.
He has researched Protein Data Bank in several fields, including Protein superfamily, Protein Data Bank and Sequence.
His research integrates issues of Sequence analysis and Database in his study of Protein Data Bank.
He most often published in these fields:
- Computational biology (17.31%)
- Protein structure (14.42%)
- Protein Data Bank (10.10%)
What were the highlights of his more recent work (between 2017-2021)?
- Computational biology (17.31%)
- Software development (4.33%)
- Protein Data Bank (10.10%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Computational biology, Software development, Protein Data Bank, Ramachandran plot and Kinase.
The Computational biology study combines topics in areas such as Domain, Protein domain, Protein family, Interface and Protein–protein interaction.
The various areas that Roland L. Dunbrack examines in his Protein Data Bank study include Similarity, Protein Data Bank, Sequence, Protein superfamily and Antibody.
His biological study spans a wide range of topics, including Dihedral angle, Conformational isomerism and Cluster analysis.
His research in BETA focuses on subjects like Set, which are connected to Protein structure prediction.
His work in Artificial intelligence covers topics such as Amino acid which are related to areas like Test set, Protein tertiary structure, Protein structure, Web server and Information retrieval.
Between 2017 and 2021, his most popular works were:
- Macromolecular modeling and design in Rosetta: recent methods and frameworks (61 citations)
- Defining a new nomenclature for the structures of active and inactive kinases. (60 citations)
- RosettaAntibodyDesign (RAbD): A general framework for computational antibody design. (36 citations)
In his most recent research, the most cited papers focused on:
Roland L. Dunbrack mainly focuses on Computational biology, Structural bioinformatics, Kinase, Protein structure and Molecular biology.
His studies in Computational biology integrate themes in fields like Protein family, Interface, Protein–protein interaction and Homology.
His Structural bioinformatics research incorporates elements of Dihedral angle, Activation loop, Stereochemistry, Modular design and Conformational isomerism.
His Kinase study incorporates themes from Multiple sequence alignment, Sequence alignment, Human genome and Protein secondary structure.
The study incorporates disciplines such as Antigen, Similarity, Protein Data Bank, Sequence and Protein superfamily in addition to Protein structure.
His studies deal with areas such as Antibody, Antibody antigen and Sequence analysis as well as Molecular biology.
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