What is he best known for?
The fields of study he is best known for:
The scientist’s investigation covers issues in Protein Data Bank, Crystallography, AutoDock, Protein Data Bank and Docking.
The concepts of his Crystallography study are interwoven with issues in Protein structure, Twist and Base pair, DNA.
David S. Goodsell combines subjects such as Biomedicine, Bioinformatics, Structural bioinformatics and Collaboratory, World Wide Web with his study of Protein Data Bank.
His Docking research focuses on Searching the conformational space for docking and Protein–ligand docking.
The study incorporates disciplines such as Combinatorial chemistry and Simulated annealing in addition to Searching the conformational space for docking.
His Lead Finder research incorporates themes from Scoring functions for docking and Molecular Docking Simulation.
His most cited work include:
- AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility (9267 citations)
- Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function (7789 citations)
- A semiempirical free energy force field with charge-based desolvation. (1503 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Cell biology, DNA, Protein Data Bank, Computational biology and Biochemistry.
His biological study spans a wide range of topics, including Crystallography and Stereochemistry.
His Protein Data Bank research incorporates elements of World Wide Web and Protein Data Bank.
His Protein Data Bank research includes themes of Bioinformatics and Structural bioinformatics.
His Structural bioinformatics study frequently draws parallels with other fields, such as Collaboratory.
His Netropsin study frequently involves adjacent topics like Hydrogen bond.
He most often published in these fields:
- Cell biology (10.51%)
- DNA (10.78%)
- Protein Data Bank (14.02%)
What were the highlights of his more recent work (between 2017-2021)?
- Protein Data Bank (14.02%)
- Protein Data Bank (10.51%)
- Structural biology (7.82%)
In recent papers he was focusing on the following fields of study:
Protein Data Bank, Protein Data Bank, Structural biology, Mesoscale meteorology and Visualization are his primary areas of study.
The various areas that David S. Goodsell examines in his Protein Data Bank study include Biomedicine, Protein structure and function and Column.
The Protein Data Bank study combines topics in areas such as Computational biology and Structural bioinformatics.
His Structural biology study incorporates themes from Pedagogy, Molecular graphics, Data science and Drug discovery.
His research integrates issues of Digital painting, Docking and Reuse in his study of Visualization.
The concepts of his Docking study are interwoven with issues in Proteomics, Small molecule and Irreversible binding.
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)
- RCSB Protein Data Bank: biological macromolecular structures enabling research and education in fundamental biology, biomedicine, biotechnology and energy. (409 citations)
- Protein Data Bank: the single global archive for 3D macromolecular structure data (192 citations)
In his most recent research, the most cited papers focused on:
His primary areas of study are Protein Data Bank, Protein Data Bank, Structural biology, Structural bioinformatics and Visualization.
His Protein Data Bank study integrates concerns from other disciplines, such as Software engineering and Column.
The Protein Data Bank study combines topics in areas such as Database, Master data and Atomic coordinates.
His Structural biology research is multidisciplinary, relying on both Protein structure and function, Molecular graphics, Computational biology and Drug discovery.
His research in Structural bioinformatics intersects with topics in Collaboratory, Biomedicine and Biotechnology.
His work deals with themes such as Digital painting and Computer graphics, Computer graphics, which intersect with Visualization.
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