What is he best known for?
The fields of study he is best known for:
His primary areas of study are Protein structure, Algorithm, Cryo-electron microscopy, Crystal structure and Crystallography.
His study in the fields of Protein structure prediction under the domain of Protein structure overlaps with other disciplines such as Energy.
His Algorithm research is multidisciplinary, incorporating perspectives in Process, Structural biology, Homology modeling, Resolution and Interpretation.
The various areas that Frank DiMaio examines in his Cryo-electron microscopy study include Virology and Cell biology.
The Crystal structure study combines topics in areas such as Chemical physics, Retroviral protease and Biochemistry, Protein folding.
His study in Crystallography is interdisciplinary in nature, drawing from both Measure and Protein model.
His most cited work include:
- High resolution comparative modeling with RosettaCM (531 citations)
- EMRinger: side chain-directed model and map validation for 3D cryo-electron microscopy (468 citations)
- The Rosetta All-Atom Energy Function for Macromolecular Modeling and Design (413 citations)
What are the main themes of his work throughout his whole career to date?
Frank DiMaio spends much of his time researching Biophysics, Protein structure, Cryo-electron microscopy, Cell biology and Crystallography.
The study incorporates disciplines such as Nucleotide, Transmembrane protein, Membrane, Protein quaternary structure and Ion channel in addition to Biophysics.
As a part of the same scientific study, Frank DiMaio usually deals with the Ion channel, concentrating on Gating and frequently concerns with HCN channel.
His research on Protein structure also deals with topics like
- Biological system that intertwine with fields like Protein design,
- Computational biology which connect with Protein folding.
The concepts of his Cryo-electron microscopy study are interwoven with issues in Resolution, Algorithm and Protein filament.
His work on Crystal structure as part of general Crystallography research is frequently linked to Low resolution, bridging the gap between disciplines.
He most often published in these fields:
- Biophysics (23.24%)
- Protein structure (20.54%)
- Cryo-electron microscopy (16.22%)
What were the highlights of his more recent work (between 2019-2021)?
- Protein design (6.49%)
- Biophysics (23.24%)
- Cell biology (11.89%)
In recent papers he was focusing on the following fields of study:
Frank DiMaio mainly investigates Protein design, Biophysics, Cell biology, Biological system and Software.
His study looks at the relationship between Protein design and fields such as Stability, as well as how they intersect with chemical problems.
His work on Gating and Cryo-electron microscopy as part of his general Biophysics study is frequently connected to Alexa Fluor, thereby bridging the divide between different branches of science.
His Cell biology study integrates concerns from other disciplines, such as Endogeny and Homology.
His Biological system study combines topics from a wide range of disciplines, such as Protein structure, Sequence and Energy landscape.
His studies deal with areas such as Structure and Data mining as well as Software.
Between 2019 and 2021, his most popular works were:
- Macromolecular modeling and design in Rosetta: recent methods and frameworks (61 citations)
- Computational design of transmembrane pores. (19 citations)
- An enumerative algorithm for de novo design of proteins with diverse pocket structures. (11 citations)
In his most recent research, the most cited papers focused on:
His main research concerns Software, Cell biology, Protein design, Docking and Benchmark.
His work on Score expands to the thematically related Software.
His research on Cell biology often connects related areas such as Homology.
His Protein design study combines topics in areas such as Stability, SUPERFAMILY and Encoding.
His Docking research incorporates elements of User interface and Software engineering.
He combines subjects such as Data mining, Protein Data Bank and Artificial intelligence with his study of Structure.
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