What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Gene
- Statistics
His main research concerns Artificial intelligence, Image processing, Computer vision, Virology and Projection.
His Artificial intelligence study combines topics in areas such as Electron microscope, Machine learning and Pattern recognition.
The Image processing study combines topics in areas such as Software engineering and Workflow, Database.
The various areas that Carlos Oscar S. Sorzano examines in his Workflow study include Image processing software, Interoperability and 3d electron microscopy.
The study incorporates disciplines such as Immune system, Immunogenicity and MVA-B in addition to Virology.
In his research on the topic of Projection, Computer graphics and Free parameter is strongly related with 3D reconstruction.
His most cited work include:
- XMIPP: a new generation of an open-source image processing package for electron microscopy (414 citations)
- Image processing for electron microscopy single-particle analysis using XMIPP (291 citations)
- Scipion: A software framework toward integration, reproducibility and validation in 3D electron microscopy. (270 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Artificial intelligence, Algorithm, Image processing, Computer vision and Single particle analysis.
His work on 3D reconstruction, Projection and Deep learning as part of general Artificial intelligence research is often related to Set, thus linking different fields of science.
His Algorithm study combines topics from a wide range of disciplines, such as Microscope, Orientation, Fourier transform, Resolution and Voxel.
His research integrates issues of Electron microscope, Optics, Microscopy and Workflow in his study of Image processing.
Carlos Oscar S. Sorzano combines subjects such as Biological system and Image formation with his study of Microscopy.
His work on Image registration as part of general Computer vision study is frequently linked to Process, bridging the gap between disciplines.
He most often published in these fields:
- Artificial intelligence (34.78%)
- Algorithm (32.02%)
- Image processing (25.30%)
What were the highlights of his more recent work (between 2018-2021)?
- Cryo-electron microscopy (9.88%)
- Single particle analysis (20.16%)
- Artificial intelligence (34.78%)
In recent papers he was focusing on the following fields of study:
Carlos Oscar S. Sorzano mostly deals with Cryo-electron microscopy, Single particle analysis, Artificial intelligence, Algorithm and Virology.
His research in Single particle analysis focuses on subjects like Macromolecule, which are connected to Electron microscope.
Carlos Oscar S. Sorzano works mostly in the field of Artificial intelligence, limiting it down to topics relating to Computer vision and, in certain cases, Tomography, as a part of the same area of interest.
His Algorithm research includes elements of Image processing and Resolution.
Carlos Oscar S. Sorzano interconnects Principal component analysis, Workflow and Flexibility in the investigation of issues within Image processing.
His research in Virology intersects with topics in T cell and Antibody, Immunogenicity.
Between 2018 and 2021, his most popular works were:
- Automatic local resolution-based sharpening of cryo-EM maps. (48 citations)
- Survey of the analysis of continuous conformational variability of biological macromolecules by electron microscopy. (30 citations)
- BIPSPI: a method for the prediction of partner-specific protein–protein interfaces (23 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Gene
- Statistics
His scientific interests lie mostly in Artificial intelligence, Single particle analysis, Deep learning, Cryo-electron microscopy and Sharpening.
His studies deal with areas such as Machine learning, Web server and Docking as well as Artificial intelligence.
He has included themes like Electron microscope, Biophysics and Macromolecule in his Single particle analysis study.
His work deals with themes such as Computer graphics and Library science, which intersect with Deep learning.
His Cryo-electron microscopy research incorporates themes from Algorithm, Structure factor, Nanotechnology and Microscopy.
The concepts of his Sharpening study are interwoven with issues in Isotropy, Noise reduction, Observer and Pattern recognition.
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