What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Gene
Andriy Kryshtafovych mainly investigates CASP, Protein structure prediction, Data mining, Machine learning and Artificial intelligence.
His study in CASP is interdisciplinary in nature, drawing from both Cluster analysis, Range, Ranking, Algorithm and Intrinsically disordered proteins.
His Protein structure prediction study combines topics in areas such as Structural biology and Computational biology.
He interconnects Sequence identity, Reliability and Template based in the investigation of issues within Data mining.
His Deep learning study, which is part of a larger body of work in Machine learning, is frequently linked to Co variation, bridging the gap between disciplines.
His research in Artificial intelligence intersects with topics in Field, Data science and LiveBench.
His most cited work include:
- Critical assessment of methods of protein structure prediction (CASP) — round x (1283 citations)
- Critical assessment of methods of protein structure prediction-Round VII. (291 citations)
- Critical assessment of methods of protein structure prediction (CASP) - round x: Critical Assessment of Structure Prediction (234 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in CASP, Protein structure prediction, Data mining, Artificial intelligence and Computational biology.
His studies link Algorithm with CASP.
His work deals with themes such as Information exchange, Structural biology and Protein folding, which intersect with Protein structure prediction.
His work in the fields of Data mining, such as Visualization, intersects with other areas such as Correlation.
Andriy Kryshtafovych studied Artificial intelligence and Machine learning that intersect with Correctness and Workflow.
His biological study spans a wide range of topics, including Sequence identity, Genetics and Homology modeling.
He most often published in these fields:
- CASP (67.90%)
- Protein structure prediction (49.38%)
- Data mining (38.27%)
What were the highlights of his more recent work (between 2018-2021)?
- CASP (67.90%)
- Artificial intelligence (24.69%)
- Machine learning (18.52%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are CASP, Artificial intelligence, Machine learning, Protein structure prediction and Cryo-electron microscopy.
Andriy Kryshtafovych combines subjects such as Protein tertiary structure, Protein secondary structure, Ranking, Algorithm and Computational biology with his study of CASP.
Andriy Kryshtafovych integrates many fields, such as Artificial intelligence and Sequence, in his works.
His work on Deep learning as part of general Machine learning research is frequently linked to Context and Structure, thereby connecting diverse disciplines of science.
The Protein structure prediction study combines topics in areas such as Resolution and Data mining.
He has researched Cryo-electron microscopy in several fields, including Biological system and Computer graphics.
Between 2018 and 2021, his most popular works were:
- Assessing the accuracy of contact predictions in CASP13. (35 citations)
- Evaluation of template-based modeling in CASP13. (26 citations)
- Assessment of protein model structure accuracy estimation in CASP13: Challenges in the era of deep learning. (22 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Statistics
- Machine learning
Andriy Kryshtafovych spends much of his time researching Artificial intelligence, Sequence, Machine learning, CASP and Deep learning.
His work in the fields of Artificial intelligence, such as Artificial neural network, overlaps with other areas such as Server, Variety and Structure.
He has included themes like Protein structure modeling and Evolutionary information in his Artificial neural network study.
Andriy Kryshtafovych performs integrative study on Server and Protein tertiary structure in his works.
His Structure research includes a combination of various areas of study, such as Protein structure prediction, Component and Measure.
His work carried out in the field of Pattern recognition brings together such families of science as Domain, Protein domain and Cluster analysis.
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