What is he best known for?
The fields of study he is best known for:
His scientific interests lie mostly in Protein structure prediction, CASP, Protein structure, Critical assessment and Computational biology.
His work on Statistical potential as part of general Protein structure prediction research is often related to Scale, Model refinement and Conditional probability, thus linking different fields of science.
John Moult interconnects Structure and Data mining in the investigation of issues within CASP.
His biological study spans a wide range of topics, including Machine learning and Artificial intelligence.
The concepts of his Protein structure study are interwoven with issues in Genetics, Crystallography, Strain, Mutagenesis and Algorithm.
John Moult has researched Computational biology in several fields, including Structure, Biophysics, Cooperative behavior and Macromolecular docking.
His most cited work include:
- Critical assessment of methods of protein structure prediction (CASP) — round x (1283 citations)
- SNPs, protein structure, and disease (576 citations)
- CAPRI: A Critical Assessment of PRedicted Interactions (502 citations)
What are the main themes of his work throughout his whole career to date?
John Moult mainly focuses on Computational biology, Protein structure, CASP, Protein structure prediction and Genetics.
John Moult integrates several fields in his works, including Computational biology and Critical assessment.
His Protein structure research includes themes of Crystallography, Stereochemistry, Chemical physics and Sequence alignment.
His CASP research incorporates elements of Algorithm, Machine learning, Data mining and Artificial intelligence.
His research investigates the link between Protein structure prediction and topics such as Threading that cross with problems in Homology modeling.
In general Genetics, his work in Genome, Gene and Missense mutation is often linked to Genome-wide association study and Polymorphism linking many areas of study.
He most often published in these fields:
- Computational biology (27.98%)
- Protein structure (22.02%)
- CASP (20.24%)
What were the highlights of his more recent work (between 2014-2020)?
- Computational biology (27.98%)
- Genome (13.69%)
- Genetics (17.26%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Computational biology, Genome, Genetics, Disease and Critical assessment.
His study in Computational biology is interdisciplinary in nature, drawing from both Phenotype and Protein structure prediction, CASP.
His work in CASP covers topics such as Structural biology which are related to areas like Protein multimerization, Machine learning, Point and Structure.
His Missense mutation and Quantitative trait locus study, which is part of a larger body of work in Genetics, is frequently linked to Genome-wide association study and UBE2I, bridging the gap between disciplines.
His Disease study combines topics from a wide range of disciplines, such as Monogenic disease, Gene, Unknown Significance, Exome and Genetic testing.
His work deals with themes such as Protein structure and Operations research, which intersect with Artificial intelligence.
Between 2014 and 2020, his most popular works were:
- Critical assessment of methods of protein structure prediction: Progress and new directions in round XI (152 citations)
- Evaluation of the template-based modeling in CASP12. (43 citations)
- A bacteriophage endolysin that eliminates intracellular streptococci (43 citations)
In his most recent research, the most cited papers focused on:
John Moult spends much of his time researching Computational biology, Genome, Genetics, Genome-wide association study and Interpretation.
John Moult incorporates Computational biology and Biological significance in his research.
His Genome research includes elements of CDKN2A and Medical genetics.
His study in the field of Quantitative trait locus, DNA microarray and Gene is also linked to topics like Linkage disequilibrium and Mechanism.
John Moult undertakes interdisciplinary study in the fields of Interpretation and Critical assessment through his research.
His research in Bioinformatics tackles topics such as Information Dissemination which are related to areas like Data science.
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