What is he best known for?
The fields of study he is best known for:
- Gene
- Genetics
- Internal medicine
The scientist’s investigation covers issues in Genetics, Genome-wide association study, Genetic association, Linkage disequilibrium and Computational biology.
His Human genetics study in the realm of Genetics interacts with subjects such as Glucokinase regulatory protein.
His Genome-wide association study study combines topics from a wide range of disciplines, such as Population stratification, Allele frequency, Hemodynamics, Type 2 diabetes and CDKN2BAS.
His Genetic association research integrates issues from Blood pressure, Methylenetetrahydrofolate reductase, Immunology and Genetic architecture.
While the research belongs to areas of Linkage disequilibrium, Simon C. Potter spends his time largely on the problem of Case-control study, intersecting his research to questions surrounding Genetic linkage, SNP, Gene and Evolutionary biology.
His Computational biology research incorporates themes from Protein Families Database, Sequence analysis and Molecular Sequence Annotation.
His most cited work include:
- Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls (7922 citations)
- Initial sequencing and comparative analysis of the mouse genome. (5789 citations)
- The Pfam protein families database: towards a more sustainable future (3658 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Genetics, Genome-wide association study, Genetic association, Computational biology and Bioinformatics.
His study in Genetics is interdisciplinary in nature, drawing from both SNP and Disease.
Simon C. Potter combines subjects such as Case-control study, Immunology, Allele, Genetic architecture and Candidate gene with his study of Genome-wide association study.
The Genetic association study combines topics in areas such as Psoriasis, Genetic predisposition, Heritability and Imputation, Haplotype.
His research in Computational biology intersects with topics in Transcriptome, Molecular Sequence Annotation, InterProScan, Genome and Metagenomics.
His studies deal with areas such as Protein Families Database and UniProt Knowledgebase as well as Molecular Sequence Annotation.
He most often published in these fields:
- Genetics (53.01%)
- Genome-wide association study (50.60%)
- Genetic association (27.71%)
What were the highlights of his more recent work (between 2016-2019)?
- Computational biology (21.69%)
- Metagenomics (6.02%)
- Bioinformatics (15.66%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Computational biology, Metagenomics, Bioinformatics, InterProScan and Disease.
Simon C. Potter studied Computational biology and Molecular Sequence Annotation that intersect with Repetitive Sequences, Protein Families Database, Sequence Ontology and Functional annotation.
Simon C. Potter is interested in Annotation, which is a field of Bioinformatics.
His Annotation research includes elements of Genome, Whole genome sequencing, Ensembl Genomes and Genomics.
His Disease research is multidisciplinary, relying on both Genetics, Genome-wide association study, Multifactorial Inheritance and Copy-number variation.
Simon C. Potter has included themes like Parkinson's disease and Age of onset in his Genetics study.
Between 2016 and 2019, his most popular works were:
- The Pfam protein families database in 2019. (1886 citations)
- The EMBL-EBI search and sequence analysis tools APIs in 2019 (1474 citations)
- InterPro in 2017-beyond protein family and domain annotations (946 citations)
In his most recent research, the most cited papers focused on:
- Gene
- Genetics
- Internal medicine
His primary scientific interests are in Molecular Sequence Annotation, Computational biology, Repetitive Sequences, Protein Families Database and Sequence Ontology.
His Molecular Sequence Annotation research includes themes of Annotation, Bioinformatics, InterProScan and Protein family.
His research on Computational biology frequently links to adjacent areas such as UniProt Knowledgebase.
His Repetitive Sequences investigation overlaps with other disciplines such as Structural classification and Tandem Repeat Sequence.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
