What is he best known for?
The fields of study he is best known for:
Genetics, Allele, Genotype, Allele frequency and Internal medicine are his primary areas of study.
His study involves Genetic linkage, Linkage disequilibrium, Locus, Chromosome and Single-nucleotide polymorphism, a branch of Genetics.
His Allele study deals with the bigger picture of Gene.
As a member of one scientific family, Tadao Arinami mostly works in the field of Genotype, focusing on Immunoglobulin E and, on occasion, Netherton syndrome and Atopic dermatitis.
The study incorporates disciplines such as Serotonin reuptake inhibitor, Gene polymorphism and Nicotine in addition to Allele frequency.
His work deals with themes such as Endocrinology, Methylenetetrahydrofolate reductase and Schizophrenia, which intersect with Internal medicine.
His most cited work include:
- Discovery of the Presence and Functional Expression of Cannabinoid CB2 Receptors in Brain (422 citations)
- A Functional Polymorphism in the Promoter Region of the Dopamine D2 Receptor Gene Is Associated with Schizophrenia (399 citations)
- Mapping of a familial moyamoya disease gene to chromosome 3p24.2-p26. (227 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Genetics, Allele, Gene, Internal medicine and Endocrinology.
His research integrates issues of Psychosis and Immunology in his study of Genetics.
His Allele research integrates issues from Odds ratio, Missense mutation and Genotype.
His research combines Molecular biology and Gene.
His study explores the link between Internal medicine and topics such as Schizophrenia that cross with problems in Haloperidol.
Tadao Arinami has researched Endocrinology in several fields, including Receptor and Case-control study.
He most often published in these fields:
- Genetics (58.61%)
- Allele (34.02%)
- Gene (27.87%)
What were the highlights of his more recent work (between 2009-2018)?
- Genetics (58.61%)
- Single-nucleotide polymorphism (15.98%)
- Schizophrenia (13.52%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Genetics, Single-nucleotide polymorphism, Schizophrenia, Internal medicine and Gene.
His Genetics research is multidisciplinary, relying on both Psychosis and Case-control study.
His Single-nucleotide polymorphism research includes elements of Allele, Polymorphism and Haplotype.
His study in Allele is interdisciplinary in nature, drawing from both Odds ratio and Adenylate kinase.
The concepts of his Internal medicine study are interwoven with issues in Japanese population, Endocrinology and Methylenetetrahydrofolate reductase.
His work deals with themes such as Schizophrenia, Immunology and Surgical treatment, which intersect with Gene.
Between 2009 and 2018, his most popular works were:
- Brain Cannabinoid CB2 Receptor in Schizophrenia (129 citations)
- Genome-wide association study identifies HLA-DP as a susceptibility gene for pediatric asthma in Asian populations (113 citations)
- Identification of Novel Candidate Genes for Treatment Response to Risperidone and Susceptibility for Schizophrenia: Integrated Analysis Among Pharmacogenomics, Mouse Expression, and Genetic Case-Control Association Approaches (80 citations)
In his most recent research, the most cited papers focused on:
The scientist’s investigation covers issues in Single-nucleotide polymorphism, Allele, Genetics, Schizophrenia and Pharmacology.
His work carried out in the field of Allele brings together such families of science as Endocannabinoid system and Internal medicine, Appetite, Endocrinology.
His High plasma research extends to Genetics, which is thematically connected.
His Schizophrenia study incorporates themes from Haloperidol, Gene, Candidate gene and SNP.
The study incorporates disciplines such as Psychosis and Bioinformatics in addition to Pharmacology.
His study looks at the intersection of Haplotype and topics like Allele frequency with Expression quantitative trait loci, Quantitative trait locus, Asthma and Odds ratio.
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.
