| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Genetics | 60 | 98 | 75 | 16 |
The main research concerns discussed in the journal are Genetics, Statistics, Genetic association, Linkage (software) and Computational biology. Genetic Epidemiology facilitated presentations on Genetics research, particularly Genetic linkage, Allele, Linkage disequilibrium, Locus (genetics) and Single-nucleotide polymorphism. The concepts on Genetic linkage presented in it can also apply to other research fields, including Genetic marker, Gene mapping and Pedigree chart.
The study on Allele presented in Genetic Epidemiology intersects with the topics under Genotype. While work presented in Genetic Epidemiology provided substantial information on Linkage disequilibrium, it also covered topics in Transmission disequilibrium test and Association mapping. The studies in Statistics featured incorporate elements of Quantitative trait locus, Trait and Econometrics.
Topics in Genetic association explored in Genetic Epidemiology were investigated in conjunction with research in Sample size determination, Genome-wide association study, Population stratification, Genotyping and Candidate gene. It focused on Linkage (software) research but expanded to cover Genetic analysis. Computational biology research presented in the journal encompasses a variety of subjects, including Genome and Gene.
The journal publications facilitate discussions on Genetics, Statistics, Genetic association, Genome-wide association study and Computational biology. The published articles hold forums on Statistics that merge themes from other disciplines such as Quantitative trait locus, Linkage (software) and Econometrics. The most cited articles focus on Genetic association but the discussions also offer insight into other areas such as Population stratification, Regression analysis, Genotyping and Candidate gene.
The journal aims to foster the development of research in Genetic association, Statistics, Genome-wide association study, Computational biology and Type I and type II errors. Genetic Epidemiology facilitates discussions on Genetic association that incorporate concepts from other fields like Set (abstract data type), Whole genome sequencing, Proportional hazards model, Likelihood-ratio test and Genetic heterogeneity. Studies on Whole genome sequencing tackled in the journal are critical in grasping new concepts in the fields of Genetics and Genome.
Genetic Epidemiology addresses concerns in Genome-wide association study which are intertwined with other disciplines, such as Quantitative trait locus, Genetic architecture, Heritability, Minor allele frequency and Candidate gene. Genetic Epidemiology explores issues in Computational biology which can be linked to other research areas like Expression quantitative trait loci, Single-nucleotide polymorphism, Missing heritability problem, Gene and Trait. The study of Type I and type II errors encompasses disciplines such as Score test, as well as fields such as Score, Exome sequencing, Pooling and Allele, all of which overlap with one another.
A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.
The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.
The top authors publishing in Genetic Epidemiology (based on the number of publications) are:
The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.
Only papers with recognized affiliations are considered
The top affiliations publishing in Genetic Epidemiology (based on the number of publications) are:
The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.
The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.
The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.
During the most recent 2021 edition, 9.23% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 37.29% were posted by at least one author from the top 10 institutions publishing in the journal. Another 18.64% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 23.73% of all publications and 20.34% were from other institutions.
A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.
The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.
The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.
Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).
The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:
The chart below illustrates experience levels of first authors in cases of publications with multiple authors.
Christopher A. German;Janet S. Sinsheimer;Yann C. Klimentidis;Hua Zhou
(2020)Damian Gola;Jeannette Erdmann;Bertram Müller‐Myhsok;Heribert Schunkert
(2020)Alvaro N. Barbeira;Owen J. Melia;Yanyu Liang;Rodrigo Bonazzola
(2020)Corbin Quick;Pramod Anugu;Solomon Musani;Scott T Weiss;Scott T Weiss;Scott T Weiss
(2020)Yixuan Ye;Hongxi Yang;Hongxi Yang;Yaogang Wang;Hongyu Zhao
(2021)James J. Fryett;Andrew P. Morris;Heather J. Cordell
(2020)
