| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Mathematics | 717 | 12 | 17 | 2 |
The scientific interests tackled in Statistics in Biosciences are Statistics, Biostatistics, Data mining, Econometrics and Estimator. The overlapping concepts between Random effects model and Mixed model are the key highlights of Statistics study. While it focused on Biostatistics, it was also able to explore topics like Observational study, Clinical trial and Missing data.
The Data mining research presented in Statistics in Biosciences explores the relationship between Computational biology and the closely related topic of DNA sequencing. Statistics in Biosciences holds forums on Econometrics that merges themes from other disciplines such as Statistical hypothesis testing and Bayesian probability. The discussions emphasized the topic of Bayesian probability in an attempt to further explore the field of Artificial intelligence.
In addition to Estimator research, the journal aims to explore topics under Event (probability theory) and Nonparametric statistics. The presented research on Sample size determination deals specifically with Type I and type II errors but it also addresses topics in Biomarker (medicine). The studies in Covariate featured incorporate elements of Regression analysis and Regression.
The most cited publications primarily focus on research topics in Biostatistics, Statistics, Data mining, Econometrics and Estimator. The journal publications with studies in Statistics featured incorporate elements of Inference and Measure (data warehouse). The studies on Estimator discussed at the journal papers can also contribute to research in the domains of Marginal structural model, Causal inference and Parametric statistics.
The foci of Statistics in Biosciences are Statistics, Biostatistics, Bayesian probability, Microbiome and Machine learning. The research on Biostatistics featured in Statistics in Biosciences combines topics in other fields like Data quality, Covariate and Correlation. The journal focuses on Covariate but the discussions also offer insight into other areas such as Regression analysis, Univariate, Regression and Receiver operating characteristic.
The Bayesian probability works featured in it incorporate elements from Rare disease, Natural history, Econometrics and Type I and type II errors. Data mining, Mixed model and Metagenomics are some topics wherein Microbiome research discussed in Statistics in Biosciences have an impact. The concepts on Machine learning presented in Statistics in Biosciences can also apply to other research fields, including Estimator, Randomized controlled trial, Artificial intelligence and Clinical trial.
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 Statistics in Biosciences (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 Statistics in Biosciences (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, 16.67% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 34.29% were posted by at least one author from the top 10 institutions publishing in the journal. Another 17.14% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 20.00% of all publications and 28.57% 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.
Patrick L. Combettes;Christian L. Müller
(2021)Md. Tuhin Sheikh;Ming-Hui Chen;Jonathan A. Gelfond;Joseph G. Ibrahim
(2021)Arnaud Monseur;Bradley P. Carlin;Bruno Boulanger;Andreea Seferian
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