Statistics in Biosciences (SIB) is published three times a year in print and electronic form. It aims at development and application of statistical methods and their interface with other quantitative methods, such as computational and mathematical methods, in biological and life science, health science, and biopharmaceutical and biotechnological science.
SIB publishes scientific papers and review articles in four sections, with the first two sections as the primary sections. Original Articles publish novel statistical and quantitative methods in biosciences. The Bioscience Case Studies and Practice Articles publish papers that advance statistical practice in biosciences, such as case studies, innovative applications of existing methods that further understanding of subject-matter science, evaluation of existing methods and data sources. Review Articles publish papers that review an area of statistical and quantitative methodology, software, and data sources in biosciences. Commentaries provide perspectives of research topics or policy issues that are of current quantitative interest in biosciences, reactions to an article published in the journal, and scholarly essays. Substantive science is essential in motivating and demonstrating the methodological development and use for an article to be acceptable. Articles published in SIB share the goal of promoting evidence-based real world practice and policy making through effective and timely interaction and communication of statisticians and quantitative researchers with subject-matter scientists in biosciences.
- Presents development of statistical methods in quantitative biosciences
- Covers important data applications of statistical methods or computational algorithms
- Emphasized areas are statistics for health/life sciences, biomarkers and precision medicine, neuroimaging statistics, big or high-dimensional data, genetics/genomics statistics, statistical methods and designs for clinical trials
- Hongzhe Li,
- Mei-Cheng Wang
- Publishing model
- Hybrid. Open Access options available
- 88 days
- Submission to first decision
- 330 days
- Submission to acceptance
- 20,045 (2019)
Regression Models for Compositional Data: General Log-Contrast Formulations, Proximal Optimization, and Microbiome Data Applications
Authors (first, second and last of 5)
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About this journal
- Electronic ISSN
- Print ISSN
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- EBSCO Discovery Service
- Emerging Sources Citation Index
- Google Scholar
- Institute of Scientific and Technical Information of China
- Japanese Science and Technology Agency (JST)
- OCLC WorldCat Discovery Service
- ProQuest Biological Science Database
- ProQuest Central
- ProQuest Engineering
- ProQuest Materials Science and Engineering Database
- ProQuest Natural Science Collection
- ProQuest SciTech Premium Collection
- ProQuest Technology Collection
- ProQuest-ExLibris Primo
- ProQuest-ExLibris Summon
- Research Papers in Economics (RePEc)
- UGC-CARE List (India)