About this Journal
Statistical Applications in Genetics and Molecular Biology covers the application of statistical ideas to problems arising from computational biology. The range of topics is wide and includes topics such as linkage mapping, association studies, gene finding and sequence alignment, protein structure prediction, design and analysis of microarray data, molecular evolution and phylogenetic trees, DNA topology, and data base search strategies. Editors Nicholas P. Jewell (UC Berkeley), Gary Churchill (The Jackson Laboratory), and Elisabeth Thompson (University of Washington) are all highly respected scholars of biostatistics and genetics. Authors include renowned professors from UC Berkeley, Johns Hopkins University, the National Cancer Institute (NIH), European Molecular Biology Laboratory, and Memorial Sloan-Kettering Cancer Center.
Publication History
One issue/year, updated continuously
Content available since 2002 (Volume 1, Issue 1)
ISSN: 1544-6115
Archiving: all bepress journals are fully and permanently archived according to leading industry standards.
Archived in PubMedCentral
Statistical Applications in Genetics and Molecular Biology is fully compliant with the open access mandates of major government and foundation research grants. Starting in 2008, bepress automatically archives articles published in SAGMB in PubMedCentral and UKPubMedCentral twelve months after publication date. Authors always have the right to post their article to their personal web sites and their institution's repository with no delay, and without any special permission from bepress. For more information, see Policies.
Indexed in
- AGRICOLA
- Chemical Abstracts
- Current Index to Statistics (CIS)
- Current Contents/Life Sciences
- EMBASE
- MathSciNET
- PubMed/MEDLINE
- Science Citation Index (Thomson/ISI)
- Scopus
- Technology Research Database (CSA)
- Zentralblatt MATH
What scholars are saying about Statistical Applications in Genetics and Molecular Biology
This journal will keep statisticians up to date on the thinking behind the development and validation of molecular biology based classifiers for diagnostic testing for use in such areas as early detection of disease or recurrence, risk stratification, prognosis, prediction of treatment response, monitoring, and drug dosing.
Gene Pennello, Ph.D., Center for Devices and Radiological Health, FDA