0 Datasets
0 Files
Get instant academic access to this publication’s datasets.
Yes. After verification, you can browse and download datasets at no cost. Some premium assets may require author approval.
Files are stored on encrypted storage. Access is restricted to verified users and all downloads are logged.
Yes, message the author after sign-up to request supplementary files or replication code.
Join 50,000+ researchers worldwide. Get instant access to peer-reviewed datasets, advanced analytics, and global collaboration tools.
✓ Immediate verification • ✓ Free institutional access • ✓ Global collaborationJoin our academic network to download verified datasets and collaborate with researchers worldwide.
Get Free AccessThe analysis of tumor growth curves is standard practice in experimental oncology including tumor immunology. In experimental oncology, cancer cells are inoculated into rodents (mostly mice) and their growth is monitored by measuring tumor diameter, surface or volume over time as a function of distinct treatments. Then, different groups of tumors/treatments are compared among each other for their evolution and possible responses to treatment. The R package TumGrowth has been created as a software tool allowing to carry out a series of statistical comparisons across or between groups of tumor growth curves obtained in a standard laboratory, for experimenters with limited knowledge in statistics. TumGrowth is freely available online at https://kroemerlab.shinyapps.io/TumGrowth/ and can be downloaded into any computer. It offers an exhaustive panoply of tools to visualize and analyze complex data sets including longitudinal, cross-sectional and time-to-endpoint measurements.
David Enot, Erika Vacchelli, Nicolas Jacquelot, Laurence Zitvogel, Guido Guido Kroemer (2018). TumGrowth: An open-access web tool for the statistical analysis of tumor growth curves. , 7(9), DOI: https://doi.org/10.1080/2162402x.2018.1462431.
Datasets shared by verified academics with rich metadata and previews.
Authors choose access levels; downloads are logged for transparency.
Students and faculty get instant access after verification.
Type
Article
Year
2018
Authors
5
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.1080/2162402x.2018.1462431
Access datasets from 50,000+ researchers worldwide with institutional verification.
Get Free Access
