Chemical read-across is a commonly used technique to fill data gaps. Existing data for one substance (the source) is used to predict the same endpoint(s) for another substance (the target) that is lacking data and considered to be 'similar' in some way (e.g., structural similarity). Read-across is a subjective, expert-driven approach which is challenging from a reproducibility and scalability perspective. GenRA is an algorithmic approach to permit objective and reproducible read-across predictions of in vivo toxicity and in vitro bioactivity.
If you click on the link above and the target URL does not connect to a U.S. Federal website (i.e. does not send you to a .gov or .mil address), the following disclaimer applies:
Links to any non-Federal organizations are provided solely as a service to our users. These links do not constitute an endorsement of these organizations or their programs by FedCenter.gov or the Federal Government, and none should be inferred. Any reference to a commercial product, process, service, or company is not an endorsement or recommendation by the U.S. government, FedCenter, or any of its partners. FedCenter.gov is not responsible for the content of the individual organization Web pages found at these links.
Acquisition
