Making the Case: In Silico Prediction of Ames Test Mutagenicity

Rich Apodaca — Thu, 28 Dec 2006 15:09:00 +0000

The two models (SAm and AIm) and the RHC [robust hybrid classifier] were implemented in C++ using OpenBabel 1.100.2 libraries (http://openbabel.sourceforge.net/wiki/Main_Page).

The AI model (AIm) is based on the LAZAR system (http://www.predictive-toxicology.org/lazar/index.html) developed by C. Helma...

-Paolo Mazzatorta, Liên-Anh Tran, Benoît Schilter, and Martin Grigorov J. Chem. Inf. Model.

Yet another appearance of Open Source software in the primary cheminformatics literature comes by way of a paper from Mazzatorta, Tran, Shilter, and Grigorov of the Nestlé Research Center. This work employs two Open Source libraries: lazar, a tool for the prediction of toxic properties of chemical structures; and Open Babel, a widely-used, low-level library for cheminformatics. lazar, in turn, is based on both Open Babel and the GNU Scientific Library (GSL), a numerical library. Unfortunately, the Nestlé authors don't indicate whether the source code for their system is publicly available. Nevertheless, their work gives a taste of the kinds of synergies that inevitably develop through the the use of Open Source software.

Depth-First: Making the Case: In Silico Prediction of Ames Test Mutagenicity

Making the Case: In Silico Prediction of Ames Test Mutagenicity