Showing results (1-10 of 89) with videos related to
Sort By:
Pageof 9
Molecular Informatics|August 4, 2016
Topological Fingerprints as an Aid in Finding Structural Patterns for LRRK2 InhibitionIiris Kahn, Andre Lomaka, Mati KarelsonJournal of Chemical Information and Modeling|May 23, 2006
Open computing grid for molecular science and engineeringSulev Sild, Uko Maran, Andre Lomaka, et al.Bioorganic & Medicinal Chemistry Letters|November 7, 2002
Six-membered cyclic ureas as HIV-1 protease inhibitors: a QSAR study based on CODESSA PRO approach. Quantitative structure-activity relationshipsAlan R Katritzky, Alexander Oliferenko, Andre Lomaka, et al.Journal of Chemical Information and Modeling|January 26, 2005
QSPR treatment of the soil sorption coefficients of organic pollutantsIiris Kahn, Dan Fara, Mati Karelson, et al.Journal of Chemical Information and Computer Sciences|July 23, 2002
Prediction of ultraviolet spectral absorbance using quantitative structure-property relationshipsWilliam L Fitch, Malcolm McGregor, Alan R Katritzky, et al.Journal of Toxicology and Environmental Health. Part A|January 16, 2010
Quantitative structure-activity relationship (QSAR) modeling of EC50 of aquatic toxicities for Daphnia magnaAlan R Katritzky, Svetoslav H Slavov, Iva S Stoyanova-Slavova, et al.Journal of Chemical Information and Computer Sciences|March 26, 2002
Correlation of the melting points of potential ionic liquids (imidazolium bromides and benzimidazolium bromides) using the CODESSA programAlan R Katritzky, Ritu Jain, Andre Lomaka, et al.Journal of Chemical Information and Computer Sciences|February 22, 2002
QSPR correlation of the melting point for pyridinium bromides, potential ionic liquidsAlan R Katritzky, Andre Lomaka, Ruslan Petrukhin, et al.Current Topics in Medicinal Chemistry|December 10, 2002
The present utility and future potential for medicinal chemistry of QSAR/QSPR with whole molecule descriptorsAlan R Katritzky, Dan C Fara, Ruslan O Petrukhin, et al.Expert Opinion on Drug Discovery|June 2, 2012
Using artificial neural networks to predict cell-penetrating compoundsMati Karelson, Dimitar DobchevPageof 9