Sarvision | SM

Product  Overview

SARvision|SM (Small Molecules) is a desktop application to assist you in the visualization, mining and organization of chemical data. The program automatically identifies chemotypes in a chemical library and organizes them into a tree structure. It has great flexibility in the definition of chemotypes, and it can filter data by scaffold type or any associated data, such as HTS results and physicochemical data. It is a fast solution to identify chemotypes responsible for a given activity.

SARvision|SM allows you to identify chemotypes automatically, organize scaffolds in a hierarchical tree, create easily R-group tables, highlight active compounds with heat maps, enumerate libraries, visualize data with plots that relate to chemotypes, filter tables by selected property ranges, Search libraries with multiple queries at once, Seamless connectivity with Word and Excel, Integrate with data piping or visualization tools, create diverse libraries based on chemotypes. Its capabilities for Match Molecular Pairs and Scaffold hopping are powerful for data analysis.

SARvision | SM can be integrated with AMEDEO to provide access to Machine Learning tools that can be useful for prediction of activity or other parameters and help in the design of better compounds. 

There are many ways to integrate SARvision|SM into your enterprise, including working with products such as CDDVault or direct integration with your enterprise architecture. 

Contact us for more information.

 

Patcore logo                                                                                       

is our exclusive distributor for Japan.                                                                    

"Currently, the tools for managing peptide data in a robust manner lag far behind those used for small molecule data. Recently, Hansen and co-workers described an informatics tool for handling biopolymer data such as peptides and biologics. This tool fills an important gap in peptide data management and analysis. "

Diller et al. Computers in Biology and Medicine, vol. 92 (2018)

For More information contact us:

1 + 7 =