SONNIA - Self-Organizing Neural Network Package

SONNIA

SONNIA offers an interactive and visual approach to the analysis of chemical structure and reaction information based on a self-organizing neural network technique. It can be utilized for the prediction of physical, chemical and biological properties of compounds and for analyzing chemical reaction information.

SONNIA offers an interactive and visual approach to the analysis of chemical structure and reaction information based on a self-organizing neural network technique. It can be utilized for the prediction of physical, chemical and biological properties of compounds and for analyzing chemical reaction information.

SONNIA provides highly interactive and visual methods and, thus, assists scientists in gaining knowledge from data faster and to make better decisions about the next steps in any research and development project.

Features & Functionality

  • Provides unsupervised and supervised learning methods based on neural networks
  • Projects data from high-dimensional spaces into two-dimensional planes
  • Includes classification and clustering procedures
  • Enables modeling and prediction of complex relationships
  • Provides a highly interactive and intuitive graphical user interface
  • Visualization of underlying data such as chemical structures and reactions

User Interface

  • Graphical user interface with batch mode capabilities

Screenshot

screenshot of SONNIA

System Requirements

  • Microsoft Windows 7/8/10 (win32)

Additional Info

Downloadable PDFs

Slide Show

SONNIA - Analysis and Visualization of Chemical Data

Evaluation Version

A demo version is available on request free of charge. Please send us an e-mail to request a demo version.