The aim of CytoCam is to reduce the number of people becoming sick due to Campylobacter infected chickens through the development of a novel feed additive product from transgenic barley seeds. The feed additive contains a bioactive protein and can result in a significant 3-log reduction of Campylobacter count in the chicken gut. Additionally a cost-reward decision-making software demonstrating the benefits to the farmer will be generated.
The purpose of this website is to provide information, examples and tutorials on Bayesian networks in relation to the CytoCam project. The site will in part also be used to document the HUGIN CytoCam project activities.
You can find example models and apps under Resources
The HUGIN Swift Application Programming Interface (API) partly developed in the CytoCam project has been finalized and is now part of the official suite of APIs for the HUGIN Decision Engine. The HUGIN Swift API was released as part of HUGIN 8.6 on March 21st, 2018. The release notes for HUGIN 8.6 can be found here and you can read about the HUGIN Swift API in the HUGIN API Reference Manual section 1.2.1.
Under the menu item Resources you will find a number of examples on the use of Bayesian networks.
November 19, 2018: Annual Consortium Meeting, Bristol
October 3, 2017: Annual Consortium Meeting, Bristol
November 29, 2016: Consortium Meeting, Bristol
September 26, 2016: Work Package 4 meeting at DTU, Copenhagen
August 11, 2016: Kick-off meeting at ORF Genetics, Reykjavik
Disclaimer
HUGIN EXPERT A/S takes no responsibility whatsoever for examples and information in examples published on this web site. ALL EXAMPLES ARE FOR DEMONSTRATION PURPOSES ONLY.