Biodegradability prediction
Biodegradability prediction is
biologically-inspired computing and attempts to predict biodegradability of
anthropogenic materials in the
environment. Demand for biodegradability prediction is expected to increase with governments stepping up environmental regulations (see, for instance, testing for
bioaccumulation in the
REACH proposal).
Example:
* Development of
quantitative structure-activity relationship (QSARs) for
biodegradation, for instance,
biochemical oxygen demand for chemicals released into the environment with the aid of
machine learning and other
artificial intelligence methods
[Artificial Intelligence & biodegradability paper James R. Baker, Dragan Gamberger, James R. Mihelcic and Aleksandar Sabljić (2004) "Evaluation of Artificial Intelligence Based Models for Chemical Biodegradability Prediction", Molecules , 9, 989-1004].
* The
University of Minnesota Biocatalysis and Biodegradation Database (UM-BBD), which contains information on microbial biocatalytic reactions and biodegradation pathways for primarily xenobiotic, chemical compounds. One of its many features allows the prediction of microbial catabolic reactions using substructure searching, a rule-base, and atom-to-atom mapping.
*
Anaerobic digestion*
Biodegradation*
Composting*
list of environment topics*
list of ecology topics*
UM-BBD
