biodegradation pathway
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2021 ◽  
pp. 117466
Author(s):  
Laura Ceresa ◽  
Alberto Guadagnini ◽  
Giovanni M. Porta ◽  
Monica Riva

2021 ◽  
Vol 413 ◽  
pp. 125310 ◽  
Author(s):  
Ting Zhou ◽  
Leipeng Cao ◽  
Qi Zhang ◽  
Yuhuan Liu ◽  
Shuyu Xiang ◽  
...  

2021 ◽  
Vol 414 ◽  
pp. 125549
Author(s):  
Lina Yang ◽  
Dehua Hu ◽  
Hailing Liu ◽  
Xiangfeng Wang ◽  
Yuan Liu ◽  
...  

2021 ◽  
Author(s):  
Jason Tam ◽  
Tim Lorsbach ◽  
Sebastian Schmidt ◽  
Jörg Wicker

The prediction of metabolism and biotransformation pathways of xenobiotics is a highly desired tool in environmental and life sciences. There are several systems that currently predict single transformation steps or complete pathways as series of parallel and subsequent steps. Their accuracy is often evaluated on the level of a single transformation step. Such an approach cannot account for some specific challenges that are related to the nature of the biotransformation experiments. This is particularly true for missing transformation products in the reference data that occur only in low concentrations, e.g. transient intermediates or higher-generation metabolites. Furthermore, some rulebased prediction systems evaluate accuracy only based on the defined set of transformation rules. Therefore, the performance of different models cannot be directly compared.


2021 ◽  
Vol 411 ◽  
pp. 125118
Author(s):  
Ericka Santacruz-Juárez ◽  
Ricardo E. Buendia-Corona ◽  
Ramsés E. Ramírez ◽  
Carmen Sánchez

2021 ◽  
Author(s):  
Jason Tam ◽  
Tim Lorsbach ◽  
Sebastian Schmidt ◽  
Jörg Wicker

The prediction of metabolism and biotransformation pathways of xenobiotics is a highly desired tool in environmental and life sciences. There are several systems that currently predict single transformation steps or complete pathways as series of parallel and subsequent steps. Their accuracy is often evaluated on the level of a single transformation step. Such an approach cannot account for some specific challenges that are related to the nature of the biotransformation experiments. This is particularly true for missing transformation products in the reference data that occur only in low concentrations, e.g. transient intermediates or higher-generation metabolites. Furthermore, some rulebased prediction systems evaluate accuracy only based on the defined set of transformation rules. Therefore, the performance of different models cannot be directly compared.


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