@misc{hudson_classifying_calpain_2016, 
author={Hudson, I.L., Leemaqz, S.Y., Neffe, A.T., Abell, A.D.},
title={Classifying calpain inhibitors for the treatment of cataracts: a Self Organising Map (SOM) ANN/KM approach in drug discovery},
year={2016},
howpublished = {book part},
doi = {https://doi.org/10.1007/978-3-319-28495-8_9},
abstract = {number of FNs by 64 % and FPs by 26 %, compared to the glide score alone. FPs were shown to be mostly esters and amides plus alcohols and non-classical, and FNs mainly aldehydes and ketones, masked aldehydes and ketones and Michael.},
note = {Online available at: \url{https://doi.org/10.1007/978-3-319-28495-8_9} (DOI). Hudson, I.; Leemaqz, S.; Neffe, A.; Abell, A.: Classifying calpain inhibitors for the treatment of cataracts: a Self Organising Map (SOM) ANN/KM approach in drug discovery. In: Shanmuganathan, S. (Ed.): Artificial Neural Network Modelling - Studies in Computational Intelligence. Springer. 2016. 161-212. DOI: 10.1007/978-3-319-28495-8_9}}