NPClassifier: A Deep Neural Network-Based Structural Classification Tool for Natural Products
By Hyun Woo Kim, Mingxun Wang, Christopher A. Leber, Louis-Félix Nothias, Raphael, Reher, K. Kang, J. J. Hooft, Pieter C. Dorrestein, H. William and 2 more. Journal of Natural Products, 2020
431 citations recorded by the source corpus.
Computational approaches such as genome and metabolome mining are becoming essential to natural products (NPs) research. Consequently, a need exists for an automated structure-type classification system to handle the massive amounts of data appearing for NP structures. An ideal semantic ontology for the classification of NPs should go beyond the simple presence/absence of chemical substructures, but also include the taxonomy of the producing organism, the nature of the biosynthetic pathway, and/or their biological properties. Thus, a holistic and automatic NP classification framework could have considerable value to comprehensively navigate the relatedness of NPs, and especially so when analyzing large numbers of NPs. Here, we introduce NPClassifier, a deep-learning tool for the automated structural classification of NPs from their counted Morgan fingerprints. NPClassifier is expected to accelerate and enhance NP discovery by linking NP structures to their underlying properties.
Subfields: Computational Theory and Mathematics, Molecular Biology, Pharmacology
View Paper: https://www.semanticscholar.org/paper/b546fdd3a7f8a7fbd3eb50ceb9ee213870646919
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In Computational Theory and Mathematics
- Philippe Schwaller
- Maria Sorokina
- Marwin H. S. Segler
- Marcy J. Balunas
- Andrea Volkamer
- Sergey I. Nikolenko
In Molecular Biology
- Kai Blin
- Philippe Schwaller
- Marnix H. Medema
- Nadine Ziemert
- Maria Sorokina
- Marwin H. S. Segler
- Djork-Arné Clevert
- Marcy J. Balunas
In Pharmacology
Citations in the corpus
- Artificial Intelligence For Natural Product Drug Discovery (2023, methodology): “For example, CANOPUS 28 , a deep neural network-based structure class annotation tool that is based on MS spectra, uses other AI tools including ClassyFire 151 and NPClassifier 29 to label data and thus train the network.”