Cargando…
Descriptor Free QSAR Modeling Using Deep Learning With Long Short-Term Memory Neural Networks
Current practice of building QSAR models usually involves computing a set of descriptors for the training set compounds, applying a descriptor selection algorithm and finally using a statistical fitting method to build the model. In this study, we explored the prospects of building good quality inte...
Autores principales: | Chakravarti, Suman K., Alla, Sai Radha Mani |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7861338/ https://www.ncbi.nlm.nih.gov/pubmed/33733106 http://dx.doi.org/10.3389/frai.2019.00017 |
Ejemplares similares
-
Detecting sarcasm in multi-domain datasets using convolutional neural networks and long short term memory network model
por: Jamil, Ramish, et al.
Publicado: (2021) -
Software defect prediction using hybrid model (CBIL) of convolutional neural network (CNN) and bidirectional long short-term memory (Bi-LSTM)
por: Farid, Ahmed Bahaa, et al.
Publicado: (2021) -
Long-short term memory networks for modeling track geometry in laser metal deposition
por: Perani, Martina, et al.
Publicado: (2023) -
Relation extraction in Chinese using attention-based bidirectional long short-term memory networks
por: Zhang, Yanzi
Publicado: (2023) -
Research on emotion classification technology of movie reviews based on topic attention mechanism and dual channel long short term memory
por: Wang, Yufei
Publicado: (2023)