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Read e-book online Artificial Neural Network for Drug Design, Delivery and PDF

By Munish Puri, Yashwant Pathak, Vijay Kumar Sutariya, Srinivas Tipparaju, Wilfrido Moreno

ISBN-10: 0128015594

ISBN-13: 9780128015599

ISBN-10: 0128017449

ISBN-13: 9780128017449

Artificial Neural community for Drug layout, supply and Disposition presents an in-depth examine using synthetic neural networks (ANN) in pharmaceutical learn. With its skill to benefit and self-correct in a hugely advanced atmosphere, this predictive instrument has large strength to assist researchers extra successfully layout, increase, and convey winning medicines.

This publication illustrates the way to use ANN methodologies and versions with the cause to regard illnesses like breast melanoma, cardiac sickness, and extra. It comprises the most recent state of the art examine, an research of the advantages of ANN, and proper examples. As such, this e-book is a necessary source for educational and researchers around the pharmaceutical and biomedical sciences.

  • Written through prime educational and scientists who've contributed considerably to the sphere and are on the leading edge of man-made neural community (ANN) research
  • Focuses on ANN in drug layout, discovery and supply, in addition to followed methodologies and their functions to the therapy of varied ailments and disorders
  • Chapters disguise very important subject matters around the pharmaceutical strategy, akin to ANN in structure-based drug layout and the appliance of ANN in sleek drug discovery
  • Presents the longer term power of ANN-based ideas in biomedical picture research and lots more and plenty more

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Additional resources for Artificial Neural Network for Drug Design, Delivery and Disposition

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Drug Discovery Today: Technol 2006;3:4. [12] Tejedor-Estrada R, Nonell S, Teixidó J, Sagristá ML, Mora M, Villanueva A, et al. An artificial neural network model for predicting the subcellular localization of photosensitisers for photodynamic therapy of solid tumours. Curr Med Chem 2012;19:2472e82. [13] Murphy RF. An active role for machine learning in drug development. Nat Chem Biol 2011;7: 327e30. [14] Xu JJ, Henstock PV, Dunn MC, Smith AR, Chabot JR, de Graaf D. Cellular imaging predictions of clinical drug-induced liver injury.

12] Tejedor-Estrada R, Nonell S, Teixidó J, Sagristá ML, Mora M, Villanueva A, et al. An artificial neural network model for predicting the subcellular localization of photosensitisers for photodynamic therapy of solid tumours. Curr Med Chem 2012;19:2472e82. [13] Murphy RF. An active role for machine learning in drug development. Nat Chem Biol 2011;7: 327e30. [14] Xu JJ, Henstock PV, Dunn MC, Smith AR, Chabot JR, de Graaf D. Cellular imaging predictions of clinical drug-induced liver injury. Toxicol Sci 2008;105(1):97e105.

They represent sites of impulse transmission across a population of neurons within the CNS. The most common synapse is between an axon and dendrite, although axosomatic synapse is also common. A neuron may receive synaptic input from thousands of presynaptic neurons and establish connections with a similar number of postsynaptic neurons. This summative synaptic connectivity creates immensely intricate neuronal circuits or network topologies.

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Artificial Neural Network for Drug Design, Delivery and Disposition by Munish Puri, Yashwant Pathak, Vijay Kumar Sutariya, Srinivas Tipparaju, Wilfrido Moreno


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