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Big Data in Predictive Toxicology (Hardcover) Loot Price: R6,284
Discovery Miles 62 840
Big Data in Predictive Toxicology (Hardcover): Daniel Neagu, Andrea-Nicole Richarz

Big Data in Predictive Toxicology (Hardcover)

Daniel Neagu, Andrea-Nicole Richarz

Series: Issues in Toxicology, Volume 41

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Loot Price R6,284 Discovery Miles 62 840 | Repayment Terms: R589 pm x 12*

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The rate at which toxicological data is generated is continually becoming more rapid and the volume of data generated is growing dramatically. This is due in part to advances in software solutions and cheminformatics approaches which increase the availability of open data from chemical, biological and toxicological and high throughput screening resources. However, the amplified pace and capacity of data generation achieved by these novel techniques presents challenges for organising and analysing data output. Big Data in Predictive Toxicology discusses these challenges as well as the opportunities of new techniques encountered in data science. It addresses the nature of toxicological big data, their storage, analysis and interpretation. It also details how these data can be applied in toxicity prediction, modelling and risk assessment. This title is of particular relevance to researchers and postgraduates working and studying in the fields of computational methods, applied and physical chemistry, cheminformatics, biological sciences, predictive toxicology and safety and hazard assessment.

General

Imprint: Royal Society of Chemistry
Country of origin: United Kingdom
Series: Issues in Toxicology, Volume 41
Release date: December 2019
Editors: Daniel Neagu • Andrea-Nicole Richarz
Dimensions: 234 x 156 x 36mm (L x W x T)
Format: Hardcover - Unsewn / adhesive bound
Pages: 394
ISBN-13: 978-1-78262-298-7
Categories: Books > Science & Mathematics > Chemistry > General
Books > Medicine > General issues > Medical equipment & techniques > General
Books > Medicine > Other branches of medicine > Pharmacology > Medical toxicology
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LSN: 1-78262-298-5
Barcode: 9781782622987

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