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Big Data Analytics in Chemoinformatics and Bioinformatics

With Applications to Computer-Aided Drug Design, Cancer Biology, Emerging Pathogens and Computational Toxicology

Jezik AngleščinaAngleščina
Knjiga Mehka
Knjiga Big Data Analytics in Chemoinformatics and Bioinformatics Subhash Basak
Koda Libristo: 36495741
Založba Elsevier - Health Sciences Division, december 2022
Big Data Analytics in Chemoinformatics and Bioinformatics provides an up-to-date presentation of big... Celoten opis
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Big Data Analytics in Chemoinformatics and Bioinformatics provides an up-to-date presentation of big data analytics methods and their applications in diverse fields. Various aspects of science, technology, and health care are affected by big data and associated prediction tools. The proper management of big data for decision making in scientific and social issues is of paramount importance. This book gives researchers the tools they need to solve big data problems in these fields. The book begins with a section on general topics that all readers will find useful, and it continues with specific sections covering a range of interdisciplinary applications. An international team of leading experts review their respective fields and present their own latest research findings, and case studies are utilized throughout to analyze and present key information. Brings together the current knowledge on the most important aspects of big data, such as analyses using deep learning and fuzzy logic, transparency and data protection, disparate data analytics, and scalability of big data domainCovers many applications of big data analysis in diverse fields such as chemistry, chemoinformatics, bioinformatics, computer-assisted drug/vaccine design, characterization of emerging pathogens, and environmental protectionHighlights the considerable benefits offered by big data analytics to science, biomedical fields and industry

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O knjigi

Polni naslov Big Data Analytics in Chemoinformatics and Bioinformatics
Jezik Angleščina
Vezava Knjiga - Mehka
Datum izida 2022
Število strani 514
EAN 9780323857130
Koda Libristo 36495741
Teža 661
Mere 152 x 229
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