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Artificial Intelligence in Bioinformatics : From Omics Analysis to Deep Learn...

Description: Artificial Intelligence in Bioinformatics : From Omics Analysis to Deep Learning and Network Mining, Paperback by Cannataro, Mario; Guzzi, Pietro Hiram; Agapito, Giuseppe; Zucco, Chiara; Milano, Marianna, ISBN 0128229527, ISBN-13 9780128229521, Like New Used, Free shipping in the US Artificial Intelligence in Bioinformatics: From Omics Analysis to Deep Learning and Network Mining reviews the main applications of the topic, from omics analysis to deep learning and network mining. Th includes a rigorous introduction on bioinformatics, also reviewing how methods are incorporated in tasks and processes. In addition, it presents methods and theory, including content for emergent fields such as Sentiment Analysis and Network Alignment. Other sections survey how Artificial Intelligence is exploited in bioinformatics applications, including sequence analysis, structure analysis, functional analysis, protein classification, omics analysis, biomarker discovery, integrative bioinformatics, protein interaction analysis, metabolic networks analysis, and much more. Bridges the gap between computer science and bioinformatics, combining an introduction to Artificial Intelligence methods with a systematic review of its applications in the life sciences Brings readers up-to-speed on current trends and methods in a dynamic and growing field Provides academic teachers with a complete resource, covering fundamental concepts as well as applications

Price: 90.78 USD

Location: Jessup, Maryland

End Time: 2024-04-28T07:56:26.000Z

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Artificial Intelligence in Bioinformatics : From Omics Analysis to Deep Learn...

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Book Title: Artificial Intelligence in Bioinformatics : From Omics Analysis t

Item Length: 9.2in

Item Width: 7.5in

Author: Mario Cannataro, Marianna Milano, Giuseppe Agapito, Chiara Zucco, Pietro Hiram Guzzi

Publication Name: Artificial Intelligence in Bioinformatics : from Omics Analysis to Deep Learning and Network Mining

Format: Trade Paperback

Language: English

Publisher: Elsevier

Publication Year: 2022

Type: Textbook

Number of Pages: 268 Pages

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