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Artificial intelligence in bioinformatics
Paperback
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- Book Synopsis
- 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. The book 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.
- About The Author
- Mario Cannataro is Full Professor of Computer Engineering and Bioinformatics at the University "Magna Graecia of Catanzaro, Italy. He directs the Data Analytics Research Center and chairs the Bioinformatics Laboratory, leading interdisciplinary research at the interface of computing and life sciences. His research interests include bioinformatics, medical informatics, artificial intelligence, data analytics, sentiment analysis, and parallel and distributed computing. Professor Cannataro is actively involved in the international bioinformatics community through editorial, conference, and professional service activities, including participation in scientific committees, workshop organization, and journal editorial boards. He has contributed extensively to research and innovation in computational biology and health informatics and has authored numerous scholarly publications and books. He also serves on regional and national bodies related to bioinformatics, telemedicine, medical informatics, and research ethics, supporting collaboration and advancement across these fields.
- Product Details
-
- ISBN
- 9780128229521
- Format
- Paperback
- Publisher
- Elsevier, (18 May 2022)
- Number of Pages
- 268
- Weight
- 540 grams
- Language
- English
- Dimensions
- 189 x 234 x 18 mm
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