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Artificial Intelligence in Bioinformatics -  Giuseppe Agapito,  Mario Cannataro,  Pietro Hiram Guzzi,  Marianna Milano,  Chiara Zucco

Artificial Intelligence in Bioinformatics (eBook)

From Omics Analysis to Deep Learning and Network Mining
eBook Download: EPUB
2022 | 1. Auflage
268 Seiten
Elsevier Science (Verlag)
978-0-12-822929-3 (ISBN)
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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. - 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

Mario Cannataro is a Full Professor of Computer Engineering and Bioinformatics at University 'Magna Graecia” of Catanzaro, Italy. He is the director of the Data Analytics research center and the chair of the Bioinformatics Laboratory. His current research interests include bioinformatics, medical informatics, artificial intelligence, sentiment analysis, data analytics, parallel and distributed computing. He is a member of the editorial boards of Briefings in Bioinformatics and IEEE/ACM Transactions on Computational Biology and Bioinformatics. He was guest editor of several special issues on bioinformatics and health informatics and organized several bioinformatics workshops in conjunction with ACM-BCB and IEEE-BIBM conferences. He has published three books and more than 300 papers in international journals and conference proceedings. Prof. Cannataro is a member of the Ethical Committee of the Calabria Region and a senior member of ACM, IEEE and SIBIM, He is currently a member of the steering committee of the Italian Bioinformatics Society (BITS) and of the Italian Association for Telemedicine and Medical Informatics (AITIM).
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. - 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
Erscheint lt. Verlag 12.5.2022
Sprache englisch
Themenwelt Mathematik / Informatik Informatik Theorie / Studium
Informatik Weitere Themen Bioinformatik
Medizin / Pharmazie
Naturwissenschaften Biologie Genetik / Molekularbiologie
ISBN-10 0-12-822929-2 / 0128229292
ISBN-13 978-0-12-822929-3 / 9780128229293
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