Artificial Intelligence in Bioinformatics

From Omics Analysis to Deep Learning and Network Mining
Erscheinungsjahr 2022
ISBN: 978-0-12-822952-1
Verlag: Elsevier Science Publishing Co Inc

Buch, Englisch, 268 Seiten, Format (B × H): 234 mm x 189 mm, Gewicht: 548 g

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.

Autoren/Hrsg.

Zucco, Chiara

Guzzi, Pietro Hiram

Agapito, Giuseppe

Milano, Marianna

Cannataro, Mario

Fachgebiete

• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizinische Mathematik & Informatik

Inhaltsverzeichnis

PART 1 ARTIFICIAL INTELLIGENCE: METHODS 1. Knowledge Representation and Reasoning 2. Machine Learning 3. Artificial Intelligence 4. Data Science 5. Deep Learning 6. Explainability of AI methods 7. Intelligent Agents

PART 2 ARTIFICIAL INTELLIGENCE: BIOINFORMATICS 8. Sequence Analysis 9. Structure Analysis 10. Omics Sciences 11. Ontologies in Bioinformatics 12. Integrative Bioinformatics 13. Biological Networks Analysis 14. Biological Pathway Analysis 15. Knowledge Extraction from Biomedical Texts 16. Artificial Intelligence in Bioinformatics: Issues and Challenges

Über Autor(innen)

Agapito, Giuseppe
Giuseppe Agapito is an assistant professor of computer engineering with the University Magna Græcia, Catanzaro, Italy. His current research interests include analysis and visualization of biological networks, efficient analysis of genomics data, parallel computing, and data mining. In particular, the research activity is focused on the development and implementation of statistical and data mining methodologies also based on parallel and distributed computing, for the efficient analysis of omics data. He has published over 70 articles for international journals and conference proceedings. He is a member of the ACM, ACM SIGBio, and BITS.

Guzzi, Pietro Hiram
Pietro Hiram Guzzi the Ph.D. degree in biomedical engi- neering from Magna Græcia University, Italy, in 2008. He has been an Associate Professor of computer engineering with Magna Græcia Univer- sity since 2008. He has been a Visiting Researcher with Georgia Tech University, Atlanta. He has authored two books. His research interests include semantic-based and network-based analysis of biological and clinical data. He is a member of the ACM, BITS, ISMB, and NETBIO COSI. He is an Editor of a newsletter of the ACM Special Interest Group on Bioinformatics, Computational Biology, and Biomedical Informatics (SIGBio), and the IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS. He serves the scientific community as a reviewer for many conferenceS. He wrote two books and he edited another one.

Milano, Marianna
Marianna Milano received her Master Degree in Computer Engineering from the University "Magna Graecia" of Catanzaro, Italy, in 2011 and the Ph.D. degree in Biomarkers of Chronic and Complex Diseases at the University "Magna Graecia" of Catanzaro, Italy, in 2019. Her research interests comprise semantic-based and network-based analysis of biological and clinical data. She is a member of BITS (Italian Bioinformatics Society).