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Artificial intelligence in bioinformatics = from omics analysis to deep learning and network mining /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Artificial intelligence in bioinformatics/ Mario Cannataro, Pietro Hiram Guzzi, Giuseppe Agapito, Chiara Zucco, Marianna Milano.
其他題名:	from omics analysis to deep learning and network mining /
其他作者:	Cannataro, Mario,
出版者:	Amsterdam, Netherlands :Elsevier, : 2022.,
面頁冊數:	1 online resource (xix, 247 p.) :ill.
內容註:	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 -- 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 -- Appendix A: Python code examples -- Appendix B: Java code examples.
標題:	Bioinformatics. -
電子資源:	https://www.sciencedirect.com/science/book/9780128229521
ISBN:	9780128229293

Artificial intelligence in bioinformatics = from omics analysis to deep learning and network mining /
Artificial intelligence in bioinformaticsfrom omics analysis to deep learning and network mining /[electronic resource] :Mario Cannataro, Pietro Hiram Guzzi, Giuseppe Agapito, Chiara Zucco, Marianna Milano. - Amsterdam, Netherlands :Elsevier,2022. - 1 online resource (xix, 247 p.) :ill.

Includes bibliographical references and index.

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 -- 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 -- Appendix A: Python code examples -- Appendix B: Java code examples.

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.--

ISBN: 9780128229293Subjects--Topical Terms:

553671
Bioinformatics.
Index Terms--Genre/Form:

542853
Electronic books.

LC Class. No.: QH324.25

Dewey Class. No.: 570.285

Artificial intelligence in bioinformatics = from omics analysis to deep learning and network mining /
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505 0 $a 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 -- 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 -- Appendix A: Python code examples -- Appendix B: Java code examples.
520 $a 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.-- $c Provided by publisher.
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