國立高雄大學圖資館 |

Language: English

Back

Artificial intelligence in bioinformaticsfrom omics analysis to deep learning and network mining /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Artificial intelligence in bioinformaticsMario Cannataro, Pietro Hiram Guzzi, Giuseppe Agapito, Chiara Zucco, Marianna Milano.
Reminder of title:	from omics analysis to deep learning and network mining /
other author:	Cannataro, Mario,
Published:	Amsterdam, Netherlands :Elsevier,2022.
Description:	1 online resource (xix, 247 p.) :ill.
Subject:	Bioinformatics.
Online resource:	https://www.sciencedirect.com/science/book/9780128229521
ISBN:	9780128229293$q(ebook)

Artificial intelligence in bioinformaticsfrom 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: 9780128229293$q(ebook)Subjects--Topical Terms:

194415
Bioinformatics.
Index Terms--Genre/Form:

214472
Electronic books.

LC Class. No.: QH324.25

Dewey Class. No.: 570.285

Artificial intelligence in bioinformaticsfrom omics analysis to deep learning and network mining /
LDR:02616nmm a2200277 a 4500 001 681234
006 m o d
007 cr nn |||muauu
008 251121s2022 ne a ob 001 0 eng d
020 $a 9780128229293$q(ebook)
020 $a 0128229292$q(ebook)
020 $z 9780128229521$q(paperback)
020 $z 0128229527$q(paperback)
035 $a (OCoLC)1317310170
035 $a on1317310170
040 $a YDX $b eng $e pn $c YDX $d OPELS $d EBLCP $d N $d OCLCF $d UKAHL $d OCLCQ $d WAU $d UKMGB $d OCLCO $d OCLCL $d SFB $d OCLCQ $d SXB $d OCLCL $d OCLCQ
041 0 $a eng
050 4 $a QH324.25
082 0 4 $a 570.285 $2 23
245 0 0 $a Artificial intelligence in bioinformatics $h [electronic resource] : $b from omics analysis to deep learning and network mining / $c Mario Cannataro, Pietro Hiram Guzzi, Giuseppe Agapito, Chiara Zucco, Marianna Milano.
260 $a Amsterdam, Netherlands : $b Elsevier, $c 2022.
300 $a 1 online resource (xix, 247 p.) : $b ill.
504 $a Includes bibliographical references and index.
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.
650 0 $a Bioinformatics. $3 194415
650 0 $a Artificial intelligence $x Biological applications. $3 238843
655 4 $a Electronic books. $2 local. $3 214472
700 1 $a Cannataro, Mario, $d 1964- $3 994315
700 1 $a Guzzi, Pietro Hiram, $d 1980- $e author. $3 896234
700 1 $a Agapito, Giuseppe, $d 1978- $3 994316
700 1 $a Zucco, Chiara. $3 994317
700 1 $a Milano, Marianna. $3 994318
776 0 8 $i Print version: $t Artificial intelligence in bioinformatics. $d Amsterdam : Elsevier, [2022] $z 9780128229521 $w (OCoLC)1328025903
856 4 0 $u https://www.sciencedirect.com/science/book/9780128229521