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Elsevier

Artificial Intelligence in Bioinformatics

From Omics Analysis to Deep Learning and Network Mining

  • 1st Edition - May 12, 2022
  • Latest edition
  • Authors: Mario Cannataro, Pietro Hiram Guzzi, Giuseppe Agapito, Chiara Zucco, Marianna Milano
  • Language: English

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… Read more

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Description

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.

Key features

  • 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

Readership

Students and researchers in biomedicine and life science, working on bioinformatics, systems biology, molecular biology and biotechnology; computer scientists and engineers working on artificial intelligence methods and their applications in bioinformatics

Table of contents

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

Product details

  • Edition: 1
  • Latest edition
  • Published: May 12, 2022
  • Language: English

About the authors

MC

Mario Cannataro

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.

Affiliations and expertise
University "Magna Græcia" of Catanzaro, Italy

PG

Pietro Hiram Guzzi

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.
Affiliations and expertise
Assocaite Professor of Computer Engineering, University of Magna Græcia, Catanzaro, Italy

GA

Giuseppe Agapito

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.
Affiliations and expertise
Assistant Professor of Computer Engineering, University Magna Graecia of Catanzaro, Catanzaro, Italy

CZ

Chiara Zucco

Chiara Zucco received her Master Degree in Mathematics at the University of Calabria. She currently is a third-year Ph.D. student in the Biomarkers of Chronic and Complex Diseases Ph.D. Program at University “Magna Graecia” of Catanzaro, Italy. Her Ph.D. research is mainly focused on applying Text Mining and in particular Sentiment Analysis techniques for patient monitoring and adverse events prediction. She is also interested in Explainable Artificial Intelligence.
Affiliations and expertise
University Magna Graecia of Catanzaro, Catanzaro, Italy

MM

Marianna Milano

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).
Affiliations and expertise
University Magna Graecia of Catanzaro, Catanzaro, Italy

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