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Advanced AI Techniques and Applications in Bioinformatics [Pehme köide]

Edited by (GBU), Edited by , Edited by (Taylors University, Malaysia), Edited by (Amity University, Noida, India)
  • Formaat: Paperback / softback, 282 pages, kõrgus x laius: 234x156 mm, kaal: 453 g, 22 Tables, black and white; 73 Line drawings, black and white; 1 Halftones, black and white; 74 Illustrations, color
  • Sari: Smart and Intelligent Computing in Engineering
  • Ilmumisaeg: 27-May-2024
  • Kirjastus: CRC Press
  • ISBN-10: 0367647672
  • ISBN-13: 9780367647674
Teised raamatud teemal:
Advanced AI Techniques and Applications in Bioinformatics
  • Formaat: Paperback / softback, 282 pages, kõrgus x laius: 234x156 mm, kaal: 453 g, 22 Tables, black and white; 73 Line drawings, black and white; 1 Halftones, black and white; 74 Illustrations, color
  • Sari: Smart and Intelligent Computing in Engineering
  • Ilmumisaeg: 27-May-2024
  • Kirjastus: CRC Press
  • ISBN-10: 0367647672
  • ISBN-13: 9780367647674
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9780367647674.html
Märksõnad:
This book covers the recent approaches in artificial intelligence and machine learning methods and their applications in Genome and Gene editing, cancer drug discovery classification, and the protein folding algorithms among others.

The advanced AI techniques are essential for resolving various problematic aspects emerging in the field of bioinformatics. This book covers the recent approaches in artificial intelligence and machine learning methods and their applications in Genome and Gene editing, cancer drug discovery classification, and the protein folding algorithms among others. Deep learning, which is widely used in image processing, is also applicable in bioinformatics as one of the most popular artificial intelligence approaches. The wide range of applications discussed in this book are an indispensable resource for computer scientists, engineers, biologists, mathematicians, physicians, and medical informaticists.

 

Features:

  1. Focusses on the cross-disciplinary relation between computer science and biology and the role of machine learning methods in resolving complex problems in bioinformatics

  2. Provides a comprehensive and balanced blend of topics and applications using various advanced algorithms

  3. Presents cutting-edge research methodologies in the area of AI methods when applied to bioinformatics and innovative solutions

  4. Discusses the AI/ML techniques, their use, and their potential for use in common and future bioinformatics applications

    5. Includes recent achievements in AI and bioinformatics contributed by a global team of researchers



    6. This book covers the recent approaches in artificial intelligence and machine learning methods and their applications in Genome and Gene editing, cancer drug discovery classification, and the protein folding algorithms among others.

    Contents

    Contributors..............................................................................................................vii

    Editors........................................................................................................................xi

    Chapter 1

    An Artificial Intelligence-based Expert System for the Initial

    Screening of COVID-19........................................................................1

    Anurag Sharma, Hitesh Marwaha, Vikrant Sharma and Love Kumar

    Chapter 2

    An Insight into the Potential Role of Artificial Intelligence in

    Bioinformatics..................................................................................... 17

    Divya Bhatia and Deepak Malik

    Chapter 3

    AI-Based Natural Language Processing for the Generation of

    Meaningful Information Electronic Health Record (EHR) Data....... 41

    Kuldeep Singh Kaswan, Loveleen Gaur, Jagjit Singh

    Dhatterwal, and Rajesh Kumar

    Chapter 4

    AI and Genomes for Decisions Regarding the Expression of

    Genes...............................................................................................87

    Abeedha Tu-Allah Khan and Haleema Qamar

    Chapter 5

    Implementation of Donor Recognition and Selection for

    Bioinformatics Blood Bank Application........................................... 105

    Soobia Saeed, N.Z. Jhanjhi, and Memood Naqvi

    Chapter 6

    Deep Learning Techniques for miRNA Sequence Analysis............. 139

    Saswati Mahapatra, Jayashankar Das, David Correa

    Martins-Jr, and Tripti Swarnkar

    Chapter 7

    Role of Machine Intelligence in Cancer Drug Discovery and

    Development...................................................................................... 153

    Kaushik Kumar Bharadwaj, Bijuli Rabha, Gaber El-Saber

    Batiha, Debabrat Baishya, and Arabinda Ghosh

    Chapter 8

    Genome and Gene Editing by Artificial Intelligence Programs....... 165

    Imran Zafar, Aamna Rafique, Javaria Fazal, Misbah Manzoor,

    Qurat Ul Ain, and Rehab A. Rayan

    Chapter 9

    Artificial Neural Network (ANN) Techniques in Solving the

    Protein Folding Problem................................................................... 189

    Raghunath Satpathy

    Chapter 10

    Application of Machine Learning and Molecular Modeling in

    Drug Discovery and Cheminformatics............................................. 201

    Manish Kumar Tripathi, Sushant Kumar Shrivastava, S.

    Karthikeyan, Dhiraj Sinha, and Abhigyan Nath

    Chapter 11

    Role of Advanced Artificial Intelligence Techniques in

    Bioinformatics................................................................................... 215

    Harshit Bhardwaj, Pradeep Tomar, Aditi Sakalle,

    and Uttam Sharma

    Chapter 12

    A Bioinformatics Perspective on Artificial Intelligence in

    Healthcare and Diagnosis: Applications, Implications, and

    Limitations........................................................................................227

    Anuradha Bhardwaj, Arun Solanki, and Vikrant Nain

    Chapter 13

    Accelerating Translational Medical Research by Leveraging

    Artificial Intelligence: Digital Healthcare........................................ 243

    G. M. Roopa, K. Shryavani, N. Pradeep, and Vicente Garcia Diaz

    Index

    .......................................................................................................................265

    Prof. Loveleen Gaur is the Professor and Program Director (Artificial Intelligence and Business Intelligence and Data Analytics) of the Amity International Business School, Amity University, Noida, India. She is a senior IEEE member and series editor with CRC Press and Wiley. Prof. Gaur is an established author and researcher; she has filed five patents and two copyrights in AI-IoT. For over 18 years she served in India and abroad in different capacities. She has specialized in the fields of artificial intelligence, the Internet of Things, data analytics, data mining, and business intelligence. Prof. Gaur has pursued research in truly inter-disciplinary areas and has authored and co-authored books with renowned international and national publishers like Elsevier, Springer, and Taylor & Francis. She was invited to be guest editor for reputed Springer and Emerald Q1 journals. She has published many research papers in SCI and Q1 journals. She has chaired various positions in international conferences of repute and is a reviewer with top-rated journals of IEEE, SCI, and ABDC.

    Dr. Arun Solanki is an Assistant Professor in the Department of Computer Science and Engineering at Gautam Buddha University, Greater Noida, India. He received his Ph.D. in Computer Science and Engineering from Gautam Buddha University in 2014. He has supervised more than 60 dissertations and has published many research articles in Scopus indexed international journals. Dr. Solanki is the editor of several published books and a reviewer in journals published by reputed publishers.

    Dr. Samuel Fosso Wamba is a Professor at Toulouse Business School in France. He earned his Ph.D. in industrial engineering at the Polytechnic School of Montreal, Canada. His current research focuses on SCM, E&M-commerce, IT-enabled social inclusion, blockchain, social media, business analytics, big data, and artificial intelligence. He is academic co-founder of RFID Academia, and founder and CEO of e-m-RFID. He has published papers in IS and OM journals and conferences. He is the guest editor of various special issues on IT/RFID/big data for various IS and OM conferences and journals. He is the head of the newly created Artificial Intelligence and Business Analytics Cluster at Toulouse Business School.

    Dr. Noor Zaman Jhanjhi is an Associate Professor at Taylor University, Malaysia, with 20 years of rich experience. He is an associate editor for several reputable journals including IEEE Access and PC, and a board member for several IEEE conferences around the globe. He is an active reviewer for a series of quality journals. He has authored several research papers in WoS/ISI indexed journals and in impact factor research IEEE journals, has edited 12 books in computer science, and has supervised a number of postgraduate students. He has successfully completed more than 19 international funded research grants.