Computational Intelligence in Epigenetics, Cellular and Mitochondrial Functions

1. Auflage 2026
ISBN: 978-1-041-06253-0
Verlag: Taylor & Francis Ltd

Buch, Englisch, 388 Seiten, Format (B × H): 156 mm x 234 mm

This book analyzes the integrated model of artificial intelligence, deep learning, and cloud computing for various bioinformatic problems, including gene signature discovery, rare cell detection, disease classification, and rare disease detection. It discusses biomedical image processing and deep learning integrated tools for the stage detection of critical diseases like cancer.

This book:

• Presents a comparative study of gradient-boosted classifier and deep learning classifier for disease classification of multi-omics sequencing data.

• Showcases biomarker discovery and differential expression analysis in single-cell RNA sequencing data through the integrated model of data imputation, feature selection, and cell clustering.

• Explains artificial intelligence, machine learning, and integrated models for DNA methylation and gene expression data analysis and disease classification.

• Covers the fundamentals of artificial intelligence, machine learning, deep learning, and cloud computing tools in bioinformatics.

• Explores rare cell detection and transcriptomic analysis in single-cell RNA sequencing.

It is primarily written for senior undergraduates, graduate students, and academic researchers in electrical engineering, electronics and communications engineering, computer science and engineering, and biomedical engineering.

Zielgruppe

Academic, Postgraduate, and Undergraduate Advanced

Autoren/Hrsg.

Mallik, Saurav

Zhao, Zhongming

Tomar, Namrata

Seth, Soumita

Umer, Saiyed

Bhadra, Tapas

Rout, Ranjeet Kumar

Fachgebiete

• Technische Wissenschaften Energietechnik | Elektrotechnik Elektrotechnik
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizintechnik, Biomedizintechnik, Medizinische Werkstoffe
• Technische Wissenschaften Sonstige Technologien | Angewandte Technik Medizintechnik, Biomedizintechnik
• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik
• Mathematik | Informatik EDV | Informatik Technische Informatik

Inhaltsverzeichnis

1. Biomedical Image Processing Meets Deep Learning: A Review of Current Trends in Cancer Stage Detection. 2. Transforming Cancer Detection: The Impact of Deep Learning on Biomedical Imaging. 3. Decoding Morphological Cues in MRI for Brain Lesion Delineation. 4. AI-Driven Classification and Biomarker Discovery in Alzheimer's Disease: Toward Early Detection and Therapeutic Insight. 5. Machine Learning-Driven DNA Mutation Detection and CRISPR Gene Editing Visualization Techniques. 6. Deciphering the methylome landscape using AI for Cancer precision medicine. 7. Integrative Multi-omics for Cancer Diagnosis and Therapy: Computational Approaches to Epigenetics, Cellular Dynamics and Mitochondrial Function. 8. Advancing Gene Regulatory Network Inference: Hybrid Modeling, Scalability, and Network-Level Insights. 9. Biomarker Discovery and Differential Expression Analysis In Single Cell Sequencing Data Through the Integrated Model of Data Imputation, Feature Selection, Cell Clustering. 10. Business Analytics–Driven Insights into Epigenetics, Cellular Dynamics, and Mitochondrial Function Using Computational Intelligence. 11. Revolutionizing Biometric Systems with Multi-Agent AI: LLMs, MoNE Optimization, and Cloud Integration. 12. Integrating Multiple Views with HMMs and Neural Nets for Accurate Protein Secondary Structure Prediction. 13. Integrative Computational Models for Predicting Crop Traits Using Multi-OMICs Data.14. Application of Nanotechnology in Cancer Diagnosis, Biomarker Discovery and Drug Discovery. 15. Targeting Electro-Chemical Signaling Pathways for Cancer Therapy.

Über Autor(innen)

Saurav Mallik is currently working as Research Scientist in the Department of Pharmacology and Toxicology at the University of Arizona, USA. Previously, he worked as Postdoctoral Fellow in Harvard T.H. Chan School of Public Health, Boston, MA, USA, for more than three years (2019–2022); in the Center of Precision Health, Department of School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, Texas, USA, for one and half year (2018–2019); and in the Division of Biostatistics, Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, Florida, USA, for more than one year (2017–2018). He obtained his PhD degree in the Department of Computer Science and Engineering (CSE.) from Jadavpur University, Kolkata, India, in 2017, while his PhD works carried out in the Machine Intelligence Unit, Indian Statistical Institute, Kolkata, India, as Junior Research Fellow and Visiting Scientist. He has obtained the award of Research Associateship from CSIR (Council of Scientific and Industrial Research), MHRD, Government of India in 2017. He has more than 150 research papers in different top high-impact factor peer-reviewed international journals, conferences, and book chapters. He has published several books and patents (cited by >5,000 times, H-index = 39). He is working as an active member of the Institute of Electrical and Electronics Engineers (IEEE), USA; ACM and American Association for Cancer Research (AACR), USA; and Bioclues, India. He has also worked with section editors and reviewers with several well-reputed high-impact journals. His research interests include computational biology, knowledge retrieval and data mining, bioinformatics, biostatistics, and machine learning/deep learning.

Zhongming Zhao holds University Chair for Precision Health. He is the Founding Director of the Center for Precision Health at the University of Texas Health Science Center in Houston (UTHealth). Before he joined UTHealth in 2016, he was the Ingram Endowed Professor of Cancer Research; Professor (tenured) in the Departments of Biomedical Informatics, Psychiatry, and Cancer Biology at Vanderbilt University Medical Center; Chief Bioinformatics Officer of the Vanderbilt-Ingram Cancer Center (VICC); Director of the VICC Bioinformatics Resource Center; and Associate Director of the Vanderbilt Center for Quantitative Sciences. He has broad interests in bioinformatics, genomics, data science/AI, population genetics, and precision medicine, and he has co-authored over 600 total publications in these areas (cited by >33,000 times, H-index = 89). He is the Founding President of The International Association for Intelligent Biology and Medicine (IAIBM, 2018).

Namrata Tomar is currently working as Assistant Clinical Research Associate at Thermo Fisher Scientific Inc., USA. Previously, she worked as an Assistant Clinical Research Associate, Medical College of Wisconsin, Milwaukee, WI, USA. She performs both experimental lab experiments and computational modeling of experimental data. She worked as Postdoctoral Fellow in the Department of Biomedical Engineering, Medical College of Wisconsin, Milwaukee, WI, USA (2016–2021). She also worked as Visiting Scientist at the Laboratory of Systems Tumor and Immune Biology, Department of Dermatology, University Hospital, Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen, Germany (2014–2016). She obtained her PhD degree from the Department of Biophysics, Molecular Biology and Bioinformatics, University of Calcutta, Kolkata, India, in 2015, while her PhD works carried out in the Machine Intelligence Unit, Indian Statistical Institute, Kolkata, India. She has more than 75 research papers in different top high-impact factor peer-reviewed international journals, conferences, and book chapters. She published several books (cited by >900 times, H-index = 14). She has also worked with section editors and reviewers with several well-reputed high-impact journals. Her research interests include computational biology, bioinformatics, biostatistics, mitochondrial biology, and biomedical engineering.

Soumita Seth is currently serving as Assistant Professor in the Department of Computer Science and Engineering at Future Institute of Engineering and Management, Kolkata, India, affiliated with MAKAUT, Kolkata. Besides, she recently submitted her PhD thesis in the Department of Computer Science and Engineering (CSE) from a state-government university, Aliah University (AU), Kolkata, India. Previously, she completed MTech and BTech from the departments of CSE and IT, respectively. She is also collaborating on her PhD research with The University of Texas Health Science Center at Houston (UTHealth), Houston, TX, USA. She has Academic Experience of almost 9 years, Fulltime Research Experience of 2 years, and Industrial Experience of 2 years. She has more than 12 research papers in different top high-impact factor peer-reviewed international journals, conferences, and book chapters. She has published several books (cited by >200 times, H-index = 8). She has also worked with section editors and section reviewers with several well-reputed high-impact journals. Her research interests include computational biology, data mining, bioinformatics, pattern recognition, biological regulatory networks, biostatistics, and machine learning/deep learning.

Saiyed Umer is working as Assistant Professor in the Department of Computer Science and Engineering, Aliah University, Kolkata, India. He obtained his PhD degree in the Department of Computer Science and Engineering (CSE) from Jadavpur University, Kolkata, India, in 2017, while his PhD works carried out at the Indian Statistical Institute, Kolkata, India. He has more than 60 research publications in different top high-impact factor peer-reviewed international journals, conferences, and book chapters. He has published several books and patents (cited by >1800 times, H-index = 23). He has also worked with section editors and reviewers with several well-reputed high-impact journals. His research interests include computer vision, machine learning/deep learning, biometric, affective computing (facial expression recognition), video analysis, and AI in agriculture.

Tapas Bhadra is currently working as Assistant Professor in the Department of Computer Science and Engineering at Aliah University in Kolkata, India. He obtained his PhD degree from the Department of Computer Science and Engineering at Jadavpur University, Kolkata, India, in 2018. Prior to this, he was an INSPIRE Fellow in the Machine Intelligence Unit at the Indian Statistical Institute, Kolkata, from 2011 to 2015. He has co-authored more than 30 research papers and several books (cited by >600 times, H-index = 12). He has also worked with section editors and reviewers from several well-reputed high-impact journals. His research interests include pattern recognition, data mining, computational biology, and bioinformatics.

Ranjeet Kumar Rout is working as Assistant Professor in the Department of Computer Science and Engineering at the National Institute of Technology, Srinagar, India. He obtained his PhD degree in the Department of Computer Science and Engineering (CSE) at the Indian Institute of Engineering Science and Technology (IIEST), Shibpur, Howrah, India, in 2018. He has more than 25 research publications in different top high-impact factor peer-reviewed international journals, conferences, and book chapters. He has published several books and patents. He has also worked with section editors and reviewers from several well-reputed high-impact journals (cited by >1,400 times, H-index = 21). His research interests include computer vision, biometric, information security and privacy, computational biology (biological data analytics), and cyber-physical systems.