Introduction to Bioinformatics and Machine Learning

Erscheinungsjahr 2027
ISBN: 978-0-443-44675-7
Verlag: Elsevier Science & Technology

Buch, Englisch, Format (B × H): 216 mm x 276 mm, Gewicht: 450 g

Introduction to Bioinformatics and Machine Learning provides comprehensive instruction in modern computational biology by integrating bioinformatics, genomics, artificial intelligence, and machine learning into a unified learning framework. The book bridges the gap between biological data analysis and computational methods, covering fundamental concepts in molecular biology and bioinformatics together with practical applications of machine learning to genomics, transcriptomics, proteomics, microbiome research, structural biology, NGS technologies, liquid biopsy, cancer genomics, and precision medicine. Readers are introduced to DNA and RNA sequencing technologies, genome assembly, sequence alignment, variant discovery, gene expression analysis, fusion gene detection, protein structure prediction, biological databases, statistical analysis, explainable artificial intelligence, and predictive modeling. Throughout the book, real-world biomedical case studies demonstrate how computational methods are transforming modern biological and clinical research; and both bioinformatics and machine learning are addressed in a coherent and accessible manner, emphasizing practical problem-solving, reproducible computational workflows, and biological interpretation of results.

Designed for upper-level undergraduate students, graduate students, and researchers, this book serves as both a classroom textbook and practical assignments for those working at the interface of biology, computer science, medicine, and data science.

Autoren/Hrsg.

Frenkel-Morgenstern, Milana

Fachgebiete

• Technische Wissenschaften Sonstige Technologien | Angewandte Technik Medizintechnik, Biomedizintechnik
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizintechnik, Biomedizintechnik, Medizinische Werkstoffe
• Technische Wissenschaften Verfahrenstechnik | Chemieingenieurwesen | Biotechnologie Biotechnologie

Inhaltsverzeichnis

1. Introduction to Bioinformatics and Machine Learning
2. Biological Data and Preprocessing
3. Sequence Analysis
4. Next-Generation Sequencing (NGS) Data Analysis
5. Structure Prediction and Modelling
6. Introduction to Machine Learning for Biological Applications
7. Advanced Machine Learning Techniques
8. Multi-Omics Data Integration
9. Algorithms in Bioinformatics and Machine Learning
10. Applications and Emerging Trends

Über Autor(innen)

Frenkel-Morgenstern, Milana
Prof. Milana Frenkel-Morgenstern is an Associate Professor and Head of the Genomics and Computational Biology Laboratory at the Scojen Institute for Synthetic Biology, Dina Recanati School of Medicine, Reichman University, Israel. She received her PhD from the Weizmann Institute of Science in 2006, followed by postdoctoral research in systems biology with Prof. Uri Alon at the Weizmann Institute and in cancer, genomics and computational biology with Prof. Alfonso Valencia at the Spanish National Cancer Research Centre (CNIO). Previously, she headed to the Cancer Genomics and BioComputing of Complex Diseases Laboratory at the Azrieli Faculty of Medicine, Bar-Ilan University. She has authored more than 100 scientific publications and serves on editorial boards of international scientific journals. She founded the Art in Science competition at international bioinformatics conferences in 2008 and has contributed to the leadership of the Israeli computational biology community.