Computational Approaches in Biotechnology and Bioinformatics (Emerging Trends in Biomedical Technologies and Health informatics)

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Computational Approaches in Biotechnology and Bioinformatics (Emerging Trends in Biomedical Technologies and Health informatics)

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  • 製本 Hardcover:ハードカバー版/ページ数 378 p.
  • 言語 ENG
  • 商品コード 9781032406107
  • DDC分類 610.284

Full Description

Volume 1 of Computational Approaches in Bioengineering—Computational Approaches in Biotechnology and Bioinformatics—explores many significant topics of biomedical engineering and bioinformatics in an easily understandable format. It explores recent developments and applications in bioinformatics, biomechanics, artificial intelligence (AI), signal processing, wearable sensors, biomaterials, cell biology, synthetic biology, biostatistics, prosthetics, big data, and algorithms. From applications of biomaterials in advanced drug delivery systems to the role of big data, AI, and machine learning in disease diagnosis and treatment, the book will help readers understand how these technologies are being applied across the areas of biomedical engineering, bioinformatics, and healthcare. The chapters also include case studies on the role of medical robots in surgery and the determination of protein structure using genetic algorithms. The contributors are all leading experts across multiple disciplines and provide chapters that truly represent a complete view of these state-of-the-art technologies.

FEATURES

Covers a wide range of subjects from biomedical engineering like wearable devices, biomaterials, synthetic biology, phytochemical extraction, and prosthetics
Explores AI, machine learning, big data analysis, and algorithms in biomedical engineering and bioinformatics in an easily understandable format
Includes case studies on the role of medical robots in surgery and the determination of protein structure using genetic algorithms
Discusses genetic diagnosis, classification, and risk prediction in cancer using next-generation sequencing in oncology

This book is ideally designed for biomedical professionals, biomedical engineers, healthcare professionals, data engineers, clinicians, physicians, medical students, hospital directors, clinical researchers, and others who work in the field of artificial intelligence, bioinformatics, and computational biology.

Contents

1. Computational Approaches for Discovery of New Drugs for Inflammatory and Infectious Diseases 2. A Bioinformatics Approach Towards Plant-Based Anticancer Drug Discovery 3. Recent Advances in Anticancer Activity and Bioinformatics Approach from Potential Plants 4. Extraction of Phenolic Compounds from some Ayurvedic Botanicals (Nigella sativa, Andrographis paniculata and Phyllanthus amarus) and Evaluation of their Antibacterial and Antiviral Properties using Bioinformatics Approaches 5. Phenolic Compounds: A Systematic Review of Extraction Methods and A Bioinformatics Approach for their Antibacterial and Antiviral Properties 6. Role of Tissue Engineering in The Treatment of Degenerative Diseases 7. An Algorithmic Soft Computing Technique for Identifying Lipase-producing Yeast Using its Gene Expression Data 8. Plant Phenolic Compound Isolation and its Bioinformatics Approaches of Molecular Mechanisms in Antimicrobial Activities and Resistance 9. Computational Evaluation of Peanut Skin Bioactive Compounds for Cancer Treatment 10. Bioinformatics Tools for the Discovery of Potential Anti Diabetic Drugs from Lichens 11. In silico Analysis of Lapachol and Nickel Lapachol Against Tumor Proteins - Insights into the Molecular Interactions and Drug Likeliness 12. Transcriptome Analysis Identifies Genes Involved in Vitamin B Biosynthesis in Solanum virginianum Whole Fruit 13. Identification of Compounds Present in the Eethanolic Extract of Cecropia pachyatachya Trécul Leaves by CG-MS and in silico Studies with the Enzymes 5-LOX and α-1-antitrypsin 14. Computational Biology Approach in Viticultu 15. Screenings of Inhibitory Ability of Vietnamese Medicinal Plants-based Substances and Protein Related Structures: Computation-Pharmacological Experiment Correlation

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