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Advances in bioengineering

Vyas, Renu.

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Advances in bioengineering

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Advances in bioengineering/ edited by Renu Vyas.
其他作者:	Vyas, Renu.
出版者:	Singapore :Springer Singapore : : 2020.,
面頁冊數:	xiii, 229 p. :ill., digital ;24 cm.
內容註:	Chapter 1. Modeling of protein complexes involved in signaling pathway for Non-Small Cell Lung Cancer -- Chapter 2. Role of BioJava in the Department of Bioinformatics Tools -- Chapter 3. Overview of machine learning methods in ADHD prediction -- Chapter 4. Simplified Protein Structure Prediction Using Parallel Genetic Algorithms -- Chapter 5. Applications of deep learning in drug discovery -- Chapter 6. Big Data Analytics for Handling NGS Data & its Applications in Identifying Cancer Mutations -- Chapter 7. Medicinal Properties of Fruit waste -- Chapter 8. Epigenetic toxicity of nanoparticles -- Chapter 9. Protein Misfolding and Aggregation in Neurodegenerative diseases -- Chapter 10. Enzyme technology prospectus & their Biomedical Applications -- Chapter 11. Polyunsaturated fatty acids enhance the recovery of bone marrow impairment caused after radiation -- Chapter 12. Nanomaterial Enabled Rapid Electrochemical Biosensors For Bacterial Pathogens -- Chapter 13. Heart Rate Variability Analysis in lung cancer patients to study the effect of treatment -- Chapter 14. Co-Relation of Physiological Signals And Therapy for Diagnostics Purpose of Periodic Limb Movement Disorder (Plmd) -- Chapter 15. Analysis of Forward Head Posture -- Chapter 16. Biopolymeric Smart Nano-Carriers for Drug Delivery Applications.
Contained By:	Springer eBooks
標題:	Bioengineering. -
電子資源:	https://doi.org/10.1007/978-981-15-2063-1
ISBN:	9789811520631

Advances in bioengineering
Advances in bioengineering[electronic resource] /edited by Renu Vyas. - Singapore :Springer Singapore :2020. - xiii, 229 p. :ill., digital ;24 cm.

Chapter 1. Modeling of protein complexes involved in signaling pathway for Non-Small Cell Lung Cancer -- Chapter 2. Role of BioJava in the Department of Bioinformatics Tools -- Chapter 3. Overview of machine learning methods in ADHD prediction -- Chapter 4. Simplified Protein Structure Prediction Using Parallel Genetic Algorithms -- Chapter 5. Applications of deep learning in drug discovery -- Chapter 6. Big Data Analytics for Handling NGS Data & its Applications in Identifying Cancer Mutations -- Chapter 7. Medicinal Properties of Fruit waste -- Chapter 8. Epigenetic toxicity of nanoparticles -- Chapter 9. Protein Misfolding and Aggregation in Neurodegenerative diseases -- Chapter 10. Enzyme technology prospectus & their Biomedical Applications -- Chapter 11. Polyunsaturated fatty acids enhance the recovery of bone marrow impairment caused after radiation -- Chapter 12. Nanomaterial Enabled Rapid Electrochemical Biosensors For Bacterial Pathogens -- Chapter 13. Heart Rate Variability Analysis in lung cancer patients to study the effect of treatment -- Chapter 14. Co-Relation of Physiological Signals And Therapy for Diagnostics Purpose of Periodic Limb Movement Disorder (Plmd) -- Chapter 15. Analysis of Forward Head Posture -- Chapter 16. Biopolymeric Smart Nano-Carriers for Drug Delivery Applications.

This book provides a single source of information on three major bioengineering areas: engineering at the cellular and molecular level; biomedical devices / instrument engineering; and data engineering. It explores the latest strategies that are essential to advancing our understanding of the mechanisms of human diseases, the development of new enzyme-based technologies, diagnostics, prosthetics, high-performance computing platforms for managing huge amounts of biological data, and the use of deep learning methods to create predictive models. The book also highlights the growing importance of integrating chemistry into life sciences research, most notably concerning the development and evaluation of nanomaterials and nanoparticles and their interactions with biological material. The underlying interdisciplinary theme of bioengineering is addressed in a range of multifaceted applications and worked out examples provided in each chapter.

ISBN: 9789811520631

Standard No.: 10.1007/978-981-15-2063-1doiSubjects--Topical Terms:

657580
Bioengineering.

LC Class. No.: TA164 / .A383 2020

Dewey Class. No.: 660.6

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505 0 $a Chapter 1. Modeling of protein complexes involved in signaling pathway for Non-Small Cell Lung Cancer -- Chapter 2. Role of BioJava in the Department of Bioinformatics Tools -- Chapter 3. Overview of machine learning methods in ADHD prediction -- Chapter 4. Simplified Protein Structure Prediction Using Parallel Genetic Algorithms -- Chapter 5. Applications of deep learning in drug discovery -- Chapter 6. Big Data Analytics for Handling NGS Data & its Applications in Identifying Cancer Mutations -- Chapter 7. Medicinal Properties of Fruit waste -- Chapter 8. Epigenetic toxicity of nanoparticles -- Chapter 9. Protein Misfolding and Aggregation in Neurodegenerative diseases -- Chapter 10. Enzyme technology prospectus & their Biomedical Applications -- Chapter 11. Polyunsaturated fatty acids enhance the recovery of bone marrow impairment caused after radiation -- Chapter 12. Nanomaterial Enabled Rapid Electrochemical Biosensors For Bacterial Pathogens -- Chapter 13. Heart Rate Variability Analysis in lung cancer patients to study the effect of treatment -- Chapter 14. Co-Relation of Physiological Signals And Therapy for Diagnostics Purpose of Periodic Limb Movement Disorder (Plmd) -- Chapter 15. Analysis of Forward Head Posture -- Chapter 16. Biopolymeric Smart Nano-Carriers for Drug Delivery Applications.
520 $a This book provides a single source of information on three major bioengineering areas: engineering at the cellular and molecular level; biomedical devices / instrument engineering; and data engineering. It explores the latest strategies that are essential to advancing our understanding of the mechanisms of human diseases, the development of new enzyme-based technologies, diagnostics, prosthetics, high-performance computing platforms for managing huge amounts of biological data, and the use of deep learning methods to create predictive models. The book also highlights the growing importance of integrating chemistry into life sciences research, most notably concerning the development and evaluation of nanomaterials and nanoparticles and their interactions with biological material. The underlying interdisciplinary theme of bioengineering is addressed in a range of multifaceted applications and worked out examples provided in each chapter.
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