Advances in Bioengineering

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.

Dr. Renu Vyas is Head of the MIT School of Bioengineering Sciences & Research, a constituent unit of MIT-ADT University Pune. She received her Ph.D. from the CSIR-NCL, Pune, India and subsequently carried out post-doctoral research at the University of Tennessee, Knoxville, USA. She has a multidisciplinary background and has held advanced positions in academia, research, and industry. She has published more than 30 international research papers, holds 15 patents, and co-authored a book on practical chemoinformatics with Springer. She is an associate editor for the journal Novel Approaches in Drug Designing and Development (NAPDD) and serves on the editorial board of the Journal of Integrated Technologies. Her research interests include drug design, machine learning, NGS, biosensors and big data analytics. She is the recipient of numerous national and international fellowships, projects and travel grants. Throughout her teaching career, she has taught various interdisciplinary subjects such as advanced chemoinformatics, systems biology, algorithms in bioinformatics, molecular modeling and drug design, proteomics , machine learning and artificial intelligence.