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Quick Guideline for Computational Drug Design
Bioinformatics allows researchers to answer biological questions with advanced computational methods which involves the application of statistics and mathematical modeling. Structural bioinformatics enables the prediction and analysis of 3D structures of macromolecules while Computer Aided Drug Designing (CADD) assists scientists to design effective active molecules against diseases. However, the concepts in structural bioinformatics and CADD can be complex to understand for students and educated laymen. This quick guideline is intended as a basic manual for beginner students and instructors involved in bioinformatics and computational chemistry courses. Readers will learn the basics of structural bioinformatics, primary and secondary analysis and prediction, structural visualization, structural analysis and molecular docking. Therefore, the book is a useful handbook for aspiring scholars who wish to learn the basic concepts in computational analysis of biomolecules.
Design and development of new therapeutics against infectious diseases using computational and experimental approaches
Infectious diseases are caused by bacteria, fungus, viruses, and other microorganisms. Biomolecules such as proteins, DNA, and/or RNA play a crucial role in the infections of these disorders. These infectious illnesses are often transmissible, meaning they may be passed from one person to another by a variety of means. Even though medical technology has progressed, some illnesses continue to cause anxiety among individuals worldwide. If we examine the situation of COVID-19, the entire world is terrified of the pandemic. Similarly, In the last decades, other infections including Dengue, Chikungunya, Zika, Ebola, Japanese Encephalitis Virus (JEV), influenza, the common cold, tuberculosis (TB), Hepatitis A and B and human immunodeficiency syndrome (HIV) have also challenged the human population.
Deep Learning in Personalized Healthcare and Decision Support
Deep Learning in Personalized Healthcare and Decision Support discusses the potential of deep learning technologies in the healthcare sector. The book covers the application of deep learning tools and techniques in diverse areas of healthcare, such as medical image classification, telemedicine, clinical decision support system, clinical trials, electronic health records, precision medication, Parkinson disease detection, genomics, and drug discovery. In addition, it discusses the use of DL for fraud detection and internet of things. This is a valuable resource for researchers, graduate students and healthcare professionals who are interested in learning more about deep learning applied to th...
Bioinformatics Research and Applications
This book constitutes the proceedings of the 13th International Symposium on Bioinformatics Research and Applications, ISBRA 2017, held in Honolulu, HI, USA, in May/June 2017. The 27 full papers presented together with 18 short papers and 24 invited abstracts were carefully reviewed and selected from 131 submissions. They cover topics such as: biomarker discovery; biomedical databases and data integration; biomedical text mining and ortologies; biomolecular imaging; comparative genomics; computational genetic epidemiology; computational proteomics; data mining and visualization; gene expression analysis; genome analysis; high-performance bio-computing; metagenomics; molecular evolution; molecular modelling and simulation; next-generation sequencing data analysis; pattern discovery and classification; population genetics; software tools and applications; structural biology; and systems biology.
Quick Guideline for Computational Drug Design (Revised Edition)
Computational Drug Designing Structural Bioinformatics Homology Modeling Molecular Docking Primary Sequence Analyses Protparam Secondary Structural Analyses Profunc Ab initio modeling I-Tasser Structural Evaluation ERRAT Rampage Structure Visualization Chimera AutoDock Tools AutoDock Vina GOLD proteomics Computational Chemistry
