
Artificial Intelligence in Bioinformatics and Chemoinformatics
- 260 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Artificial Intelligence in Bioinformatics and Chemoinformatics
About this book
The authors aim to shed light on the practicality of using machine learning in finding complex chemoinformatics and bioinformatics applications as well as identifiying AI in biological and chemical data points. The chapters are designed in such a way that they highlight the important role of AI in chemistry and bioinformatics particularly for the classification of diseases, selection of features and compounds, dimensionality reduction and more. In addition, they assist in the organization and optimal use of data points generated from experiments performed using AI techniques. This volume discusses the development of automated tools and techniques to aid in research plans.
Features
- Covers AI applications in bioinformatics and chemoinformatics
- Demystifies the involvement of AI in generating biological and chemical data
- Provides an Introduction to basic and advanced chemoinformatics computational tools
- Presents a chemical biology based toolset for artificial intelligence usage in drug design
- Discusses computational methods in cancer, genome mapping, and stem cell research
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Information
Table of contents
- Cover
- Half Title
- Title Page
- Copyright Page
- Table of Contents
- Preface
- Editors
- List of Contributors
- 1 Bridging Bioinformatics and Chemoinformatics Approaches in Public Databases
- 2 An Introduction to Basic and Advanced Chemoinformatics Computational Tools
- 3 An Introduction to Basic and Advanced Bioinformatics Computational Tools
- 4 Computational Methods in Cancer, Genome Mapping, and Stem Cell Research
- 5 Using Chemistry to Understand Biology
- 6 Chemical Biology-based Toolset for Artificial Intelligence Usage in Drug Design
- 7 Machine Learning and Data Mining: Uses and Challenges in Bioinformatics
- 8 Application of Deep Learning in Chemistry and Biology
- 9 Text Mining in Chemistry for Organizing Chemistry Data
- 10 CNN Use and Performance in Virtual Screening
- 11 Machine Learning in Improving Force Fields of Molecular Dynamics
- 12 Defining the Role of Chemical and Biological Data and Applying Algorithms
- 13 Optimization and Quantification of Uncertainty in Machine Learning
- Index
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