Bioinformatics: Algorithms, Coding, Data Science and Biostatistics 9781839386886
Introducing the Ultimate Bioinformatics Book Bundle! Dive into the world of bioinformatics with our comprehensive book
133 102
English Pages 271 Year 2024
Table of contents :
Introduction
Chapter 1: Introduction to Bioinformatics
Chapter 2: Fundamentals of Molecular Biology
Chapter 3: Basics of Sequence Analysis
Chapter 4: Understanding Genetic Variation
Chapter 5: Introduction to Bioinformatics Algorithms
Chapter 6: Pairwise Sequence Alignment Techniques
Chapter 7: Multiple Sequence Alignment Methods
Chapter 8: Genome Assembly and Annotation
Chapter 9: Phylogenetic Analysis
Chapter 10: Applications of Bioinformatics in Biomedical Researc
Chapter 1: Introduction to Programming for Bioinformatics
Chapter 2: Essential Tools and Languages for Bioinformatics Coding
Chapter 3: Scripting Basics: Automating Tasks in Bioinformatics
Chapter 4: Data Manipulation and Parsing Techniques
Chapter 5: File Handling and Input/Output Operations
Chapter 6: Intermediate Coding Concepts in Bioinformatics
Chapter 7: Object-Oriented Programming for Bioinformatics
Chapter 8: Advanced Scripting Techniques and Best Practices
Chapter 9: High-Performance Computing and Parallel Processing
Chapter 10: Developing Bioinformatics Applications and Tools
Chapter 1: Introduction to Data Science in Bioinformatics
Chapter 2: Exploratory Data Analysis Techniques
Chapter 3: Data Visualization in Bioinformatics
Chapter 4: Statistical Methods for Data Analysis
Chapter 5: Machine Learning Fundamentals in Bioinformatics
Chapter 6: Predictive Modeling and Classification
Chapter 7: Clustering and Dimensionality Reduction Techniques
Chapter 8: Deep Learning Applications in Bioinformatics
Chapter 9: Network Analysis and Graph Theory in Bioinformatics
Chapter 10: Big Data Management and Tools for Bioinformatics
Chapter 1: Introduction to Biostatistics in Bioinformatics
Chapter 2: Probability and Statistical Distributions
Chapter 3: Hypothesis Testing and Statistical Inference
Chapter 4: Parametric and Nonparametric Tests in Bioinformatics
Chapter 5: Regression Analysis in Bioinformatics
Chapter 6: Survival Analysis and Time-to-Event Data
Chapter 7: Experimental Design and Statistical Power
Chapter 8: Bayesian Methods in Bioinformatics
Chapter 9: Advanced Topics in Biostatistics: Meta-analysis and Multilevel Modeling
Chapter 10: Practical Applications and Case Studies in Bioinformatics Biostatistics
Conclusion
Introduction
Chapter 1: Introduction to Bioinformatics
Chapter 2: Fundamentals of Molecular Biology
Chapter 3: Basics of Sequence Analysis
Chapter 4: Understanding Genetic Variation
Chapter 5: Introduction to Bioinformatics Algorithms
Chapter 6: Pairwise Sequence Alignment Techniques
Chapter 7: Multiple Sequence Alignment Methods
Chapter 8: Genome Assembly and Annotation
Chapter 9: Phylogenetic Analysis
Chapter 10: Applications of Bioinformatics in Biomedical Researc
Chapter 1: Introduction to Programming for Bioinformatics
Chapter 2: Essential Tools and Languages for Bioinformatics Coding
Chapter 3: Scripting Basics: Automating Tasks in Bioinformatics
Chapter 4: Data Manipulation and Parsing Techniques
Chapter 5: File Handling and Input/Output Operations
Chapter 6: Intermediate Coding Concepts in Bioinformatics
Chapter 7: Object-Oriented Programming for Bioinformatics
Chapter 8: Advanced Scripting Techniques and Best Practices
Chapter 9: High-Performance Computing and Parallel Processing
Chapter 10: Developing Bioinformatics Applications and Tools
Chapter 1: Introduction to Data Science in Bioinformatics
Chapter 2: Exploratory Data Analysis Techniques
Chapter 3: Data Visualization in Bioinformatics
Chapter 4: Statistical Methods for Data Analysis
Chapter 5: Machine Learning Fundamentals in Bioinformatics
Chapter 6: Predictive Modeling and Classification
Chapter 7: Clustering and Dimensionality Reduction Techniques
Chapter 8: Deep Learning Applications in Bioinformatics
Chapter 9: Network Analysis and Graph Theory in Bioinformatics
Chapter 10: Big Data Management and Tools for Bioinformatics
Chapter 1: Introduction to Biostatistics in Bioinformatics
Chapter 2: Probability and Statistical Distributions
Chapter 3: Hypothesis Testing and Statistical Inference
Chapter 4: Parametric and Nonparametric Tests in Bioinformatics
Chapter 5: Regression Analysis in Bioinformatics
Chapter 6: Survival Analysis and Time-to-Event Data
Chapter 7: Experimental Design and Statistical Power
Chapter 8: Bayesian Methods in Bioinformatics
Chapter 9: Advanced Topics in Biostatistics: Meta-analysis and Multilevel Modeling
Chapter 10: Practical Applications and Case Studies in Bioinformatics Biostatistics
Conclusion
