Statistical Bioinformatics
eBook - ePub

Statistical Bioinformatics

For Biomedical and Life Science Researchers

  1. English
  2. ePUB (mobile friendly)
  3. Available on iOS & Android
eBook - ePub

Statistical Bioinformatics

For Biomedical and Life Science Researchers

Book details
Table of contents
Citations

About This Book

This book provides an essential understanding of statistical concepts necessary for the analysis of genomic and proteomic data using computational techniques. The author presents both basic and advanced topics, focusing on those that are relevant to the computational analysis of large data sets in biology. Chapters begin with a description of a statistical concept and a current example from biomedical research, followed by more detailed presentation, discussion of limitations, and problems. The book starts with an introduction to probability and statistics for genome-wide data, and moves into topics such as clustering, classification, multi-dimensional visualization, experimental design, statistical resampling, and statistical network analysis.

  • Clearly explains the use of bioinformatics tools in life sciences research without requiring an advanced background in math/statistics
  • Enables biomedical and life sciences researchers to successfully evaluate the validity of their results and make inferences
  • Enables statistical and quantitative researchers to rapidly learn novel statistical concepts and techniques appropriate for large biological data analysis
  • Carefully revisits frequently used statistical approaches and highlights their limitations in large biological data analysis
  • Offers programming examples and datasets
  • Includes chapter problem sets, a glossary, a list of statistical notations, and appendices with references to background mathematical and technical material
  • Features supplementary materials, including datasets, links, and a statistical package available online

Statistical Bioinformatics is an ideal textbook for students in medicine, life sciences, and bioengineering, aimed at researchers who utilize computational tools for the analysis of genomic, proteomic, and many other emerging high-throughput molecular data. It may also serve as a rapid introduction to the bioinformatics science for statistical and computational students and audiences who have not experienced such analysis tasks before.

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Yes, you can access Statistical Bioinformatics by Jae K. Lee in PDF and/or ePUB format, as well as other popular books in Medicine & Immunology. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Wiley-Blackwell
Year
2011
ISBN
9781118211526
Edition
1
Topic
Medicine
Subtopic
Immunology

Table of contents

  1. COVER
  2. TITLE PAGE
  3. COPYRIGHT
  4. DEDICATION
  5. PREFACE
  6. CONTRIBUTORS
  7. CHAPTER 1: ROAD TO STATISTICAL BIOINFORMATICS
  8. CHAPTER 2: PROBABILITY CONCEPTS AND DISTRIBUTIONS FOR ANALYZING LARGE BIOLOGICAL DATA
  9. CHAPTER 3: QUALITY CONTROL OF HIGH-THROUGHPUT BIOLOGICAL DATA
  10. CHAPTER 4: STATISTICAL TESTING AND SIGNIFICANCE FOR LARGE BIOLOGICAL DATA ANALYSIS
  11. CHAPTER 5: CLUSTERING: UNSUPERVISED LEARNING IN LARGE BIOLOGICAL DATA
  12. CHAPTER 6: CLASSIFICATION: SUPERVISED LEARNING WITH HIGH-DIMENSIONAL BIOLOGICAL DATA
  13. CHAPTER 7: MULTIDIMENSIONAL ANALYSIS AND VISUALIZATION ON LARGE BIOMEDICAL DATA*
  14. CHAPTER 8: STATISTICAL MODELS, INFERENCE, AND ALGORITHMS FOR LARGE BIOLOGICAL DATA ANALYSIS
  15. CHAPTER 9: EXPERIMENTAL DESIGNS ON HIGH-THROUGHPUT BIOLOGICAL EXPERIMENTS
  16. CHAPTER 10: STATISTICAL RESAMPLING TECHNIQUES FOR LARGE BIOLOGICAL DATA ANALYSIS
  17. CHAPTER 11: STATISTICAL NETWORK ANALYSIS FOR BIOLOGICAL SYSTEMS AND PATHWAYS
  18. CHAPTER 12: TRENDS AND STATISTICAL
  19. CHAPTER 13: R AND BIOCONDUCTOR PACKAGES IN BIOINFORMATICS: TOWARD SYSTEMS BIOLOGY
  20. COLOR PLATE
  21. INDEX