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Big Data Analytics in Bioinformatics and Healthcare

Book Description

As technology evolves and electronic data becomes more complex, digital medical record management and analysis becomes a challenge. In order to discover patterns and make relevant predictions based on large data sets, researchers and medical professionals must find new methods to analyze and extract relevant health information. Big Data Analytics in Bioinformatics and Healthcare merges the fields of biology, technology, and medicine in order to present a comprehensive study on the emerging information processing applications necessary in the field of electronic medical record management. Complete with interdisciplinary research resources, this publication is an essential reference source for researchers, practitioners, and students interested in the fields of biological computation, database management, and health information technology, with a special focus on the methodologies and tools to manage massive and complex electronic information.

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright Page
  4. Book Series
    1. Mission
    2. Coverage
  5. Editorial Advisory Board and List of Reviewers
    1. Editorial Advisory Board
    2. List of Reviewers
  6. Preface
    1. REFERENCE
  7. Section 1: Big Data Analysis Methods and Applications
    1. Chapter 1: Advanced Datamining Using RNAseq Data
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. ADDITIONAL DATAMINING IN RNASEQ DATA
      5. FUTURE RESEARCH DIRECTIONS
      6. CONCLUSION
      7. REFERENCES
      8. ADDITIONAL READING
      9. KEY TERMS AND DEFINITIONS
    2. Chapter 2: Text Mining on Big and Complex Biomedical Literature
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. MIRNA-CANCER RELATIONSHIP TEXT MINING
      5. FUTURE DIRECTIONS
      6. CONCLUSION
      7. REFERENCES
      8. ADDITIONAL READING
      9. KEY TERMS AND DEFINITIONS
    3. Chapter 3: Interactive Data Visualization Techniques Applied to Healthcare Decision Making
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. LITERATURE REVIEW
      4. 3. CASE STUDIES
      5. 4. CONCLUSION AND FUTURE RESEARCH DIRECTIONS
      6. REFERENCES
      7. ADDITIONAL READING
      8. KEY TERMS AND DEFINITIONS
    4. Chapter 4: Large-Scale Regulatory Network Analysis from Microarray Data
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. METHODS
      5. RESULTS
      6. DISCUSSION
      7. FUTURE RESEARCH DIRECTIONS
      8. CONCLUSION
      9. REFERENCES
      10. ADDITIONAL READING
      11. KEY TERMS AND DEFINITIONS
    5. Chapter 5: Detection and Employment of Biological Sequence Motifs
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. MOTIF PREDICTION ALGORITHMS
      5. FUTURE RESEARCH DIRECTIONS
      6. CONCLUSION
      7. REFERENCES
      8. ADDITIONAL READING
      9. KEY TERMS AND DEFINITIONS
    6. Chapter 6: Observer-Biased Analysis of Gene Expression Profiles
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. FUZZY CLUSTERING WITH A FOCAL POINT
      5. ILLUSTRATIVE RESULTS
      6. FUTURE RESEARCH DIRECTIONS
      7. CONCLUSION
      8. ACKNOWLEDGMENT
      9. REFERENCES
      10. ADDITIONAL READING
      11. KEY TERMS AND DEFINITIONS
    7. Chapter 7: Heuristic Principal Component Analysis-Based Unsupervised Feature Extraction and Its Application to Bioinformatics
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. INTRODUCTION OF PCA BASED UNSUPERVISED FE AND ITS APPLICATIONS
      5. FUTURE RESEARCH DIRECTIONS
      6. CONCLUSION
      7. REFERENCES
      8. ADDITIONAL READING
      9. KEY TERMS AND DEFINITIONS
  8. Section 2: Reviews and Perspectives on Big Data Analysis
    1. Chapter 8: The Role of Big Data in Radiation Oncology
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. BIG DATA IN RADIOTHERAPY
      5. ISSUES AND RECOMMENDATIONS
      6. FUTURE RESEARCH DIRECTIONS
      7. CONCLUSION
      8. REFERENCES
      9. ADDITIONAL READING
      10. KEY TERMS AND DEFINITIONS
    2. Chapter 9: Analysis of Genomic Data in a Cloud Computing Environment
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. MAIN FOCUS OF THE CHAPTER
      5. FUTURE RESEARCH DIRECTION: UTILIZING CLOUD COMPUTING TO ANALYZE SNP6 ARRAYS
      6. CONCLUSION
      7. ACKNOWLEDGMENT
      8. REFERENCES
      9. ADDITIONAL READING
      10. KEY TERMS AND DEFINITIONS
      11. APPENDIX
    3. Chapter 10: Pathway Analysis and Its Applications
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. DATA GENERATION TECHNOLOGIES
      5. DATABASES
      6. PATHWAY AND NETWORK ANALYSIS METHODOLOGIES
      7. SOLUTIONS AND RECOMMENDATIONS
      8. FUTURE RESEARCH DIRECTIONS
      9. CONCLUSION
      10. REFERENCES
      11. ADDITIONAL READING
      12. KEY TERMS AND DEFINITIONS
    4. Chapter 11: Computational Systems Biology Perspective on Tuberculosis in Big Data Era
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. PREDICTIVE COMPUTATIONAL MODELS ON TUBERCULOSIS
      5. INTEGRATION OF SYSTEM BIOLOGY APPROACHES IN TB PREDICTION MODELS AND THEIR APPLICATIONS
      6. MAJOR COMPONENTS AND RESOURCES IN SYSTEM BIOLOGY
      7. SPECIFIC AREAS OF BIG DATA AND THEIR COMPUTATIONAL RESOURCES
      8. EMERGING CHALLENGES FOR SYSTEM BIOLOGY IN BIG DATA ERA
      9. CHALLENGES AND SOLUTIONS IN COMBINING BIG DATA AND SYSTEMS BIOLOGY
      10. FUTURE RESEARCH DIRECTIONS
      11. CONCLUSION
      12. REFERENCES
      13. ADDITIONAL READING
      14. KEY TERMS AND DEFINITIONS
    5. Chapter 12: Bioinformatics-Driven Big Data Analytics in Microbial Research
      1. ABSTRACT
      2. INTRODUCTION
      3. DEVELOPMENTS IN MICROBIAL RESEARCH FOR BIG DATA
      4. BIG DATA SOURCES IN MICROBIAL RESEARCH
      5. MICROBIAL BIG DATA ANALYTICS: BIOINFORMATICS PERSPECTIVE
      6. FUTURE RESEARCH DIRECTIONS
      7. CONCLUSION
      8. ACKNOWLEDGMENT
      9. REFERENCES
      10. ADDITIONAL READING
      11. KEY TERMS AND DEFINITIONS
    6. Chapter 13: Perspectives on Data Integration in Human Complex Disease Analysis
      1. ABSTRACT
      2. INTRODUCTION
      3. TAXONOMY
      4. FROM COMPONENTWISE TO GLOBAL STRATEGIES
      5. FUTURE RESEARCH DIRECTIONS
      6. CONCLUSION
      7. ACKNOWLEDGMENT
      8. REFERENCES
      9. ADDITIONAL READING
      10. KEY TERMS AND DEFINITIONS
    7. Chapter 14: Current Study Designs, Methods, and Future Directions of Genetic Association Mapping
      1. ABSTRACT
      2. INTRODUCTION
      3. STUDY DESIGNS IN ASSOCIATION MAPPING
      4. CHOICES AND TRENDS IN GENOTYPING
      5. QUALITY CONTROL
      6. SINGLE-SNP ANALYSIS
      7. MULTIPLE-SNP ANALYSIS
      8. GWAS META-ANALYSIS
      9. UNCOMMON AND RARE VARIANT ANALYSIS
      10. FUTURE DIRECTIONS
      11. CONCLUSION
      12. REFERENCES
      13. ADDITIONAL READING
      14. KEY TERMS AND DEFINITIONS
    8. Chapter 15: Personalized Disease Phenotypes from Massive OMICs Data
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. ANALYZING AND VISUALIZING BIG OMICS DATA USING SELF ORGANIZING MAPS
      5. CASE STUDY: GENE EXPRESSION AND -METHYLATION PHENOTYPES OF THE HEALTHY AND DISEASED HUMAN COLON
      6. FUTURE RESEARCH DIRECTIONS
      7. CONCLUSION
      8. ACKNOWLEDGMENT
      9. REFERENCES
      10. ADDITIONAL READING
      11. KEY TERMS AND DEFINITIONS
  9. Section 3: Issues and Concerns in the Big Data Era
    1. Chapter 16: Intellectual Property Protection for Synthetic Biology, Including Bioinformatics and Computational Intelligence
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. ISSUES, CONTROVERSIES, AND PROBLEMS OF IP PROTECTION OF SYNTHETIC BIOLOGY
      5. ADDRESSING THE ISSUES: SOLUTIONS AND RECOMMENDATIONS OF IP PROTECTION OF SYNTHETIC BIOLOGY
      6. FUTURE DIRECTIONS
      7. CONCLUSION
      8. REFERENCES
      9. ADDITIONAL READING
      10. KEY TERMS AND DEFINITIONS
    2. Chapter 17: Clinical Data Linkages in Spinal Cord Injuries (SCI) in Australia
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. CHALLENGES WITH LINKING SCI DATA AND RECOMMENDATIONS
      5. FUTURE RESEARCH DIRECTIONS
      6. CONCLUSION
      7. REFERENCES
      8. ADDITIONAL READING
      9. KEY TERMS AND DEFINITIONS
    3. Chapter 18: The Benefits of Big Data Analytics in the Healthcare Sector
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. MAIN FOCUS OF THE CHAPTER
      5. CLINICAL OPERATIONS
      6. FUTURE RESEARCH DIRECTIONS
      7. CONCLUSION
      8. REFERENCES
      9. KEY TERMS AND DEFINITIONS
  10. Compilation of References
  11. About the Contributors