The Resource Big data analytics in genomics, Ka-Chun Wong, editor

Big data analytics in genomics, Ka-Chun Wong, editor

Label
Big data analytics in genomics
Title
Big data analytics in genomics
Statement of responsibility
Ka-Chun Wong, editor
Contributor
Editor
Subject
Genre
Language
eng
Summary
This contributed volume explores the emerging intersection between big data analytics and genomics. Recent sequencing technologies have enabled high-throughput sequencing data generation for genomics resulting in several international projects which have led to massive genomic data accumulation at an unprecedented pace. To reveal novel genomic insights from this data within a reasonable time frame, traditional data analysis methods may not be sufficient or scalable, forcing the need for big data analytics to be developed for genomics. The computational methods addressed in the book are intended to tackle crucial biological questions using big data, and are appropriate for either newcomers or veterans in the field. This volume offers thirteen peer-reviewed contributions, written by international leading experts from different regions, representing Argentina, Brazil, China, France, Germany, Hong Kong, India, Japan, Spain, and the USA. In particular, the book surveys three main areas: statistical analytics, computational analytics, and cancer genome analytics. Sample topics covered include: statistical methods for integrative analysis of genomic data, computation methods for protein function prediction, and perspectives on machine learning techniques in big data mining of cancer. Self-contained and suitable for graduate students, this book is also designed for bioinformaticians, computational biologists, and researchers in communities ranging from genomics, big data, molecular genetics, data mining, biostatistics, biomedical science, cancer research, medical research, and biology to machine learning and computer science. Readers will find this volume to be an essential read for appreciating the role of big data in genomics, making this an invaluable resource for stimulating further research on the topic
Cataloging source
N$T
Dewey number
005.7
Index
no index present
LC call number
QA76.9.B45
Literary form
non fiction
Nature of contents
dictionaries
http://library.link/vocab/relatedWorkOrContributorName
Wong, Ka-Chun
http://library.link/vocab/subjectName
  • COMPUTERS
  • Big data
  • Genomics
  • Data mining
  • Quantitative research
  • Big data
  • Data mining
  • Genomics
  • Data mining
  • Probability & statistics
  • Applied mathematics
  • Life sciences: general issues
Label
Big data analytics in genomics, Ka-Chun Wong, editor
Link
https://ezproxy.lib.ou.edu/login?url=http://link.springer.com/10.1007/978-3-319-41279-5
Instantiates
Publication
Antecedent source
unknown
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
Introduction to Statistical Methods for Integrative Analysis of Genomic Data -- Robust Methods for Expression Quantitative Trait Loci Mapping -- Causal Inference and Structure Learning of Genotype-Phenotype Networks using Genetic Variation -- Genomic Applications of the Neyman-Pearson Classification Paradigm -- Improving Re-annotation of Annotated Eukaryotic Genomes -- State-of-the-art in Smith-Waterman Protein Database Search -- A Survey of Computational Methods for Protein Function Prediction -- Genome Wide Mapping of Nucleosome Position and Histone Code Polymorphisms in Yeast -- Perspectives of Machine Learning Techniques in Big Data Mining of Cancer -- Mining Massive Genomic Data for Therapeutic Biomarker Discovery in Cancer: Resources, Tools, and Algorithms -- NGC Analysis of Somatic Mutations in Cancer Genomes -- OncoMiner: A Pipeline for Bioinformatics Analysis of Exonic Sequence Variants in Cancer -- A Bioinformatics Approach for Understanding Genotype-Phenotype Correlation in Breast Cancer
Dimensions
unknown
Extent
1 online resource
File format
unknown
Form of item
online
Isbn
9783319412795
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
c
Note
SpringerLink
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
  • (OCoLC)961271949
  • (OCoLC)ocn961271949
Label
Big data analytics in genomics, Ka-Chun Wong, editor
Link
https://ezproxy.lib.ou.edu/login?url=http://link.springer.com/10.1007/978-3-319-41279-5
Publication
Antecedent source
unknown
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
Introduction to Statistical Methods for Integrative Analysis of Genomic Data -- Robust Methods for Expression Quantitative Trait Loci Mapping -- Causal Inference and Structure Learning of Genotype-Phenotype Networks using Genetic Variation -- Genomic Applications of the Neyman-Pearson Classification Paradigm -- Improving Re-annotation of Annotated Eukaryotic Genomes -- State-of-the-art in Smith-Waterman Protein Database Search -- A Survey of Computational Methods for Protein Function Prediction -- Genome Wide Mapping of Nucleosome Position and Histone Code Polymorphisms in Yeast -- Perspectives of Machine Learning Techniques in Big Data Mining of Cancer -- Mining Massive Genomic Data for Therapeutic Biomarker Discovery in Cancer: Resources, Tools, and Algorithms -- NGC Analysis of Somatic Mutations in Cancer Genomes -- OncoMiner: A Pipeline for Bioinformatics Analysis of Exonic Sequence Variants in Cancer -- A Bioinformatics Approach for Understanding Genotype-Phenotype Correlation in Breast Cancer
Dimensions
unknown
Extent
1 online resource
File format
unknown
Form of item
online
Isbn
9783319412795
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
c
Note
SpringerLink
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
  • (OCoLC)961271949
  • (OCoLC)ocn961271949

Library Locations

  • Architecture LibraryBorrow it
    Gould Hall 830 Van Vleet Oval Rm. 105, Norman, OK, 73019, US
    35.205706 -97.445050
  • Bizzell Memorial LibraryBorrow it
    401 W. Brooks St., Norman, OK, 73019, US
    35.207487 -97.447906
  • Boorstin CollectionBorrow it
    401 W. Brooks St., Norman, OK, 73019, US
    35.207487 -97.447906
  • Chinese Literature Translation ArchiveBorrow it
    401 W. Brooks St., RM 414, Norman, OK, 73019, US
    35.207487 -97.447906
  • Engineering LibraryBorrow it
    Felgar Hall 865 Asp Avenue, Rm. 222, Norman, OK, 73019, US
    35.205706 -97.445050
  • Fine Arts LibraryBorrow it
    Catlett Music Center 500 West Boyd Street, Rm. 20, Norman, OK, 73019, US
    35.210371 -97.448244
  • Harry W. Bass Business History CollectionBorrow it
    401 W. Brooks St., Rm. 521NW, Norman, OK, 73019, US
    35.207487 -97.447906
  • History of Science CollectionsBorrow it
    401 W. Brooks St., Rm. 521NW, Norman, OK, 73019, US
    35.207487 -97.447906
  • John and Mary Nichols Rare Books and Special CollectionsBorrow it
    401 W. Brooks St., Rm. 509NW, Norman, OK, 73019, US
    35.207487 -97.447906
  • Library Service CenterBorrow it
    2601 Technology Place, Norman, OK, 73019, US
    35.185561 -97.398361
  • Price College Digital LibraryBorrow it
    Adams Hall 102 307 West Brooks St., Norman, OK, 73019, US
    35.210371 -97.448244
  • Western History CollectionsBorrow it
    Monnet Hall 630 Parrington Oval, Rm. 300, Norman, OK, 73019, US
    35.209584 -97.445414
Processing Feedback ...