rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Scalable Big Data Analytics for Protein Bioinformatics
    sub title: Efficient Computational Solutions for Protein Structures
  name:
    name part: Mrozek, Dariusz
    role:
      role term: creator
    role:
      role term: author.
    role:
      role term: http://id.loc.gov/vocabulary/relators/aut
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  genre: Electronic books.
  origin info:
    place:
      place term: gw
    date issued: 2018
    issuance: monographic
  language:
    language term: eng
  physical description:
    reformatting quality: access
    form: remote
    extent: 1 online resource (XXVI, 315 pages 151 illustrations, 110 illustrations in color) : online resource.
  abstract: This book presents a focus on proteins and their structures. The text describes various scalable solutions for protein structure similarity searching, carried out at main representation levels and for prediction of 3D structures of proteins. Emphasis is placed on techniques that can be used to accelerate similarity searches and protein structure modeling processes. The content of the book is divided into four parts. The first part provides background information on proteins and their representation levels, including a formal model of a 3D protein structure used in computational processes, and a brief overview of the technologies used in the solutions presented in the book. The second part of the book discusses Cloud services that are utilized in the development of scalable and reliable cloud applications for 3D protein structure similarity searching and protein structure prediction. The third part of the book shows the utilization of scalable Big Data computational frameworks, like Hadoop and Spark, in massive 3D protein structure alignments and identification of intrinsically disordered regions in protein structures. The fourth part of the book focuses on finding 3D protein structure similarities, accelerated with the use of GPUs and the use of multithreading and relational databases for efficient approximate searching on protein secondary structures. The book introduces advanced techniques and computational architectures that benefit from recent achievements in the field of computing and parallelism. Recent developments in computer science have allowed algorithms previously considered too time-consuming to now be efficiently used for applications in bioinformatics and the life sciences. Given its depth of coverage, the book will be of interest to researchers and software developers working in the fields of structural bioinformatics and biomedical databases.
  table of contents: Formal Model of 3D Protein Structures for Functional Genomics, Comparative Bioinformatics, and Molecular Modeling -- Multithreaded PSS-SQL for Searching Databases of Secondary Structures -- GPU and CUDA for 3D Protein Structure Similarity Searching -- Cloud Computing for 3D Protein Structure Alignment -- General Discussion and Concluding Remarks.
  note: by Dariusz Mrozek.
  note: Electronic resource.
  subject:
    topic: Bioinformatics
  subject:
    topic: Computer Communication Networks
  subject:
    topic: Biochemistry
  subject:
    topic: Computational Biology/Bioinformatics
  subject:
    topic: Computer Communication Networks
  subject:
    topic: Protein Structure
  subject:
    topic: Bioinformatics
  subject:
    topic: Mathematical and Computational Biology
  classification: QH324.2-324.25
  classification: 570.285
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Computational biology. 28
  identifier: 9783319988399
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record creation date: 180925
    record change date: 20240730210918.3
    record identifier: in00004008108