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: Comparative Gene Finding
    sub title: Models, Algorithms and Implementation
  name:
    name part: Axelson-Fisk, Marina.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: xxk
    date issued: 2015
    edition: 2nd ed. 2015.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XX, 382 p. 81 illus. online resource.
  abstract: This unique text/reference presents a concise guide to building computational gene finders, and describes the state of the art in computational gene finding methods, with a particular focus on comparative approaches. Fully updated and expanded, this new edition examines next-generation sequencing (NGS) technology, including annotation pipelines for NGS data. The book also discusses conditional random fields, enhancing the broad coverage of topics spanning probability theory, statistics, information theory, optimization theory, and numerical analysis. Topics and features: Introduces the fundamental terms and concepts in the field, and provides an historical overview of algorithm development Discusses algorithms for single-species gene finding, and approaches to pairwise and multiple sequence alignments, then describes how the strengths in both areas can be combined to improve the accuracy of gene finding Explores the gene features most commonly captured by a computational gene model, and explains the basics of parameter training Illustrates how to implement a comparative gene finder, reviewing the different steps and accuracy assessment measures used to debug and benchmark the software Examines NGS techniques, and how to build a genome annotation pipeline, discussing sequence assembly, de novo repeat masking, and gene prediction (NEW) Postgraduate students, and researchers wishing to enter the field quickly, will find this accessible text a valuable source of insights and examples. A suggested course outline for instructors is provided in the preface. Dr. Marina Axelson-Fisk is an Associate Professor at the Department of Mathematical Sciences of Chalmers University of Technology, Gothenburg, Sweden.
  table of contents: Introduction -- Single Species Gene Finding -- Sequence Alignment -- Comparative Gene Finding -- Gene Structure Submodels -- Parameter Training -- Implementation of a Comparative Gene Finder -- Annotation Pipelines for Next Generation Sequencing Projects.
  note: by Marina Axelson-Fisk.
  subject:
    topic: Computer science
  subject:
    topic: Bioinformatics
  subject:
    topic: Computer Science
  subject:
    topic: Computational Biology/Bioinformatics
  subject:
    topic: Bioinformatics
  classification: QH324.2-324.25
  classification: 570.285
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Computational Biology, 20
  identifier: 9781447166931
  identifier: http://dx.doi.org/10.1007/978-1-4471-6693-1
  record info:
    record creation date: 150413
    record change date: 20170127141432.0
    record identifier: 978-1-4471-6693-1