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: Advancing Gene Fusion Detection Towards Personalized Cancer Nanodiagnostics
  name:
    name part: Koo, Kevin M.
    role:
      role term: creator
    role:
      role term: author.
    role:
      role term: aut
    role:
      role term: http://id.loc.gov/vocabulary/relators/aut
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2019
    edition: 1st ed. 2019.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XIII, 102 p. online resource.
  abstract: This book presents a unique concept of merging nanotechnology and novel urinary biomarkers for accurate early prostate cancer detection, discussing an entire progressive pipeline of innovative new strategies in biosensor development, from a simple colorimetric system to a complex system for simultaneous multiple biomarker sensing. For newcomers to the field of nucleic acid biosensing, it also describes various isothermal amplification and amplification-free strategies, which are currently the main research areas. Lastly, the book introduces and demonstrates the notion of clinical nanobiosensor validation toward clinical translation: the ultimate aim of researchers in the biosensor field. This book is a valuable reference resource learners seeking inspiration for cancer biosensor development.
  table of contents: Unifying Next-Generation Biomarkers and Nanodiagnostic Platforms for Precision Prostate Cancer (PCa) Management -- Colorimetric Gene Fusion Diagnostics for Visual Binary Readout -- Label -Free Surface-Enhanced Raman Scattering Detection System for Clinical Biomarker Targets -- Amplification-Free Electrochemical RNA Biomarker Sensing -- Simultaneous Analysis of Multiple Biomarkers via High-Throughput Parallel Profiling.
  note: by Kevin M. Koo.
  subject:
    topic: Biomedical engineering
  subject:
    topic: Nanotechnology
  subject:
    topic: Cancer research
  subject:
    topic: Biomedical Engineering/Biotechnology
  subject:
    topic: Nanotechnology
  subject:
    topic: Biomedical Engineering and Bioengineering
  subject:
    topic: Cancer Research
  classification: R856-R857
  classification: 610.28
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Springer Theses, Recognizing Outstanding Ph.D. Research
  identifier: 9783030310004
  identifier: https://doi.org/10.1007/978-3-030-31000-4
  record info:
    record creation date: 190924
    record change date: 20191022021011.0
    record identifier: 978-3-030-31000-4