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: Predicting the Lineage Choice of Hematopoietic Stem Cells
    sub title: A Novel Approach Using Deep Neural Networks
  name:
    name part: Kroiss, Manuel.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2016
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XV, 68 p. online resource.
  abstract: Manuel Kroiss examines the differentiation of hematopoietic stem cells using machine learning methods. This work is based on experiments focusing on the lineage choice of CMPs, the progenitors of HSCs, which either become MEP or GMP cells. The author presents a novel approach to distinguish MEP from GMP cells using machine learning on morphology features extracted from bright field images. He tests the performance of different models and focuses on Recurrent Neural Networks with the latest advances from the field of deep learning. Two different improvements to recurrent networks were tested: Long Short Term Memory (LSTM) cells that are able to remember information over long periods of time, and dropout regularization to prevent overfitting. With his method, Manuel Kroiss considerably outperforms standard machine learning methods without time information like Random Forests and Support Vector Machines. Contents Machine Learning – Deep Learning Training Neural Networks Recurrent Neural Networks Stem Cell Classification Using Microscopy Images Target Groups Teachers and students in the field of computer science and applied machine learning Executives and specialists in the field of neural networks and computational biology About the Author After finishing his MSc in Bioinformatics, Manuel Kroiss moved to London to work for a computer science company. In his work, the author is focusing on algorithmic problem solving while still remaining interested in applied machine learning.
  table of contents: Machine Learning – Deep Learning -- Training Neural Networks -- Recurrent Neural Networks -- Stem Cell Classification Using Microscopy Images.
  note: by Manuel Kroiss.
  subject:
    topic: Chemistry
  subject:
    topic: Organic chemistry
  subject:
    topic: Chemical engineering
  subject:
    topic: Catalysis
  subject:
    topic: Chemistry
  subject:
    topic: Organic Chemistry
  subject:
    topic: Catalysis
  subject:
    topic: Industrial Chemistry/Chemical Engineering
  classification: QD415-436
  classification: 547
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: BestMasters
  identifier: 9783658128791
  identifier: http://dx.doi.org/10.1007/978-3-658-12879-1
  record info:
    record creation date: 160512
    record change date: 20160512133834.0
    record identifier: 978-3-658-12879-1