• DocumentCode
    3496354
  • Title

    Towards whole transcriptome deconvolution using single-cell data

  • Author

    Lindsay, James ; Nelson, Craig E. ; Mandoiu, Ion I.

  • Author_Institution
    Comput. Sci. & Eng., Univ. of Connecticut, Storrs, CT, USA
  • fYear
    2013
  • fDate
    12-14 June 2013
  • Firstpage
    1
  • Lastpage
    1
  • Abstract
    Obtaining whole-transcriptome expression profiles of closely related cell types is a daunting task faced by stem-cell biologists. Here we present an approach that utilizes single-cell qPCR probing of a small number of genes to aid in the deconvolution of whole-transcriptome profiles of mixed samples.
  • Keywords
    cellular biophysics; genetics; daunting task; genes; single-cell data; single-cell qPCR probing; stem-cell biologists; whole transcriptome deconvolution; whole-transcriptome expression profiles; Biological cells; Computational modeling; Computer science; Deconvolution; Educational institutions; Gene expression;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Advances in Bio and Medical Sciences (ICCABS), 2013 IEEE 3rd International Conference on
  • Conference_Location
    New Orleans, LA
  • Type

    conf

  • DOI
    10.1109/ICCABS.2013.6629234
  • Filename
    6629234
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3496354