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A strategy to identify genomic expression at single-cell level or a small number of cells

  • Biaoru Li(corresponding author)
*Corresponding author for this work
  • Case Western Reserve University
Scholary Output:
Contribution to journal
Review article
Peer-review

Abstract

Recent advances in functional genomics allow us to estimate the expression of several thousands of genes in the mammalian genome. Techniques such as microarrays, expressed tag sequencing (EST), serial analysis of gene expression (SAGE), subtractive cloning and differential display (DD), and two-dimensional electrophoresis gel have been extensively used to screen and analyze parallel gene expression. Some pathological processes, for example, tumorigenesis and solid tumour growth, in which the former is derived from a single-cell and the latter has a mixed-cell problem, present new challenges to the limit of these functional genomic techniques. To fully understand the functions of cells in tumorigenesis or in heterogeneous solid tumour masses, it is essential for scientists and physicians to develop a strategy to identify genomic expression profiles for a single-cell or for small numbers of cells. In this article, we review recently developed methods that enable functional genomic analysis at the single-cell or multicell level. In addition, the paper will review different techniques of single-cell genomic expression at the level of DNA, mRNA, protein and post-translational modifications.

Publication Information

Output type

Scholary Output:
Contribution to journal
Review article
Peer-review

Original language

English (US)

Pages from-to (Number of pages)

Pages 71-81 (11 pages)

Journal (Volume, Issue Number)

Electronic Journal of Biotechnology (Volume 8, Issue 1)

Publication milestones

  • Published - 04/15/2005

Publication status

Published - 04/15/2005

ISSN

0717-3458

Publication IDs

  • Scopus: 19344374851

Publication metrics

Metrics

Scopus
citations
SciVal
citations
6
SciVal
FWCI
0.23
SciVal
Author count
1
SciVal
Paper percentile
53
Fractional count
1
Fractional count
1
Fractional count
1
Fractional count
1

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Citation count
10
Captures
18