Abstract
| Original language | English |
|---|---|
| Pages (from-to) | 429 - 435 |
| Number of pages | 7 |
| Journal | Trends in Biotechnology |
| Volume | 23 |
| Issue number | 8 |
| DOIs | |
| Publication status | Published - 2005 |
| MoE publication type | A1 Journal article-refereed |
Fingerprint
Keywords
- cDNA microarrays
- microarray
- oligonucleotide microarrays
- pathway analysis
Cite this
}
Pathways to the analysis of microarray data. / Curtis, R. Keira (Corresponding Author); Orešič, Matej; Vidal-Puig, Antonio.
In: Trends in Biotechnology, Vol. 23, No. 8, 2005, p. 429 - 435.Research output: Contribution to journal › Article › Scientific › peer-review
TY - JOUR
T1 - Pathways to the analysis of microarray data
AU - Curtis, R. Keira
AU - Orešič, Matej
AU - Vidal-Puig, Antonio
PY - 2005
Y1 - 2005
N2 - The development of microarray technology allows the simultaneous measurement of the expression of many thousands of genes. The information gained offers an unprecedented opportunity to fully characterize biological processes. However, this challenge will only be successful if new tools for the efficient integration and interpretation of large datasets are available. One of these tools, pathway analysis, involves looking for consistent but subtle changes in gene expression by incorporating either pathway or functional annotations. We review several methods of pathway analysis and compare the performance of three, the binomial distribution, z scores, and gene set enrichment analysis, on two microarray datasets. Pathway analysis is a promising tool to identify the mechanisms that underlie diseases, adaptive physiological compensatory responses and new avenues for investigation.
AB - The development of microarray technology allows the simultaneous measurement of the expression of many thousands of genes. The information gained offers an unprecedented opportunity to fully characterize biological processes. However, this challenge will only be successful if new tools for the efficient integration and interpretation of large datasets are available. One of these tools, pathway analysis, involves looking for consistent but subtle changes in gene expression by incorporating either pathway or functional annotations. We review several methods of pathway analysis and compare the performance of three, the binomial distribution, z scores, and gene set enrichment analysis, on two microarray datasets. Pathway analysis is a promising tool to identify the mechanisms that underlie diseases, adaptive physiological compensatory responses and new avenues for investigation.
KW - cDNA microarrays
KW - microarray
KW - oligonucleotide microarrays
KW - pathway analysis
U2 - 10.1016/j.tibtech.2005.05.011
DO - 10.1016/j.tibtech.2005.05.011
M3 - Article
VL - 23
SP - 429
EP - 435
JO - Trends in Biotechnology
JF - Trends in Biotechnology
SN - 0167-7799
IS - 8
ER -