Atlas of signaling for interpretation of microarray experiments.
Microarray-based expression profiling of living systems is a quick and inexpensive method to obtain insights into the nature of various diseases and phenotypes. A typical microarray profile can yield hundreds or even thousands of differentially expressed genes and finding biologically plausible them...
Main Authors: | , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2010-01-01
|
Series: | PLoS ONE |
Online Access: | http://europepmc.org/articles/PMC2822851?pdf=render |
id |
doaj-df93682dd4ce44bcbea055a39df26100 |
---|---|
record_format |
Article |
spelling |
doaj-df93682dd4ce44bcbea055a39df261002020-11-24T21:46:42ZengPublic Library of Science (PLoS)PLoS ONE1932-62032010-01-0152e925610.1371/journal.pone.0009256Atlas of signaling for interpretation of microarray experiments.Ekaterina KotelnikovaNatalia IvanikovaAndrey KalininAnton YuryevNikolai DaraseliaMicroarray-based expression profiling of living systems is a quick and inexpensive method to obtain insights into the nature of various diseases and phenotypes. A typical microarray profile can yield hundreds or even thousands of differentially expressed genes and finding biologically plausible themes or regulatory mechanisms underlying these changes is a non-trivial and daunting task. We describe a novel approach for systems-level interpretation of microarray expression data using a manually constructed "overview" pathway depicting the main cellular signaling channels (Atlas of Signaling). Currently, the developed pathway focuses on signal transduction from surface receptors to transcription factors and further transcriptional regulation of cellular "workhorse" proteins. We show how the constructed Atlas of Signaling in combination with an enrichment analysis algorithm allows quick identification and visualization of the main signaling cascades and cellular processes affected in a gene expression profiling experiment. We validate our approach using several publicly available gene expression datasets.http://europepmc.org/articles/PMC2822851?pdf=render |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ekaterina Kotelnikova Natalia Ivanikova Andrey Kalinin Anton Yuryev Nikolai Daraselia |
spellingShingle |
Ekaterina Kotelnikova Natalia Ivanikova Andrey Kalinin Anton Yuryev Nikolai Daraselia Atlas of signaling for interpretation of microarray experiments. PLoS ONE |
author_facet |
Ekaterina Kotelnikova Natalia Ivanikova Andrey Kalinin Anton Yuryev Nikolai Daraselia |
author_sort |
Ekaterina Kotelnikova |
title |
Atlas of signaling for interpretation of microarray experiments. |
title_short |
Atlas of signaling for interpretation of microarray experiments. |
title_full |
Atlas of signaling for interpretation of microarray experiments. |
title_fullStr |
Atlas of signaling for interpretation of microarray experiments. |
title_full_unstemmed |
Atlas of signaling for interpretation of microarray experiments. |
title_sort |
atlas of signaling for interpretation of microarray experiments. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS ONE |
issn |
1932-6203 |
publishDate |
2010-01-01 |
description |
Microarray-based expression profiling of living systems is a quick and inexpensive method to obtain insights into the nature of various diseases and phenotypes. A typical microarray profile can yield hundreds or even thousands of differentially expressed genes and finding biologically plausible themes or regulatory mechanisms underlying these changes is a non-trivial and daunting task. We describe a novel approach for systems-level interpretation of microarray expression data using a manually constructed "overview" pathway depicting the main cellular signaling channels (Atlas of Signaling). Currently, the developed pathway focuses on signal transduction from surface receptors to transcription factors and further transcriptional regulation of cellular "workhorse" proteins. We show how the constructed Atlas of Signaling in combination with an enrichment analysis algorithm allows quick identification and visualization of the main signaling cascades and cellular processes affected in a gene expression profiling experiment. We validate our approach using several publicly available gene expression datasets. |
url |
http://europepmc.org/articles/PMC2822851?pdf=render |
work_keys_str_mv |
AT ekaterinakotelnikova atlasofsignalingforinterpretationofmicroarrayexperiments AT nataliaivanikova atlasofsignalingforinterpretationofmicroarrayexperiments AT andreykalinin atlasofsignalingforinterpretationofmicroarrayexperiments AT antonyuryev atlasofsignalingforinterpretationofmicroarrayexperiments AT nikolaidaraselia atlasofsignalingforinterpretationofmicroarrayexperiments |
_version_ |
1725900560545087488 |