Atlas of Signaling for Interpretation of Microarray Experiments

Abstract

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.

In silico analysis of high affinity potassium transporter (HKT) isoforms in different plants

“…Then, the data of this experiment was analyzed using pathway studio 9 and ResNet5.0 database. Pathway Studio is a commercial product for pathway analysis, containing a comprehensive database of protein–protein relationships extracted from literature using MedScan an entirely automated biomedical information extraction engine [ 10 ].…”

Gene Expression Differences Predict Treatment Outcome of Merkel Cell Carcinoma Patients

“…In order to better understand the biological context of the gene expression differences between MCC from good and poor prognosis patients, the expression microarray data was analyzed using Ariadne Pathway Studio's Subnetwork Enrichment Analysis tool [ 16 , 17 ]. Pathway Studio utilizes MedScan, the literature mining program that searches publicly the available literature such as PubMed for relationships between entities [ 18 ].…”

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