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BACKGROUND Type 2 diabetes mellitus (T2DM) is a complex systemic disease, with significant disorders of metabolism. The liver, a central energy metabolic organ, plays a critical role in the development of diabetes. Although gene expression levels are able to be measured via microarray since 1996, it is difficult to evaluate the contributions of one altered(More)
Synergistic interactions among transcription factors (TFs) and their cofactors collectively determine gene expression in complex biological systems. In this work, we develop a novel graphical model, called Active Protein-Gene (APG) network model, to quantify regulatory signals of transcription in complex biomolecular networks through integrating both TF(More)
We have recently identified a number of active regulatory networks involved in diabetes progression in Goto-Kakizaki (GK) rats by network screening. The networks were quite consistent with the previous knowledge of the regulatory relationships between transcription factors (TFs) and their regulated genes. To study the underlying molecular mechanisms(More)
We estimated the key molecules related to Type 2 diabetes mellitus (T2DM) in adipose, liver, and muscle tissues, from nonobese diabetic Goto-Kakizaki (GK) rats and their Wistar controls, by computationally analyzing the expression profiles in open source data. With the aid of information from previous reports, Rev-erbα in adipose tissue emerged as one of(More)
—Recently, we have identified 39 candidates of active regulatory networks for the diabetes progression in Goto-Kakizaki (GK) rat by using the network screening, which were well consistent with the previous knowledge of regulatory relationship between transcription factors (TFs) and their regulated genes. In addition, we have developed a computational(More)
In the aim of identifying significant transcriptional regulatory networks in the liver contributing to diabetes, we have performed comprehensive active regulatory network survey by network screening in 4weeks (w), 8-12w, and 18-20w Goto-Kakizaki (GK) rat liver microarray data. The comprehensive survey of the consistency between the networks and the measured(More)
In this report, we designed a procedure for exploring the cellular relationships from the sets of characteristic genes in distinctive cell types, by using partial canonical correlation analysis. We applied the present procedure to the characteristic gene sets of seven subtypes of testicular germ cell tumors in a previous report. The cellular relationships(More)
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