Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2007 Jul;35(Web Server issue):W238-44.
doi: 10.1093/nar/gkm308. Epub 2007 May 21.

PAP: a comprehensive workbench for mammalian transcriptional regulatory sequence analysis

Li-Wei Chang  1 , Burr R Fontaine, Gary D Stormo, Rakesh Nagarajan
Affiliations

PAP: a comprehensive workbench for mammalian transcriptional regulatory sequence analysis

Li-Wei Chang et al. Nucleic Acids Res. 2007 Jul.

Abstract

Given the recent explosion of publications that employ microarray technology to monitor genome-wide expression and that correlate these expression changes to biological processes or to disease states, the determination of the transcriptional regulation of these co-expressed genes is the next major step toward deciphering the genetic network governing the pathway or disease under study. Although computational approaches have been proposed for this purpose, there is no integrated and user-friendly software application that allows experimental biologists to tackle this problem in higher eukaryotes. We have previously reported a systematic, statistical model of mammalian transcriptional regulatory sequence analysis. We have now made crucial extensions to this model and have developed a comprehensive, user-friendly web application suite termed the Promoter Analysis Pipeline (PAP). PAP is available at: http://bioinformatics.wustl.edu/webTools/portalModule/PromoterSearch.do.

PubMed Disclaimer

Figures

Figure 1.
Figure 1.
Workflow of the user interface of PAP. A complete PAP analysis consists of four major steps: gene selection (orange), transcription factor selection (yellow), result visualization (green) and advanced analyses (blue). The major workflow of a typical analysis is shown in pink arrows. Links between pages are shown in gray arrows.
Figure 2.
Figure 2.
Screenshot of the Transcription Factor Selection page. The distribution of transcription factors as determined by their probability of regulating a set of ‘interesting’ genes is shown. The user may adjust the threshold to select high-scoring transcription factors.
Figure 3.
Figure 3.
Screenshot of the result overview page. Predicted transcription factor binding sites that are conserved in selected species are shown in a sequence browser. The user may alter the stringency of evolutionary conservation or view multiple sequence alignments annotated by binding sites in this page.
See this image and copyright information in PMC

References

    1. Tenen DG. Disruption of differentiation in human cancer: AML shows the way. Nat. Rev. Cancer. 2003;3:89–101. - PubMed
    1. Mooradian AD, Haas MJ, Wong NC. Transcriptional control of apolipoprotein A-I gene expression in diabetes. Diabetes. 2004;53:513–520. - PubMed
    1. Davicioni E, Finckenstein FG, Shahbazian V, Buckley JD, Triche TJ, Anderson MJ. Identification of a PAX-FKHR gene expression signature that defines molecular classes and determines the prognosis of alveolar rhabdomyosarcomas. Cancer Res. 2006;66:6936–6946. - PubMed
    1. Borovecki F, Lovrecic L, Zhou J, Jeong H, Then F, Rosas HD, Hersch SM, Hogarth P, Bouzou B, et al. Genome-wide expression profiling of human blood reveals biomarkers for Huntington's disease. Proc. Natl Acad. Sci. USA. 2005;102:11023–11028. - PMC - PubMed
    1. Segal E, Friedman N, Kaminski N, Regev A, Koller D. From signatures to models: understanding cancer using microarrays. Nat. Genet. 2005;37(Suppl. 1):S38–45. - PubMed

Publication types

Substances