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1.  Genomic Promoter Analysis Predicts Functional Transcription Factor Binding 
Advances in bioinformatics  2008;2008:3698301-3698309.
Background
The computational identification of functional transcription factor binding sites (TFBSs) remains a major challenge of computational biology.
Results
We have analyzed the conserved promoter sequences for the complete set of human RefSeq genes using our conserved transcription factor binding site (CONFAC) software. CONFAC identified 16296 human-mouse ortholog gene pairs, and of those pairs, 9107 genes contained conserved TFBS in the 3 kb proximal promoter and first intron. To attempt to predict in vivo occupancy of transcription factor binding sites, we developed a novel marginal effect isolator algorithm that builds upon Bayesian methods for multigroup TFBS filtering and predicted the in vivo occupancy of two transcription factors with an overall accuracy of 84%.
Conclusion
Our analyses show that integration of chromatin immunoprecipitation data with conserved TFBS analysis can be used to generate accurate predictions of functional TFBS. They also show that TFBS cooccurrence can be used to predict transcription factor binding to promoters in vivo.
doi:10.1155/2008/369830
PMCID: PMC2768302  PMID: 19865592
2.  Genomic Promoter Analysis Predicts Functional Transcription Factor Binding 
Advances in Bioinformatics  2008;2008:369830.
Background. The computational identification of functional transcription factor binding sites (TFBSs) remains a major challenge of computational biology. Results. We have analyzed the conserved promoter sequences for the complete set of human RefSeq genes using our conserved transcription factor binding site (CONFAC) software. CONFAC identified 16296 human-mouse ortholog gene pairs, and of those pairs, 9107 genes contained conserved TFBS in the 3 kb proximal promoter and first intron. To attempt to predict in vivo occupancy of transcription factor binding sites, we developed a novel marginal effect isolator algorithm that builds upon Bayesian methods for multigroup TFBS filtering and predicted the in vivo occupancy of two transcription factors with an overall accuracy of 84%. Conclusion. Our analyses show that integration of chromatin immunoprecipitation data with conserved TFBS analysis can be used to generate accurate predictions of functional TFBS. They also show that TFBS cooccurrence can be used to predict transcription factor binding to promoters in vivo.
doi:10.1155/2008/369830
PMCID: PMC2768302  PMID: 19865592
3.  Cross-platform expression profiling demonstrates that SV40 small tumor antigen activates Notch, Hedgehog, and Wnt signaling in human cells 
BMC Cancer  2006;6:54.
Background
We previously analyzed human embryonic kidney (HEK) cell lines for the effects that simian virus 40 (SV40) small tumor antigen (ST) has on gene expression using Affymetrix U133 GeneChips. To cross-validate and extend our initial findings, we sought to compare the expression profiles of these cell lines using an alternative microarray platform. METHODS: We have analyzed matched cell lines with and without expression of SV40 ST using an Applied Biosystems (AB) microarray platform that uses single 60-mer oligonucleotides and single-color quantitative chemiluminescence for detection. RESULTS: While we were able to previously identify only 456 genes affected by ST with the Affymetrix platform, we identified 1927 individual genes with the AB platform. Additional technical replicates increased the number of identified genes to 3478 genes and confirmed the changes in 278 (61%) of our original set of 456 genes. Among the 3200 genes newly identified as affected by SV40 ST, we confirmed 20 by QRTPCR including several components of the Wnt, Notch, and Hedgehog signaling pathways, consistent with SV40 ST activation of these developmental pathways. While inhibitors of Notch activation had no effect on cell survival, cyclopamine had a potent killing effect on cells expressing SV40 ST. CONCLUSIONS: These data show that SV40 ST expression alters cell survival pathways to sensitize cells to the killing effect of Hedgehog pathway inhibitors.
doi:10.1186/1471-2407-6-54
PMCID: PMC1420312  PMID: 16522205
4.  CONFAC: automated application of comparative genomic promoter analysis to DNA microarray datasets 
Nucleic Acids Research  2004;32(Web Server issue):W475-W484.
The advent of DNA microarray technology and the sequencing of multiple vertebrate genomes has provided a unique opportunity for the integration of comparative genomics with high-throughput gene expression analysis. Here we describe the conserved transcription factor binding site (CONFAC) software that enables the high-throughput identification of conserved transcription factor binding sites (TFBSs) in the regulatory regions of hundreds of genes at a time (http://morenolab.whitehead.emory.edu/cgi-bin/confac/login.pl). The CONFAC software compares non-coding regulatory sequences between human and mouse genomes to enable identification of conserved TFBSs that are significantly enriched in promoters of gene clusters from microarray analyses compared to sets of unchanging control genes using a Mann–Whitney U-test. Analysis of random gene sets demonstrated that using our approach, over 98% of TFBSs had false positive rates below 5%. As a proof-of-principle, we have validated the CONFAC software using gene sets from four separate microarray studies and identified TFBSs known to be functionally important for regulation of each of the four gene sets.
doi:10.1093/nar/gkh353
PMCID: PMC441491  PMID: 15215433

Results 1-4 (4)