A Mixed Model Approach to Identify Yeast Transcriptional Regulatory Motifs via Microarray Experiments
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| 024 | 7 | 0 | |a 10.2202/1544-6115.1045 |2 doi |
| 035 | |a (NATIONALLICENCE)gruyter-10.2202/1544-6115.1045 | ||
| 245 | 0 | 2 | |a A Mixed Model Approach to Identify Yeast Transcriptional Regulatory Motifs via Microarray Experiments |h [Elektronische Daten] |c [Xiang Yu, Tzu-Ming Chu, Greg Gibson, Russell D Wolfinger] |
| 520 | 3 | |a A genome-wide location analysis method has been introduced as a means to simultaneously study protein-DNA binding interactions for a large number of genes on a microarray platform. Identification of interactions between transcription factors (TF) and genes provide insight into the mechanisms that regulate a variety of cellular responses. Drawing proper inferences from the experimental data is key to finding statistically significant TF-gene binding interactions. We describe how the analysis and interpretation of genome-wide location data can be fit into a traditional statistical modeling framework that considers the data across all arrays and formulizes appropriate hypothesis tests. The approach is illustrated with data from a yeast transcription factor binding experiment that illustrates how identified TF-gene interactions can enhance initial exploration of transcriptional regulatory networks. Examples of five kinds of transcriptional regulatory structure are also demonstrated. Some stark differences with previously published results are explored. | |
| 540 | |a ©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston | ||
| 690 | 7 | |a Microarrays |2 nationallicence | |
| 690 | 7 | |a Computational Biology/Bioinformatics |2 nationallicence | |
| 700 | 1 | |a Yu |D Xiang |u Bioinformatics Research Center, North Carolina State University |4 aut | |
| 700 | 1 | |a Chu |D Tzu-Ming |u Department of Genomics, SAS Institute Inc |4 aut | |
| 700 | 1 | |a Gibson |D Greg |u Bioinformatics Research Center, North Carolina State University; Department of Genetics, North Carolina State University |4 aut | |
| 700 | 1 | |a Wolfinger |D Russell D. |u Department of Genomics, SAS Institute Inc |4 aut | |
| 773 | 0 | |t Statistical Applications in Genetics and Molecular Biology |d De Gruyter |g 3/1(2004-09-29), 1-20 |q 3:1<1 |1 2004 |2 3 |o sagmb | |
| 856 | 4 | 0 | |u https://doi.org/10.2202/1544-6115.1045 |q text/html |z Onlinezugriff via DOI |
| 908 | |D 1 |a research article |2 jats | ||
| 950 | |B NATIONALLICENCE |P 856 |E 40 |u https://doi.org/10.2202/1544-6115.1045 |q text/html |z Onlinezugriff via DOI | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Yu |D Xiang |u Bioinformatics Research Center, North Carolina State University |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Chu |D Tzu-Ming |u Department of Genomics, SAS Institute Inc |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Gibson |D Greg |u Bioinformatics Research Center, North Carolina State University; Department of Genetics, North Carolina State University |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Wolfinger |D Russell D. |u Department of Genomics, SAS Institute Inc |4 aut | ||
| 950 | |B NATIONALLICENCE |P 773 |E 0- |t Statistical Applications in Genetics and Molecular Biology |d De Gruyter |g 3/1(2004-09-29), 1-20 |q 3:1<1 |1 2004 |2 3 |o sagmb | ||
| 900 | 7 | |b CC0 |u http://creativecommons.org/publicdomain/zero/1.0 |2 nationallicence | |
| 898 | |a BK010053 |b XK010053 |c XK010000 | ||
| 949 | |B NATIONALLICENCE |F NATIONALLICENCE |b NL-gruyter | ||