PlasmoTFBM: An Intelligent Queriable Database for Predicted Transcription Factor Binding Motifs in Plasmodium falciparum

Chengyong Yang; Erliang Zeng; Kalai Mathee; Giri Narasimhan

doi:10.1007/978-0-387-34569-7_9

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Book chapter

PlasmoTFBM: An Intelligent Queriable Database for Predicted Transcription Factor Binding Motifs in Plasmodium falciparum

Chengyong Yang, Erliang Zeng, Kalai Mathee and Giri Narasimhan

Methods of Microarray Data Analysis V, pp.121-136

Springer US

2007

DOI: 10.1007/978-0-387-34569-7_9

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Abstract

There is very little information available with regard to gene regulatory circuitries in Plasmodium falciparum. In an attempt to discover transcription factor binding motifs (TFBMs) in P. falciparum, we considered two approaches. In the first approach, gene expression data from asexual intraerythrocytic developmental cycle generated every hour for 48 hour post-infection were fed into the ISA (Iterative Signature Algorithm), which outputs modules composed of sets of genes associated with co-regulating conditions. Putative TFBMs were discovered by applying the AlignACE program on the resulting gene sets. In the second approach, the MotifRegressor program was used to predict potential motifs associated with induced and repressed genes for each time point and then clustered based on the strength of their correlation to the gene expression (i.e., motif coefficients) across different time points. A total of 637 and 840 putative motifs were predicted by the MotifRegressor and ISA-AlignACE programs, respectively. All this information was uploaded into a database, thus making it easy to devise complex queries. Using published information on known motifs, we were able to validate some of our results. In addition, modules consisting of putative transcription factors and related genes were also investigated. This work provides a bioinformatics methodology to analyze transcription regulation and TFBMs across the whole genome. By constructing a comprehensive relational database and an intelligent, user-friendly query system, biologically meaningful conclusions can be drawn easily even by an investigator with no prior knowledge of databases.

Genes

transcription factor

Plasmodium falciparum

regulatory elements

motifs

elements

SERA

EBA140

heat shock protein

G-box

Details

Title: Subtitle: PlasmoTFBM: An Intelligent Queriable Database for Predicted Transcription Factor Binding Motifs in Plasmodium falciparum
Creators: Chengyong Yang - Bioinformatics Research Group (BioRG), School of Computing and Informations Sciences, Florida International University, Miami, USA
Erliang Zeng - Bioinformatics Research Group (BioRG), School of Computing and Informations Sciences, Florida International University, Miami, USA
Kalai Mathee - Department of Biological Sciences, Florida International University, Miami, USA
Giri Narasimhan - Bioinformatics Research Group (BioRG), School of Computing and Informations Sciences, Florida International University, Miami, USA
Resource Type: Book chapter
Publication Details: Methods of Microarray Data Analysis V, pp.121-136
DOI: 10.1007/978-0-387-34569-7_9
Publisher: Springer US; Boston, MA
Language: English
Date published: 2007
Academic Unit: Preventive and Community Dentistry; Roy J. Carver Department of Biomedical Engineering; Iowa Neuroscience Institute; Biostatistics; Dental Research
Record Identifier: 9984065368302771

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