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

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