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Title: Graphical representation of biological information
Keywords: TFBS, promoter, motif, ab-initio, heuristics, expectation-maximization, genetic algorithm
Issue Date: 29-May-2006
Citation: HUANG ENLI (2006-05-29). Graphical representation of biological information. ScholarBank@NUS Repository.
Abstract: Biological information is complex due to numerous ways how biological entities affect each other. Human comprehension of this information is easier if the information is in a graphic form. However, different biological problems require different types of information to be presented and thus graphical information is dependent on the type of problem in question and equally on the type of data from which the representation is generated. In this study I focused on preparation of data for graphical representation and graphical presentation of information for several transcription regulation problems. The problems investigated were: a/ annotation of human promoters by transcription factor binding sites (TFBSs), b/ distribution of DNA motifs in a set of sequences, c/ networks of genes and associated TFBSs or motifs. In this process, a database of annotated human promoters with interactive graphical representation of the promoter content is developed where user can visualize distribution of individual TFBSs and pairs of TFBSs across the promoter and also find basic information on the TFBSs. Two novel heuristic models (based on expectation maximization and genetic algorithm) to identify motifs by ab-initio approach were developed and implemented. This allowed for the visualization of the distribution of motifs found across set of sequences and within individual sequences. Moreover, this served as a basis for producing data from which graphical representation of transcriptional regulatory networks were derived. The results developed in this study have been proven useful for the analysis of several transcription regulation problems as they allowed for inspection of complex relation between TFBSs/motifs and promoters/genes through relatively simple graphical representation.
Appears in Collections:Master's Theses (Open)

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