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- Type of Document: M.Sc. Thesis
- Language: Farsi
- Document No: 55856 (19)
- University: Sharif University of Technology
- Department: Computer Engineering
- Advisor(s): Koohi, Somayyeh
- Abstract:
- Motif finding problem in biology is a search for repeated patterns to reveal information about gene expression, one of the most complex subsystems in genomics. ChIP-seq technology abled researchers to investigate location of protein-DNA interactions but analyzing downstream results of such experiments to find actual regulatory signals in genome is challenging. For many years, applications of motif finding had models based on limiting assumption as an exchange for lower computational complexity. Results: AKAGI program is build upon upgraded methods and new general models to investigate statistical and experimental evidences for accurately finding significant patterns among biological sequences. Here we present AKAGI and discuss its significant results on ChIP-seq datasets by comparing it with known motif profiles in jaspar database. Motifs from AKAGI are the most general patterns, without any length strains for its instances and considers edit distances instead of only hamming distances despite many other tools. Evidences used by AKAGI is evaluated by executing experiments of the same target protein but in different cells which finally pointed out nearly the same results
- Keywords:
- Parallelization ; Distributed System ; ChIP-Seq ; Edit Distance ; Protein-DNA Interaction ; Motif Finding ; Gene Expression Data
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