Author :
Seo, Daekwan ; Yasunaga, Moritoshi ; Kim, Jung Hwan
Author_Institution :
Dept. of Appl. Sci., Arkansas Univ., Little Rock, AR, USA
Abstract :
Finding transcription regulatory elements (TREs) is one of most important tasks in current bioinformatics and functional genomics and is the first step to discover regulatory mechanisms of gene expression. The goal of this paper is to detect class-specific TREs associated with four classes of developmentally regulated genes in Dictyostelium discoideum (Dd) with statistically significant measure. Applying a DP matching to 5\´ UTR sequences of Dd with generated candidate TREs, we calculate the evaluation score (E-score) for given candidate TREs. Based on the proposed selection criteria of TREs, we choose putative class-specific TREs among candidate TREs in each developmentally regulated class of Dd. According to the simulation result with 49 sequences in V expression stage, 43 in A, 42 in S, and 47 in C, we predicted class-specific putative TREs, corresponding to a P ≤ 10-3 such as "aataattt", "attacaaa", and "attaatat" in V, "ttattcta", "atgtgtta", and "aaaattga" in A, "atttcaat", "aataattg", and "acaacaac" in S, "aaaaaatt", "ttaataat", and "atagtttt" in C expression stage of Dd. We could achieve 17.8 times faster TRE detection via parallel computing algorithm with 32 processor machines.
Keywords :
biology computing; genetics; microorganisms; parallel algorithms; pattern classification; C expression stage; Dictyostelium discoideum; TRE detection; UTR sequences; bioinformatics; computational approach; evaluation score; functional genomics; gene expression; parallel computing algorithm; processor machine; regulatory element detection; transcription regulatory elements; Bioinformatics; Biological information theory; Cells (biology); Gene expression; Genetics; Genomics; Organisms; Predictive models; Sequences; Systems engineering and theory;