The signal elements in promoter sequences are not well characterized. We propose to develop statistical tests to find nucleotide words (generally of length 8) that appear localized relative to TSSs (transcription start site). These words will then form """"""""seeds"""""""" for expansion to develop PSSMs (position-specific scoring matrices) characterizing systems of co-regulated genes. To this end, Dr. Marino-Ramirez has collected a database of about 4700 sequences around the TSS of human genes. The database is exceptionally well characterized, and ideal for our statistical study. We are using two statistics, the well respected KS (Kolmogorov-Smirnov) statistic, and a less known Poisson scan statistic, to determine whether occurrences of a given 8-letter DNA word are clustered unusually relative to the TSS. The KS statistic provides a standard for sensitivity, but it does not assign the statistical significance to a particular set of word occurrences. The Poisson scan statistic does, however, and we plan to use its list of significant occurrences as our """"""""seeds"""""""" for developing our PSSMs.
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| Tharakaraman, Kannan; Marino-Ramirez, Leonardo; Sheetlin, Sergey L et al. (2006) Scanning sequences after Gibbs sampling to find multiple occurrences of functional elements. BMC Bioinformatics 7:408 |
| Tharakaraman, Kannan; Marino-Ramirez, Leonardo; Sheetlin, Sergey et al. (2005) Alignments anchored on genomic landmarks can aid in the identification of regulatory elements. Bioinformatics 21 Suppl 1:i440-8 |
| Marino-Ramirez, Leonardo; Spouge, John L; Kanga, Gavin C et al. (2004) Statistical analysis of over-represented words in human promoter sequences. Nucleic Acids Res 32:949-58 |
| Frith, Martin C; Hansen, Ulla; Spouge, John L et al. (2004) Finding functional sequence elements by multiple local alignment. Nucleic Acids Res 32:189-200 |
