| To understand the wealth of genomic data that has recently become available, and to tackle large biological problems, biologists need effective tools for computational analysis. My graduate research developed tools in several areas of computational biology. I have developed new methods to produce large genomic alignments, to find genes in genomic sequence, and to analyze sequences phylogenetically.;Given only genomic sequence data, gene finders seek to the locate the genes in a given sequence and determine their structures. Most gene finders utilize only a single sequence. The best of these use practically all available biological knowledge that could be useful, but such methods remain far from accurate.;Additional information useful for gene finding can be found in the correlations between multiple long (100s to 1000s of kilobase) homologous sequences. To utilize this information, I designed and implemented algorithms for the alignment of sequences like these.;Within these alignments are recognizable patterns (signals) arising from conservation due to natural selection; there are also noises which come primarily from the stochastic nature of mutation. Fortunately, these signals and noises can largely be separated using a method called pattern filtering. The core of pattern filtering is a Wiener filter, which has been proven to be the optimal linear method for separating signals from stochastic noise.;Using the pattern-filtered distances and a few conventional single-sequence signals, the gene finding program which I designed performs better than the best single sequence gene finder or any other published multiple sequence method. Additionally, it readily identifies potential DNA regulatory elements and detects some DNA sequencing errors. We anticipate that pattern filtering will facilitate sequence annotation and the discovery of new functional elements by the genetics and genomics communities.;I also developed and implemented methods in phylogenetic analysis, which are useful for the study of horizontal gene transfer and the development of Bayesian methods for phylogenetic reconstruction. |
