Genomic sequence databases are widely used by molecular biologists for homology searching. Amino-acid and nucleotide databases are increasing in size exponentially, and mean sequence lengths are also increasing. In searching such databases, it is desirable to use heuristics to perform computationally intensive local alignments on selected sequences only and to reduce the costs of the alignments that are attempted. We present an index-based approach for both selecting sequences that display broad similarity to a query and for fast local alignment. We show experimentally that the indexed approach results in signi cant savings in computationally intensive local alignments, and that index-based searching is as accurate as existing exhaustive search schemes.

Virtually all large-scale sequencing projects use automatic sequence-assembly programs to aid in the determination of DNA sequences. The computer-generated assemblies require substantial hand-editing to transform them into submissions for GenBank. As the size of sequencing projects increases, it becomes essential to improve the quality of the automated assemblies so that this timeconsuming hand-editing may be reduced. Current ABI sequencing technology uses base calls made from fluorescently-labeled DNA fragments run on gels. We present a new representation for the fluorescent trace data associated with individual base calls. This representation can be used before, during, and after fragment assembly to improve the quality of assemblies. We demonstrate one such use -- end-trimming of sub-optimal data -- that results in a significant improvement in the quality of subsequent assemblies. Introduction A fundamental goal of the Human Genome Project is to determine the seque...

for their love, laughter, and support As advances in technology result in the production of increasing amounts of DNA sequencing data in decreasing amounts of time, it is imperative that computational methods are developed that allow data analysis to keep pace. In this dissertation, I present methods that improve the speed and accuracy of DNA fragment assembly. One critical characteristic of automatic methods for fragment assembly is that they must be accurate. Currently, to ensure accurate sequences, the data that underlies questionable base calls must be examined by human editors so that the correct base call can be determined. This manual process is both error-prone and time-consuming. Automatic methods that yield high accuracy and few questionable calls can reduce errors and lessen the need for manual inspections. In my work, I developed a method, Trace-Evidence, that automatically produces highly accurate consensus sequences, even with few aligned sequences. Most assembly programs analyze only base calls when determining a consensus sequence. The key to the high accuracy is that I incorporate morphological information about the