{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/28438"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/28438","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Algorithmic advances towards a fully automated DNA genotyping system","abstract":"Short Tandem Repeats (STR) genotyping is a leading tool in forensic DNA analysis. In STR genotyping, alleles in a sample are identified by measuring their lengths to form a genetic profile. Forming a genetic profile is time-consuming and labor-intensive. As the technology matures, increasing demand for improved throughput and efficiency is fueling development of automated forensic DNA analysis systems. This thesis describes two algorithmic advances towards implementing such a system. In particular, the algorithms address motif-matching and pattern recognition issues that arise in processing a genetic profile. 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