| dc.contributor.advisor | Dan Ehrlich. | en_US |
| dc.contributor.author | Liu, Manway Michael, 1980- | en_US |
| dc.contributor.other | Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. | en_US |
| dc.date.accessioned | 2005-09-26T20:27:55Z | |
| dc.date.available | 2005-09-26T20:27:55Z | |
| dc.date.copyright | 2004 | en_US |
| dc.date.issued | 2004 | en_US |
| dc.identifier.uri | http://hdl.handle.net/1721.1/28438 | |
| dc.description | Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004. | en_US |
| dc.description | Includes bibliographical references (leaves 46-47). | en_US |
| dc.description.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. The algorithms were initially written in MATLAB and later converted into C++ for incorporation into a prototype, automated system. | en_US |
| dc.description.statementofresponsibility | by Manway Michael Liu. | en_US |
| dc.format.extent | 47 leaves | en_US |
| dc.format.extent | 2052335 bytes | |
| dc.format.extent | 2055723 bytes | |
| dc.format.mimetype | application/pdf | |
| dc.format.mimetype | application/pdf | |
| dc.language.iso | en_US | |
| dc.publisher | Massachusetts Institute of Technology | en_US |
| dc.rights | M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. | en_US |
| dc.rights.uri | http://dspace.mit.edu/handle/1721.1/7582 | |
| dc.subject | Electrical Engineering and Computer Science. | en_US |
| dc.title | Algorithmic advances towards a fully automated DNA genotyping system | en_US |
| dc.type | Thesis | en_US |
| dc.description.degree | M.Eng. | en_US |
| dc.contributor.department | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science | |
| dc.identifier.oclc | 57003244 | en_US |
