Multiple polymerase chain reaction (multiple PCR) is one of the most important
techniques in molecular biology. The selection of a suitable set of primers is very important
for multiple PCR experiments. The primer selection problem is to minimize the
number of primers required to amplify a set of DNA sequences. If the minimum set can
be used to amplify the entire target DNA sequences, the experimental costs and time will
be reduced. But the primer selection problem was proved to be an NP-complete problem.
In this thesis, we develop an efficient heuristic algorithm for selecting a set of
primer candidates, each may be able to amplify more than one target sequence. Those
primers are called universal primers. The universal primer finding can be viewed as the
local motif finding in our method.
We modify the score function of the original Gibbs sampler method to find local
motifs. The new score function is added a new parameter, weight parameter. The weight
parameter can guide the Gibbs sampler method to find local motifs with the local view.
Then, the complementary sequences of those local motifs are input into the binary integer
programming. Thus we can reduce the size of the solution space. We also test our method
on some artificial domains and two gene families. All the results show that we get some
improvements on the problem.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0817104-133701 |
| Date | 17 August 2004 |
| Creators | Liu, Wei-ting |
| Contributors | Maw-shang Chang, Chang-biau Yang, Chungnan Lee, Yow-ling Shiue, Bang-ye Wu |
| Publisher | NSYSU |
| Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0817104-133701 |
| Rights | off_campus_withheld, Copyright information available at source archive |
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