Modeling transcription factor motifs

نویسندگان

  • Ben Kao
  • Deyou Cai
  • Peter Nelson
چکیده

Motivation: Generating small models for which there may exist very little training data presents a crucial problem in computational biology, namely the trade-oo between model speciicity and under-tting the data. There are a bevy of superior modeling techniques; however, certain domain speciic problems, such as modeling the regulatory regions in intergenic DNA impose constraints on the modeling process due to the lack of suucient data. A simple alignment method based on local search is compared with two existing systems for nding binding site models of six transcription factors. Results: In a much more connned search space, local search converges quicker than EM and tends to nd slightly better matrices based on information content. On average, alignment qualities based on information content found by local search are slightly better than those found with the other methods.

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تاریخ انتشار 2008