Abstract:
A novel approach is presented for the detection and localization of changing periodicities in symbolic sequences. Various symbolic sequences like DNA can be modelled as s...Show MoreMetadata
Abstract:
A novel approach is presented for the detection and localization of changing periodicities in symbolic sequences. Various symbolic sequences like DNA can be modelled as stochastic processes that exhibit time-varying cyclostation- arity. The coding regions of the DNA, for instance, exhibit statistical periodicity with period three. The complexity-regularized maximum-likelihood estimates are developed in this paper for the statistical period of symbolic sequences. The changing periodicities along the sequence are discovered by using sliding windows. A cumulative sum test is also presented to detect the change points. The formulation in this paper avoids any kind of numerical mapping for the symbolic DNA sequences and does not impose any algebraic structure.
Date of Conference: 31 March 2008 - 04 April 2008
Date Added to IEEE Xplore: 12 May 2008
ISBN Information:
ISSN Information:
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- IEEE Keywords
- Index Terms
- Symbol Sequence ,
- DNA Sequencing ,
- Maximum Likelihood Estimation ,
- Change Point ,
- Algebraic Structure ,
- Source Of Information ,
- Random Variables ,
- Partial Sequences ,
- Window Size ,
- Probability Mass Function ,
- Simulated Sequences ,
- Mathematical Structure ,
- Minimum Description Length ,
- Successive Windows
- Author Keywords
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Symbol Sequence ,
- DNA Sequencing ,
- Maximum Likelihood Estimation ,
- Change Point ,
- Algebraic Structure ,
- Source Of Information ,
- Random Variables ,
- Partial Sequences ,
- Window Size ,
- Probability Mass Function ,
- Simulated Sequences ,
- Mathematical Structure ,
- Minimum Description Length ,
- Successive Windows
- Author Keywords