Conference proceeding
More powerful discriminants for classifying phylogenetic signals in dinucleotide frequencies
2008 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING, VOLS 1-12, pp 605-608
01 Jan 2008
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Abstract
Microbial DNA fragments are classified according to species using compositional features and "genomic signatures" the oldest of which is the dinucleotide relative abundance profile defined by Karlin et al. More informative features, including higher order signatures, have demonstrated greater species-specificity in comparison to the baseline established by the dinucleotide signature using "delta-distance" to assess dissimilarity; but lack of standard methods has precluded rigorous comparison. We describe a new method for classifier evaluation that reduces any number of pair-wise inter-genomic comparisons to a single performance measure. To illustrate the method, we compare delta-distance to quadratic and linear discriminants prescribed by elementary pattern recognition theory, and find that the quadratic form is significantly more powerful.
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Details
- Title
- More powerful discriminants for classifying phylogenetic signals in dinucleotide frequencies
- Creators
- Robert H. Baran - Korea UniversityChangwon Jeon - Korea UniversityDavid K. Han - United States Naval AcademyHanseok Ko - Korea University
- Publication Details
- 2008 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING, VOLS 1-12, pp 605-608
- Series
- International Conference on Acoustics Speech and Signal Processing ICASSP
- Publisher
- IEEE
- Number of pages
- 2
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Web of Science ID
- WOS:000257456700152
- Scopus ID
- 2-s2.0-51449100134
- Other Identifier
- 991021931083604721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Acoustics
- Computer Science, Artificial Intelligence
- Computer Science, Cybernetics
- Engineering, Biomedical
- Engineering, Electrical & Electronic
- Imaging Science & Photographic Technology
- Mathematical & Computational Biology
- Radiology, Nuclear Medicine & Medical Imaging
- Telecommunications