NDLI: Significantly lower entropy estimates for natural DNA sequences

Content Provider	IEEE Xplore Digital Library
Author	Loewenstern, D. Yianilos, P.N.
Copyright Year	1997
Description	Author affiliation: Bell Labs., Whippany, NJ, USA (Loewenstern, D.)
Abstract	If DNA were a random string over its alphabet {A,C,G,T}, an optimal code would assign 2 bits to each nucleotide. We imagine DNA to be a highly ordered, purposeful molecule, and might therefore reasonably expect statistical models of its string representation to produce much lower entropy estimates. Surprisingly this has not been the case for many natural DNA sequences, including portions of the human genome. We introduce a new statistical model (compression algorithm), the strongest reported to date, for naturally occurring DNA sequences. Conventional techniques code a nucleotide using only slightly fewer bits (1.90) than one obtains by relying only on the frequency statistics of individual nucleotides (1.95). Our method in some cases increases this gap by more than five-fold (1.66) and may lead to better performance in microbiological pattern recognition applications. One of our main contributions, and the principle source of these improvements, is the formal inclusion of inexact match information in the model. The existence of matches at various distances forms a panel of experts which are then combined into a single prediction. The structure of this combination is novel and its parameters are learned using expectation maximization (EM).
Starting Page	151
Ending Page	160
File Size	629239
Page Count	10
File Format	PDF
ISBN	0818677619
ISSN	10680314
DOI	10.1109/DCC.1997.581998
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1997-03-25
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Entropy DNA Sequences Humans Genomics Bioinformatics Compression algorithms Frequency Statistics Pattern recognition
Content Type	Text
Resource Type	Article
Subject	Computer Networks and Communications

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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