Investigating long range correlation in DNA sequences using significance tests of conditional mutual information

2014 ◽  
Vol 53 ◽  
pp. 32-42 ◽  
Author(s):  
Maria Papapetrou ◽  
Dimitris Kugiumtzis
Keyword(s):  
Mutual Information ◽  
Long Range ◽  
Dna Sequences ◽  
Conditional Mutual Information ◽  
Significance Tests ◽  
Range Correlation

Long-range correlation properties of coding and noncoding DNA sequences: GenBank analysis

1995 ◽  
Vol 51 (5) ◽  
pp. 5084-5091 ◽  
Author(s):  
S. V. Buldyrev ◽  
A. L. Goldberger ◽  
S. Havlin ◽  
R. N. Mantegna ◽  
M. E. Matsa ◽  
...  
Keyword(s):  
Long Range ◽  
Dna Sequences ◽  
Noncoding Dna ◽  
Range Correlation ◽  
Correlation Properties

scholarly journals Statistical Analysis of Genomic Information : Long-Range Correlation in DNA Sequences

2000 ◽  
Vol 40 (supplement) ◽  
pp. S68 ◽  
Author(s):  
A. Fukushima ◽  
M. Kinouchi ◽  
Y. Kudo ◽  
S. Kanaya
Keyword(s):  
Statistical Analysis ◽  
Long Range ◽  
Dna Sequences ◽  
Genomic Information ◽  
Range Correlation

Long range correlation and possible electron conduction through DNA sequences

2008 ◽  
Vol 387 (21) ◽  
pp. 5159-5168 ◽  
Author(s):  
Sheng-Cheng Wang ◽  
Ping-Cheng Li ◽  
Hsen-Che Tseng
Keyword(s):  
Long Range ◽  
Dna Sequences ◽  
Electron Conduction ◽  
Range Correlation

scholarly journals MUTUAL INFORMATION FOR EXAMINING CORRELATIONS IN DNA

2004 ◽  
Vol 04 (02) ◽  
pp. L237-L246 ◽  
Author(s):  
M. J. BERRYMAN ◽  
A. ALLISON ◽  
D. ABBOTT
Keyword(s):  
Mutual Information ◽  
Long Range ◽  
Dna Sequences ◽  
In Silico ◽  
Fractal Measure ◽  
Long Range Correlations

This paper examines two methods for finding whether long-range correlations exist in DNA: a fractal measure and a mutual information technique. We evaluate the performance and implications of these methods in detail. In particular we explore their use comparing DNA sequences from a variety of sources. Using software for performing in silico mutations, we also consider evolutionary events leading to long range correlations and analyse these correlations using the techniques presented. Comparisons are made between these virtual sequences, randomly generated sequences, and real sequences. We also explore correlations in chromosomes from different species.

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