Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Are amino acids counts in yeast ORFs negative binomial?

Are amino acids counts in yeast ORFs negative binomial? The genetic code of living organisms is inscribed into so called Open Reading Frames (ORFs) positioned in chromosomes. The code uses 20 amino acids as building blocks for the inscribed information. We show that the number of appearances of a given amino acid in ORFs on a yeast chromosome may be described in a highly satisfactory manner by the Negative Binomial (NB) distribution. The fit is surprisingly good. We show the results for ORFs found in four yeast chromosomes, namely no. 4, 7, 11 and 13. The negative binomial fit is shown (1) graphically; (2) considering the Kolmogorov statistic; (3) performing a chi-square test and (4) using simulated samples. The applicability of the Kolmogorov test to the analysed data is discussed. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Biometrics Inderscience Publishers

Are amino acids counts in yeast ORFs negative binomial?

Loading next page...
 
/lp/inderscience-publishers/are-amino-acids-counts-in-yeast-orfs-negative-binomial-arI2DL0UAx

References (19)

Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd. All rights reserved
ISSN
1755-8301
eISSN
1755-831X
DOI
10.1504/IJBM.2009.024274
Publisher site
See Article on Publisher Site

Abstract

The genetic code of living organisms is inscribed into so called Open Reading Frames (ORFs) positioned in chromosomes. The code uses 20 amino acids as building blocks for the inscribed information. We show that the number of appearances of a given amino acid in ORFs on a yeast chromosome may be described in a highly satisfactory manner by the Negative Binomial (NB) distribution. The fit is surprisingly good. We show the results for ORFs found in four yeast chromosomes, namely no. 4, 7, 11 and 13. The negative binomial fit is shown (1) graphically; (2) considering the Kolmogorov statistic; (3) performing a chi-square test and (4) using simulated samples. The applicability of the Kolmogorov test to the analysed data is discussed.

Journal

International Journal of BiometricsInderscience Publishers

Published: Jan 1, 2009

There are no references for this article.