Literature DB >> 9640559

Chaos game representation of proteins.

S Basu1, A Pan, C Dutta, J Das.   

Abstract

The present report proposes a new method for the chaos game representation (CGR) of different families of proteins. Using concatenated amino acid sequences of proteins belonging to a particular family and a 12-sided regular polygon, each vertex of which represents a group of amino acid residues leading to conservative substitutions, the method can generate the CGR of the family and allows pictorial representation of the pattern characterizing the family. An estimation of the percentages of points plotted in different segments of the CGR (grid points) allows quantification of the nonrandomness of the CGR patterns generated. The CGRs of different protein families exhibited distinct visually identifiable patterns. This implies that different functional classes of proteins follow specific statistical biases in the distribution of different mono-, di-, tri-, or higher order peptides along their primary sequences. The potential of grid counts as the discriminative and diagnostic signature of a family of proteins is discussed.

Mesh:

Substances:

Year:  1997        PMID: 9640559     DOI: 10.1016/s1093-3263(97)00106-x

Source DB:  PubMed          Journal:  J Mol Graph Model        ISSN: 1093-3263            Impact factor:   2.518


  13 in total

1.  Identifying anticancer peptides by using a generalized chaos game representation.

Authors:  Li Ge; Jiaguo Liu; Yusen Zhang; Matthias Dehmer
Journal:  J Math Biol       Date:  2018-10-05       Impact factor: 2.259

2.  Chaos game representation of human pallidal spike trains.

Authors:  Mahta Rasouli; Golta Rasouli; Fredrick A Lenz; Donald S Borrett; Leo Verhagen; Hon C Kwan
Journal:  J Biol Phys       Date:  2009-08-18       Impact factor: 1.365

3.  Biological sequences as pictures: a generic two dimensional solution for iterated maps.

Authors:  Jonas S Almeida; Susana Vinga
Journal:  BMC Bioinformatics       Date:  2009-03-31       Impact factor: 3.169

4.  Universal sequence map (USM) of arbitrary discrete sequences.

Authors:  Jonas S Almeida; Susana Vinga
Journal:  BMC Bioinformatics       Date:  2002-02-05       Impact factor: 3.169

5.  A high performance prediction of HPV genotypes by Chaos game representation and singular value decomposition.

Authors:  Watcharaporn Tanchotsrinon; Chidchanok Lursinsap; Yong Poovorawan
Journal:  BMC Bioinformatics       Date:  2015-03-05       Impact factor: 3.169

6.  A phylogenetic analysis of the brassicales clade based on an alignment-free sequence comparison method.

Authors:  Klas Hatje; Martin Kollmar
Journal:  Front Plant Sci       Date:  2012-08-29       Impact factor: 5.753

7.  An ensemble method for predicting subnuclear localizations from primary protein structures.

Authors:  Guo Sheng Han; Zu Guo Yu; Vo Anh; Anaththa P D Krishnajith; Yu-Chu Tian
Journal:  PLoS One       Date:  2013-02-27       Impact factor: 3.240

8.  Accurate prediction of nuclear receptors with conjoint triad feature.

Authors:  Hongchu Wang; Xuehai Hu
Journal:  BMC Bioinformatics       Date:  2015-12-03       Impact factor: 3.169

9.  Tetrahedral gray code for visualization of genome information.

Authors:  Natsuhiro Ichinose; Tetsushi Yada; Osamu Gotoh
Journal:  PLoS One       Date:  2014-01-27       Impact factor: 3.240

10.  Additive methods for genomic signatures.

Authors:  Rallis Karamichalis; Lila Kari; Stavros Konstantinidis; Steffen Kopecki; Stephen Solis-Reyes
Journal:  BMC Bioinformatics       Date:  2016-08-22       Impact factor: 3.169

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.