title: Complexity measures for the evolutionary categorization of organisms.
abstract: Complexity measures are used to compare the genomic characteristics of five organisms belonging to distinct classes spanning the evolutionary tree: higher eukaryotes, amoebae, unicellular eukaryotes and bacteria. The comparisons are undertaken using the full four-letter alphabet and the coarse grained two-letter alphabets AG-CT and AT-CG. We show that the conditional probability matrix for the four-letter and AT-CG alphabet is markedly asymmetric in eukaryotes while it is nearly symmetric in bacterial genomes. Spatial asymmetry is revealed in the four-letter alphabet, signifying that the probability fluxes are nonvanishing and thus the reading sense of a sequence is irreversible for all organisms. Calculations of the block entropy and excess entropy demonstrate that the human genome accommodates better all possible block configurations, especially for long blocks. With respect to point-to-point details and to spatial arrangement of blocks the exit distance distributions from a particular letter demonstrate long distance characteristics in the eukaryotic sequences for all three alphabets, while the bacterial (prokaryotic) genomes deviate indicating short range characteristics. Overall, the conditional probability, the fluxes, the block entropy content and the exit distance distributions can be used as markers, discriminating between eukaryotic and prokaryotic DNA, allowing in many cases to discern details related to finer classes. In all cases the reduction from four letters to two masks some important statistical and spatial properties, with the AT-CG alphabet having higher ability of discrimination than the AG-CT one. In particular, the AT-CG alphabet reduction accentuates the CpG related properties (conditional probabilities w32, long ranged exit distance distribution for A and T nucleotides), but masks sequence asymmetry and irreversibility in all examined organisms.
authors.affiliation: Institute of Nanoscience and Nanotechnology, National Center for Scientific Research "Demokritos", 15310 Athens, Greece. Electronic address: aprovata@chem.demokritos.gr.
authors.forename: A
authors.initials: A
authors.lastname: Provata
authors.affiliation: Institut Royal Météorogique de Belgique, 3 Avenue Circulaire, 1180 Bruxelles, Belgium. Electronic address: cnicolis@oma.be.
authors.forename: C
authors.initials: C
authors.lastname: Nicolis
authors.affiliation: Interdisciplinary Center for Nonlinear Phenomena and Complex Systems, Université Libre de Bruxelles, Campus Plaine, C.P. 231, 1050 Bruxelles, Belgium. Electronic address: gnicolis@ulb.ac.be.
authors.forename: G
authors.initials: G
authors.lastname: Nicolis
mesh_terms: D000656:Amoeba / Q000145:classification / Q000235:genetics*; D001419:Bacteria / Q000145:classification / Q000235:genetics*; D005075:Biological Evolution; D004247:DNA / Q000235:genetics; D019277:Entropy; D056890:Eukaryota / Q000145:classification / Q000235:genetics*; D005057:Eukaryotic Cells / Q000145:classification / Q000378:metabolism*; D005815:Genetic Code; D005819:Genetic Markers; D015894:Genome, Human; D023281:Genomics / Q000706:statistics & numerical data*; D006801:Humans; D010802:Phylogeny; D017422:Sequence Analysis, DNA
chemical_list: D005819:Genetic Markers; D004247:DNA
keywords: Block entropy; Genomic sequences; Irreversibly; Probability fluxes