Biomedical subjects

Christoforos Nikolaou

Publications and source records attributed to Christoforos Nikolaou.

6 recordsLinked to original sources

PubMed2005

A study on the correlation of nucleotide skews and the positioning of the origin of replication: different modes of replication in bacterial species.

Deviations from Chargaff's 2nd parity rule, according to which A approximately T and G approximately C in single stranded DNA, have been associated with replication as well as with transcription in prokaryotes. Based on observations regarding mainly the transcription-replication co-linearity in a large number of prokaryotic species, we formulate the hypothesis that the replication procedure may follow different modes between genomes throughout which the skews clearly follow different patterns. We draw the conclusion that multiple functional sites of origin of replication may exist in the genomes of most archaea and in some exceptional cases of eubacteria, while in the majority of eubacteria, replication occurs through a single fixed origin.

Archaea↗

PubMed2005

"Word" preference in the genomic text and genome evolution: different modes of n-tuplet usage in coding and noncoding sequences.

Extensive work on n-tuplet occurrence in genomic sequences has revealed the correlation of their usage with sequence origin. Parallel to that, there exist different restrictions in the nucleotide composition of coding and noncoding sequences that may result in distinct modes of usage of n-tuplets. The relatively simple approaches described herein focus on such differences. They are based on simple summation measures of n-tuplet frequencies, computed after filtering the background nucleotide composition. Among the main targets of this work is to draw some conclusions on the qualitative differences in the composition of genomic sequences depending on their functionality. Moreover, an evolutionary model is formulated, including simple forms of ubiquitous events of genome dynamics: genomic fusions, genome shuffling due to transpositions, replication slippage, and point mutations. This model is shown to be able to reproduce all the statistical features of genomic sequences discussed herein.

Base Sequence↗

PubMed2005

Multi-criterial coding sequence prediction. Combination of GeneMark with two novel, coding-character specific quantities.

This work applies two recently formulated quantities, strongly correlated with the coding character of a sequence, as an additional "module" on GeneMark, in a three-criterial method. The difference in the statistical approaches implicated by the methods combined here, is expected to contribute to an efficient assignment of functionality to unannotated genomic sequences. The developed combined algorithm is used to fractionalize a collection of GeneMark-predicted exons into sub-collections of different expectation to be coding. A further modification of the algorithm allows for the assignment of an improved estimation of the probability to be coding, to GeneMark-predicted exons. This is on the basis of a suitable training set of GeneMark-predicted exons of known functionality.

Algorithms↗

PubMed2004

Measuring the coding potential of genomic sequences through a combination of triplet occurrence patterns and RNY preference.

The distribution of n-tuplet frequencies is shown to strongly correlate with functionality when examining a genomic sequence in a reading-frame specific manner. The approach described herein applies a coarse-graining procedure, which is able to reveal aspects of triplet usage that are related to protein coding, while at the same time remaining species independent, based on a simple summation of suitable triplet occurrences measures. These quantities are ratios of simple frequencies to suitable mononucleotide-frequency products promoting the incidence of the RNY motif, preferred in the most widely used codons. A significant distinction of coding and noncoding sequences is achieved.

Algorithms↗

PubMed2003

Mutually symmetric and complementary triplets: differences in their use distinguish systematically between coding and non-coding genomic sequences.

The general property of asymmetry in word use in meaningful texts written in a variety of languages, motivates a quantification of the differences in the use of mutually symmetric triplets in genomic sequences. When this is done in the three reading frames, high values found for one of them are used as indication that the sequence is coding for a protein. Moreover, a similar quantification of the differences in the use of complementary triplets is introduced, again with predictive power of the coding character of a sequence. This method reflects the non-equivalence between sense and anti-sense strand of a coding segment. In both approaches, "linguistic asymmetry" in coding sequences is related to the form of the genetic code and to the bias in codon usage and amino acid use skews.

Algorithms↗

PubMed2002

A study of the middle-scale nucleotide clustering in DNA sequences of various origin and functionality, by means of a method based on a modified standard deviation.

The deviation from randomness in the distribution of nucleotides in genomic sequences is quantified and studied, using a modified standard deviation (MSD). This method implies a "per block" computation of the standard deviation of the nucleotide frequencies of occurrence, using local means (means taken in a neighborhood of each block). This quantity may serve as a scale-dependent measure of the nucleotide clustering. In the present work, the meso-scale of tenths of nucleotides is principally explored, by means of suitably adjusted filter parameters. This length scale is of an order of magnitude not directly affected by the grammar and syntax rules of the protein-coding procedure, remaining shorter than the scale of appearance of large-scale characteristics of the genome. MSD has been found to distinguish systematically between the sequences of different origin and functionality. The most near-random are found to be coding sequences of prokaryotes, while in intronic and intergenic regions of eukaryotic genomes, extended clustering of similar nucleotides is observed. The distributions of MSD values of large collections of sequences are found to be in most cases characteristic of their biological role and origin. Protein- and non-coding, prokaryotic and eukaryotic DNA as well as promoter, rRNA, viral and organelle sequences have been examined. The presented results corroborate a recently proposed model for genome evolution. The method is also applied for an assessment of the annotation of ORFs taken from the complete genome of Saccharomyces cerevisiae.

Animals↗