V. V. Khrustalev, E. V. Barkovsky, V. Kolodkina, T. Khrustaleva
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引用次数: 4
Abstract
In this work we described a bacterial open reading frame with two different directions of nucleotide usage biases in its two parts. The level of GC-content in third codon positions (3GC) is equal to 40.17 ± 0.22% during the most of the length of Corynebacterium diphtheriae spaC gene. However, in the 3'-end of the same gene (from codon #1600 to codon #1873) 3GC level is equal to 64.61 ± 0.91%. Using original methodology ('VVTAK Sliding window' and 'VVTAK VarInvar') we approved that there is an ongoing mutational AT-pressure during the most of the length of spaC gene (up to codon #1599), and there is an ongoing mutational G-pressure in the 3′-end of spaC. Intragenic promoters predicted by three different methods may be the cause of the differences in preferable types of nucleotide mutations in spaC parts because of their autonomous transcription.
期刊介绍:
Bioinformatics is an interdisciplinary research field that combines biology, computer science, mathematics and statistics into a broad-based field that will have profound impacts on all fields of biology. The emphasis of IJBRA is on basic bioinformatics research methods, tool development, performance evaluation and their applications in biology. IJBRA addresses the most innovative developments, research issues and solutions in bioinformatics and computational biology and their applications. Topics covered include Databases, bio-grid, system biology Biomedical image processing, modelling and simulation Bio-ontology and data mining, DNA assembly, clustering, mapping Computational genomics/proteomics Silico technology: computational intelligence, high performance computing E-health, telemedicine Gene expression, microarrays, identification, annotation Genetic algorithms, fuzzy logic, neural networks, data visualisation Hidden Markov models, machine learning, support vector machines Molecular evolution, phylogeny, modelling, simulation, sequence analysis Parallel algorithms/architectures, computational structural biology Phylogeny reconstruction algorithms, physiome, protein structure prediction Sequence assembly, search, alignment Signalling/computational biomedical data engineering Simulated annealing, statistical analysis, stochastic grammars.