通过熵、能量学和谱域方法对DNA/RNA序列进行内聚分析，以评估单个病毒多样性的基因组特征

Q4 Health Professions

International Journal of Bioinformatics Research and Applications Pub Date : 2015-06-01 DOI:10.1504/IJBRA.2015.070113

P. Neelakanta, S. Chatterjee, M. Pavlovic

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引用次数: 0

摘要

在病毒学背景下，一种特定病毒可能以不同形式的血清型流行(如登革热1-4病毒株)，具有共同和独特的基因组特征。发现血清群的这种基因组细节有助于了解与病毒多样性免疫兼容的独特疫苗设计的相关信息。为了对病毒的血清型基因组进行可靠的比较，以确定它们的共同和差异基因组细节，本文提出了一套通过熵、能量和谱域方法并行执行的序列分析。本文给出了登革热病毒血清型DEN1、DEN2、DEN3和DEN4的结果。因此，对所提取的不同特征和共同特征的推论进行了注释和说明，以供可能的疫苗设计应用。

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A cohesive analysis of DNA/RNA sequences via entropy, energetics and spectral-domain methods to assess genomic features across single viral diversity

In virology context, a particular virus may prevail in different forms of serotypes (as in the case of dengue 1-4 viral strains) with common and distinct genomic features. Finding such genomic details of a serogroup is useful in knowing related information for unique vaccine designs compatible for immunity across the viral diversity. For robust comparison of genomes of serovars of a virus in order to decide on their common and differential genomic details, proposed here is a set of sequence analyses exercised side-by-side via entropy, energetic and spectral-domain methods. Results obtained thereof with dengue viral serotypes, namely DEN1, DEN2, DEN3 and DEN4, are presented. Hence, inferences on distinct as well as common features extracted are annotated and indicated for possible vaccine design applications.

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来源期刊

International Journal of Bioinformatics Research and Applications Health Professions-Health Information Management

CiteScore

0.60

自引率

0.00%

发文量

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.