植物和动物转座因子的硅分析。

Q4 Health Professions

International Journal of Bioinformatics Research and Applications Pub Date : 2014-01-01 DOI:10.1504/IJBRA.2014.060763

Mo-Li Huang, Songsak Wattanachaisaereekul, Yu-Jun Han, Wanwipa Vongsangnak

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引用次数: 0

摘要

转座因子(te)在真核生物的进化中起着重要的作用。te根据其在基因组中的特性广泛分布。本研究利用生物信息学和芯片突变的方法阐明了陆生动植物TEs的分子特征。我们发现富含gc的I类TEs在动物中占主导地位，而富含at的II类TEs在植物中普遍存在。富含gc的I类TEs似乎是在动物体内进化而来的。相反，保存在富含at的II类te中被认为对宿主防御系统有贡献。

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In silico analysis of plant and animal transposable elements.

Transposable Elements (TEs) play important roles in the evolution of eukaryotic organisms. TEs widely distribute depending on their properties present in the genome. This study elucidated the molecular characteristics of TEs in land plants and animals using bioinformatics and in silico mutational approach. We discovered that the GC-rich class I TEs is the predominant class of TEs in animal, but the AT-rich class II TEs is prevalent in plants. The GC-rich class I TEs appears to be evolved within the animals. On contrary, the preserved in AT-rich in class II TEs is believed to be contributed in host defence systems.

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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.