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MONO DI and TRI SSRs data extraction storage from 1403 virus genomes with next generation retrieval mechanism

机译:利用新一代检索机制从1403个病毒基因组中提取和存储MONODI和TRI SSRs数据

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摘要

Now a day׳s SSRs occupy the dominant role in different areas of bio-informatics like new virus identification, DNA finger printing, paternity & maternity identification, disease identification, future disease expectations and possibilities etc., Due to their wide applications in various fields and their significance, SSRs have been the area of interest for many researchers. In the SSRs extraction, retrieval algorithms are used; if retrieval algorithms quality is improved then automatically SSRs extraction system will achieve the most relevant results. For this retrieval purpose in this paper a new retrieval mechanism is proposed which will extracted the MONO, DI and TRI patterns. To extract the MONO, DI and TRI patterns using proposed retrieval mechanism in this paper, DNA sequence of 1403 virus genome data sets are considered and different MONO, DI and TRI patterns are searched in the data genome sequence file. The proposed Next Generation Sequencing (NGS) retrieval mechanism extracted the MONO, DI and TRI patterns without missing anything. It is observed that the retrieval mechanism reduces the unnecessary comparisons. Finally the extracted SSRs provide the useful, single view and useful resource to researchers.
机译:如今,SSR在生物信息学的不同领域占据着主导地位,例如新病毒识别,DNA指纹识别,亲子鉴定,疾病识别,未来疾病预期和可能性等,由于它们在各个领域的广泛应用SSR及其重要性,已成为许多研究人员关注的领域。在SSR提取中,使用了检索算法。如果提高检索算法的质量,则自动SSR提取系统将获得最相关的结果。为此,本文提出了一种新的检索机制,该机制将提取MONO,DI和TRI模式。为了利用本文提出的检索机制提取MONO,DI和TRI模式,考虑了1403个病毒基因组数据集的DNA序列,并在数据基因组序列文件中搜索了不同的MONO,DI和TRI模式。拟议的下一代排序(NGS)检索机制提取了MONO,DI和TRI模式,而不会丢失任何内容。可以看出,检索机制减少了不必要的比较。最后,提取的SSR为研究人员提供了有用的,单一的视图和有用的资源。

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