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Coffee Transcriptome Visualization Based on Functional Relationships among Gene Annotations

机译:基于基因注释之间功能关系的咖啡转录组可视化

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Simplified visualization and conformation of gene networks is one of the current bioinformatics challenges when thousands of gene models are being described in an organism genome. Bioinformatics tools such as BLAST and Inter-proscan build connections between sequences and potential biological functions through the search, alignment and annotation based on heuristic comparisons that make use of previous knowledge obtained from other sequences. This work describes the search procedure for functional relationships among a set of selected annotations, chosen by the quality of the sequence comparison as defined by the coverage, the identity and the length of the query, when coffee transcriptome sequences were compared against the reference databases UNIREF 100, Interpro, PDB and PFAM. Term descriptors for molecular biology and biochemistry were used along the wordnet dictionary in order to construct a Resource Description Framework (RDF) that enabled the finding of associations between annotations.Sequence-annotation relationships were graphically represented through a total of 6845 oriented vectors. A large gene network connecting transcripts by way of relational concepts was created with over 700 non-redundant annotations, that remain to be validated with biological activity data such as microarrays and RNA-seq. This tool development facilitates the visualization of complex and abundant transcripotome data, opens the possibility to complement genomic information for data mining purposes and generates new knowledge in metabolic pathways analysis.
机译:当在生物基因组中描述成千上万的基因模型时,基因网络的简化可视化和构象是当前生物信息学的挑战之一。 BLAST和Inter-proscan等生物信息学工具可基于启发式比较,通过搜索,比对和注释,在序列与潜在生物学功能之间建立连接,这些启发式比较利用了从其他序列获得的先前知识。这项工作描述了一组选定注释之间的功能关系的搜索过程,该注释是通过将咖啡转录组序列与参考数据库UNIREF进行比较时,通过序列比较的质量来选择的,序列比较的质量由覆盖范围,标识和查询的长度定义100,Interpro,PDB和PFAM。沿词网词典使用分子生物学和生物化学的术语描述符来构建资源描述框架(RDF),从而能够找到注释之间的关联。序列注释关系通过总共6845个定向向量以图形方式表示。创建了一个大型基因网络,通过相关概念将转录本连接起来,并带有700多个非冗余注释,这些注释仍需通过生物活性数据(如微阵列和RNA-seq)进行验证。该工具的开发促进了复杂且丰富的转录组数据的可视化,为基因挖掘提供了补充基因组信息的可能性,并在代谢途径分析中产生了新的知识。

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