Coffee Transcriptome Visualization Based on Functional Relationships among Gene Annotations
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 Interproscan 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 RNAseq. 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.
KeywordsGene ontology vector visualization metadata relationship transcription network
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