Title
Coffee Transcriptome Visualization Based on Functional Relationships among Gene Annotations.
Abstract
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 he 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.
Year
DOI
Venue
2012
10.1007/978-3-642-28839-5_32
6TH INTERNATIONAL CONFERENCE ON PRACTICAL APPLICATIONS OF COMPUTATIONAL BIOLOGY & BIOINFORMATICS
Keywords
Field
DocType
Gene ontology,vector visualization,metadata relationship,transcription network
Data mining,Annotation,InterProScan,Computer science,Visualization,Computational biology,Gene regulatory network,WordNet,RDF,Gene Annotation,InterPro
Conference
Volume
ISSN
Citations 
154
1867-5662
0
PageRank 
References 
Authors
0.34
10
6