Advertisement

Coffee Transcriptome Visualization Based on Functional Relationships among Gene Annotations

  • Luis F. Castillo
  • Oscar Gómez-Ramírez
  • Narmer Galeano-Vanegas
  • Luis Bertel-Paternina
  • Gustavo Isaza
  • Álvaro Gaitán-Bustamante
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 154)

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 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.

Keywords

Gene ontology vector visualization metadata relationship transcription network 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Li, W., Feng, J., Jiang, T.: ’Workshop: Transcriptome assembly from RNA-Seq data: Objectives, algorithms and challenges. In: 2011 IEEE 1st International Conference on Computational Advances in Bio and Medical Sciences (ICCABS), February 3-5, p. 271 (2011), doi:10.1109/ICCABS.2011.5729925Google Scholar
  2. 2.
    Jing, L., Ng, M.K., Liu, Y.: Construction of Gene Networks With Hybrid Approach From Expression Profile and Gene Ontology. IEEE Transactions on Information Technology in Biomedicine 14(1), 107–118 (2010), doi:10.1109/TITB.2009.2033056CrossRefGoogle Scholar
  3. 3.
    Zheng, H., Azuaje, F., Wang, H.: seGOsa: Software environment for gene ontology-driven similarity assessment. In: 2010 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), December 18-21, pp. 539–542 (2010), doi:10.1109/BIBM.2010.5706624Google Scholar
  4. 4.
    Zhi, D., Keich, U., Pevzner, P., Heber, S., Tang, H.: Correcting Base-Assignment Errors in Repeat Regions of Shotgun Assembly. IEEE/ACM Transactions on Computational Biology and Bioinformatics 4(1), 54–64 (2007), doi:10.1109/TCBB.2007.1005CrossRefGoogle Scholar
  5. 5.
    Essinger, S.D., Rosen, G.L.: The Effect of Sequence Error and Partial Training Data on BLAST Accuracy. In: 2010 IEEE International Conference on BioInformatics and BioEngineering (BIBE), May 31-June 3, pp. 257–262 (2010), doi:10.1109/BIBE.2010.49Google Scholar
  6. 6.
    Langari, Z., Tompa, F.W.: Subject classification in the Oxford English Dictionary. In: Proceedings IEEE International Conference on Data Mining, ICDM 2001, pp. 329–336 (2001), doi:10.1109/ICDM.2001.989536Google Scholar
  7. 7.
    Ngo, V.M., Cao, T.H., Le, T.M.V.: Combining Named Entities with WordNet and Using Query-Oriented Spreading Activation for Semantic Text Search. In: 2010 IEEE RIVF International Conference on Computing and Communication Technologies, Research, Innovation, and Vision for the Future (RIVF), November 1-4, pp. 1–6 (2010), doi:10.1109/RIVF.2010.5633401Google Scholar
  8. 8.
    Abulaish, M.: Relation Characterization Using Ontological Concepts. In: 2011 Eighth International Conference on Information Technology:New Generations (ITNG), April 11-13, pp. 585–590 (2011), doi:10.1109/ITNG.2011.107Google Scholar
  9. 9.
    Matthew, S., Michael, H.: Tools for visually exploring biological networks. Bioinformatics Review 23(20), 2651–2659 (2007), doi:10.1093/bioinformatics/btm401Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Luis F. Castillo
    • 1
    • 2
  • Oscar Gómez-Ramírez
    • 4
  • Narmer Galeano-Vanegas
    • 3
  • Luis Bertel-Paternina
    • 4
  • Gustavo Isaza
    • 1
  • Álvaro Gaitán-Bustamante
    • 3
  1. 1.Departamento de Sistemas e InformáticaUniversidad de CaldasManizalesColombia
  2. 2.Departamento Ing. IndustrialUniversidad Nacional de ColombiaManizalesColombia
  3. 3.Centro Nacional de Investigación del Café- CENICAFÉChinchinaColombia
  4. 4.Grupo Investigación Ing. Del SoftwareUniversidad Autónoma de ManizalesManizalesColombia

Personalised recommendations