Extraction of Conservative Rules for Translation Initiation Site Prediction using Formal Concept Analysis

Leandro M. Ferreira, Cristiano L. N. Pinto, Sérgio M. Dias, Cristiane N. Nobre, Luis E. Zárate

Abstract

The search for conservative features that define the translation and transcription processes used by cells to interpret and express their genetic information is one of the great challenges in the molecular biology. Each transcribed mRNA sequence has only one part translated into proteins, called \textit{Coding Sequence}. The detection of this region is what motivates the search for conservative characteristics in an mRNA sequence. In eukaryotes, this region usually begins with the first occurrence of the sequence of 3 nucleotides, being Adenine, Thymine and Guanine, the nucleotide set that it is called Translation Initiation Site. One way to look for conservative rules that define this region is to use the formal analysis of concepts that can have implications that indicate a coexistence between the positions of the sequence with the presence of the translation start site. This papers tries to study the use of this technique to extract conservative rules in order to predict the translation initiation site.

References

  1. Carpineto, C., Romano, G., and d'Adamo, P. (1999). Inferring dependencies from relations: a conceptual clustering approach. Computational Intelligence, 15(4):415-441.
  2. Curé, O. C., Maurer, H., and Shah, Nigam H.and LePendu, P. (2015). A formal concept analysis and semantic query expansion cooperation to refine health outcomes of interest. BMC Medical Informatics and Decision Making, 15(1):1-6.
  3. Ganter, B. and Wille, R. (1999). Formal Concept Analysis: Mathematical Foundations. Springer-Verlag, Germany.
  4. Hristoskova, A., Boeva, V., and Tsiporkova, E. (2014). A formal concept analysis approach to consensus clustering of multi-experiment expression data. BMC Bioinformatics, 15(1):1-16.
  5. Kaytoue, M., Kuznetsov, S. O., Napoli, A., and Duplessis, S. (2011). Mining gene expression data with pattern structures in formal concept analysis. Information Sciences, 181(10):1989 - 2001. Special Issue on Information Engineering Applications Based on Lattices.
  6. Kozak, M. (1984). Compilation and analysis of sequences upstream from the translational start site in eukaryotic mrnas. Nucleic Acids Research, 12(2):857-872.
  7. Kuznetsov, S. O. and Poelmans, J. (2013). Knowledge representation and processing with formal concept analysis. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 3(3):200-215.
  8. LIU, H. and WONG, L. (2003). Data mining tools for biological sequences. Journal of Bioinformatics and Computational Biology, 01(01):139-167.
  9. Pinto, C. L. N., Nobre, C. N., and Zárate, L. E. (2017). Transductive learning as an alternative to translation initiation site identification. BMC Bioinformatics, 18(1):81.
  10. Poelmans, J., Elzinga, P., Viaene, S., and Dedene, G. (2010). Formal Concept Analysis in Knowledge Discovery: A Survey. Springer Berlin Heidelberg, Berlin, Heidelberg.
  11. Poelmans, J., Ignatov, D. I., Kuznetsov, S. O., and Dedene, G. (2013). Formal concept analysis in knowledge processing: A survey on applications. Expert Systems with Applications, 40(16):6538 - 6560.
  12. Pruitt, K. D. and Maglott, D. R. (2001). Refseq and locuslink: Ncbi gene-centered resources. Nucleic Acids Research, 29(1):137-140.
  13. Silva, L. M., de Souza Teixeira, F. C., Ortega, J. M., Zárate, L. E., and Nobre, C. N. (2011). Improvement in the prediction of the translation initiation site through balancing methods, inclusion of acquired knowledge and addition of features to sequences of mrna. BMC Genomics, 12(4):1-20.
  14. Tzanis, G., Berberidis, C., and Vlahavas, I. (2007). Mantis: a data mining methodology for effective translation initiation site prediction. In Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE, pages 6343- 6347. IEEE.
  15. Wille, R. (1982). Restructuring lattice theory: an approach based on hierarchies of concepts. I. Rival (Ed.): Ordered Sets, pages 445-470.
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Paper Citation


in Harvard Style

Ferreira L., Pinto C., M. Dias S., Nobre C. and Zárate L. (2017). Extraction of Conservative Rules for Translation Initiation Site Prediction using Formal Concept Analysis . In Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-247-9, pages 265-271. DOI: 10.5220/0006326202650271


in Bibtex Style

@conference{iceis17,
author={Leandro M. Ferreira and Cristiano L. N. Pinto and Sérgio M. Dias and Cristiane N. Nobre and Luis E. Zárate},
title={Extraction of Conservative Rules for Translation Initiation Site Prediction using Formal Concept Analysis},
booktitle={Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2017},
pages={265-271},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006326202650271},
isbn={978-989-758-247-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Extraction of Conservative Rules for Translation Initiation Site Prediction using Formal Concept Analysis
SN - 978-989-758-247-9
AU - Ferreira L.
AU - Pinto C.
AU - M. Dias S.
AU - Nobre C.
AU - Zárate L.
PY - 2017
SP - 265
EP - 271
DO - 10.5220/0006326202650271