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A Simplified Complex Network-Based Approach to mRNA and ncRNA Transcript Classification

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Advances in Bioinformatics and Computational Biology (BSB 2020)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 12558))

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Abstract

Bioinformatics is an interdisciplinary area that presents several important computational challenges. These challenges are usually related to the large volume of biological data generated and that needs to be analyzed for information discovery. An important challenge is the need to distinguish mRNAs and ncRNAs in an efficient and assertive way. The correct identification of these transcripts is due to the existence of thousands of non-coding transcripts, whose function and meaning are not known, as well as the challenge to understand the expression and regulation of genetic information. On the other hand, the complex network theory has been successfully applied in many real-world problems in different contexts. Therefore, this work presents a simplified and efficient complex network-based approach for the classification of mRNA and ncRNA sequences. Experiments were performed to evaluate the proposed approach considering a dataset with six different species and with important methods in the literature such as CPC, CPC2 and PLEK. The results indicated the assertiveness of the proposed approach achieving average accuracy rates higher than 98% in the classification of mRNA and ncRNA considering all compared species. Besides, the proposed approach presents fewer variations on its results when compared to competitor methods, indicating its robustness and suitability for the classification of transcripts.

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Acknowledgments

This work was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES), Conselho Nacional de Desenvolvimento Científico e Tecnológico - CNPq (Grant number 406099 /2016-2) and the Fundação Araucária e do Governo do Estado do Paraná/SETI (Grant number 035/2019).

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Authors and Affiliations

  1. Departamento Acadêmico de Computação (DACOM), Universidade Tecnológica Federal do Paraná (UTFPR) Câmpus Cornélio Procópio, Av. Alberto Carazzai, 1640, Cornélio Procópio, PR, CEP 86300-000, Brazil

    Murilo Montanini Breve & Fabrício Martins Lopes

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  1. Murilo Montanini Breve
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  2. Fabrício Martins Lopes
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Correspondence to Fabrício Martins Lopes .

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Editors and Affiliations

  1. University of São Paulo, São Paulo, Brazil

    João C. Setubal

  2. Instituto Federal de Goiás, Formosa, Goiás, Brazil

    Waldeyr Mendes Silva

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Breve, M.M., Lopes, F.M. (2020). A Simplified Complex Network-Based Approach to mRNA and ncRNA Transcript Classification. In: Setubal, J.C., Silva, W.M. (eds) Advances in Bioinformatics and Computational Biology. BSB 2020. Lecture Notes in Computer Science(), vol 12558. Springer, Cham. https://doi.org/10.1007/978-3-030-65775-8_18

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  • DOI: https://doi.org/10.1007/978-3-030-65775-8_18

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