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Classification Methodology for Bioinformatics Data Analysis

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Abstract

The paper presents a methodology for bioinformatics data analysis. First, it describes the use of data analysis in bioinformatics—data preprocessing approaches, missing data processing approaches, data dimensionality reduction and classification algorithms. Then, the next section determines the most appropriate data analysis methods, which should be used in bioinformatics data analysis methodology to solve diagnostic classification task. The methodology was practically approbated in experiments using WEKA software and real-world bioinformatics data sets. This allowed determination of specific method realizations that show the best classification result; all intermediate results are recorded. Finally, the best preprocessing method sequence for this methodology is determined.

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Authors and Affiliations

  1. Riga Technical University, LV-1658, Riga, Latvia

    M. Gasparovica-Asīte & L. Aleksejeva

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  1. M. Gasparovica-Asīte
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  2. L. Aleksejeva
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Correspondence to M. Gasparovica-Asīte or L. Aleksejeva.

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Gasparovica-Asīte, M., Aleksejeva, L. Classification Methodology for Bioinformatics Data Analysis. Aut. Control Comp. Sci. 53, 28–38 (2019). https://doi.org/10.3103/S0146411619010073

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