Classification Methodology for Bioinformatics Data Analysis
Automatic Control and Computer Sciences 2019
Madara Gasparoviča-Asīte, Ludmila Aleksejeva

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.


Atslēgas vārdi
data mining, bioinformatics, preprocessing
Hipersaite
https://link.springer.com/article/10.3103/S0146411619010073

Gasparoviča-Asīte, M., Aleksejeva, L. Classification Methodology for Bioinformatics Data Analysis. Automatic Control and Computer Sciences, 2019, Vol. 53, No. 1, 28.-38.lpp. ISSN 0146-4116.

Publikācijas valoda
English (en)
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