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Titlebook: Computational Science – ICCS 2019; 19th International C João M. F. Rodrigues,Pedro J. S. Cardoso,Peter M.A Conference proceedings 2019 Spri

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https://doi.org/10.1007/978-981-16-6734-3 every single mutation we used to compose our set of mutation operators. Moreover, a population diversity metric is used to analyze the behavior of each one of them. The proposed method was tested with ten protein sequences with different folding patterns. Results obtained showed that the self-adapt
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Godwell Nhamo,Muchaiteyi Togo,Kaitano Dubeork aims to open a new direction for learning from imbalanced data, by investigating an interplay between the oversampling and cost-sensitive approaches. We show that there is a direct relationship between the misclassification cost imposed on the minority class and the oversampling ratios that aim
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Mavis Thokozile Macheka,Gift Wasambo Kayiralso identify non-signature malware. Comprehensive experimental results show that our proposed method performs better than the state-of-art methods for malicious behaviours detection relying on low-level features.
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Comparing Deep and Machine Learning Approaches in Bioinformatics: A miRNA-Target Prediction Case Stuthree different machine learning models to two different miRNA-mRNA datasets, of predictions from 3 different tools: TargetScan, miRanda, and RNAhybrid. Although an experimental validation of the results is needed to better confirm the predictions, deep learning techniques achieved the best performa
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