Ensemble of Bidirectional Recurrent Networks and Random Forests for Protein Secondary Structure Prediction

Author(s)

de Oliveira, Gabriel Bianchin ; Pedrini, Helio ; Dias, Zanoni ; Paiva, AC ; Conci, A ; Braz, G ; Almeida, JDS ; Fernandes, LAF

• Document type: Journal article
• Source: PROCEEDINGS OF THE 2020 INTERNATIONAL CONFERENCE ON SYSTEMS, SIGNALS AND IMAGE PROCESSING (IWSSIP), 27TH EDITION; v. N/A, p. 6-pg., 2020-01-01.

Abstract

The prediction of secondary protein structures is one of the classic problems of bioinformatics and has several practical applications. In this work, we present an ensemble of bidirectional recurrent networks (capable of doing long-term analyses of amino acid sequences) with random forests (capable of doing local analyses). The fusion was performed using weights for each of the classifiers and classes, found by searching through genetic algorithms. To evaluate our method, we used the PDB, CB6133 and CB513 datasets. We achieved 73.1%, 59.1% and 55.8% Q8 accuracy on PDB, CB6133 and CB513 proteins, respectively, whereas 81.5% Q3 accuracy on PDB proteins using only amino acid sequence information. In order to compare our results against the literature, we also evaluated our method using amino acid sequence and sequence profile features, achieving 73.4% and 68.9% Q8 accuracy on CB6133 and CB513. Our method yielded good results when using only the amino acid sequence and presents competitive results compared to the literature when using amino acid sequence information and protein sequence similarity. (AU)

• FAPESP's process: 17/16246-0 - Sensitive media analysis through deep learning architectures
• Grantee: Sandra Eliza Fontes de Avila
• Support Opportunities: Regular Research Grants
• FAPESP's process: 19/20875-8 - Chest X-ray image classification using deep neural networks
• Grantee: Vinicius Teixeira de Melo
• Support Opportunities: Scholarships in Brazil - Master
• FAPESP's process: 17/12646-3 - Déjà vu: feature-space-time coherence from heterogeneous data for media integrity analytics and interpretation of events
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• Support Opportunities: Research Projects - Thematic Grants
• FAPESP's process: 15/11937-9 - Investigation of hard problems from the algorithmic and structural stand points
• Grantee: Flávio Keidi Miyazawa
• Support Opportunities: Research Projects - Thematic Grants