Refereed journal article or data article (A1)

Neural Network and Random Forest Models in Protein Function Prediction




List of AuthorsHakala Kai, Kaewphan Suwisa, Björne Jari, Mehryary Farrokh, Moen Hans, Tolvanen Martti, Salakoski Tapio, Ginter Filip

PublisherInstitute of Electrical and Electronics Engineers Inc.

Publication year2022

JournalIEEE/ACM Transactions on Computational Biology and Bioinformatics

Journal name in sourceIEEE/ACM Transactions on Computational Biology and Bioinformatics

Volume number19

Issue number3

Start page1772

End page1781

eISSN1557-9964

DOIhttp://dx.doi.org/10.1109/TCBB.2020.3044230

URLhttps://doi.org/10.1109/TCBB.2020.3044230

Self-archived copy’s web addresshttps://research.utu.fi/converis/portal/detail/Publication/51384893


Abstract

Over the past decade, the demand for automated protein function prediction has increased due to the volume of newly sequenced proteins. In this paper, we address the function prediction task by developing an ensemble system automatically assigning Gene Ontology (GO) terms to the given input protein sequence. We develop an ensemble system which combines the GO predictions made by random forest (RF) and neural network (NN) classifiers. Both RF and NN models rely on features derived from BLAST sequence alignments, taxonomy and protein signature analysis tools. In addition, we report on experiments with a NN model that directly analyzes the amino acid sequence as its sole input, using a convolutional layer. The Swiss-Prot database is used as the training and evaluation data. In the CAFA3 evaluation, which relies on experimental verification of the functional predictions, our submitted ensemble model demonstrates competitive performance ranking among top-10 best-performing systems out of over 100 submitted systems. In this paper, we evaluate and further improve the CAFA3-submitted system. Our machine learning models together with the data pre-processing and feature generation tools are publicly available as an open source software at https://github.com/TurkuNLP/CAFA3.


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Last updated on 2023-27-09 at 11:45