Wan, Cen and Lees, J. and Minneci, F. and Orengo, C. and Jones, D. (2017) Analysis of temporal transcription expression profiles reveal links between protein function and developmental stages of Drosophila melanogaster. PLoS Computational Biology , ISSN 1553-7358.
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Abstract
Accurate gene or protein function prediction is a key challenge in the post-genome era. Most current methods perform well on molecular function prediction, but struggle to provide useful annotations relating to biological process functions due to the limited power of sequence-based features in that functional domain. In this work, we systematically evaluate the predictive power of temporal transcription expression profiles for protein function prediction in Drosophila melanogaster. Our results show significantly better performance on predicting protein function when transcription expression profile-based features are integrated with sequence-derived features, compared with the sequence-derived features alone. We also observe that the combination of expression-based and sequence-based features leads to further improvement of accuracy on predicting all three domains of gene function. Based on the optimal feature combinations, we then propose a novel multi-classifier-based function prediction method for Drosophila melanogaster proteins, FFPred-fly+. Interpreting our machine learning models also allows us to identify some of the underlying links between biological processes and developmental stages of Drosophila melanogaster.
Metadata
Item Type: | Article |
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School: | Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences |
Research Centres and Institutes: | Bioinformatics, Bloomsbury Centre for (Closed) |
Depositing User: | Cen Wan |
Date Deposited: | 31 Jan 2020 09:16 |
Last Modified: | 09 Aug 2023 12:47 |
URI: | https://eprints.bbk.ac.uk/id/eprint/30712 |
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