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Analysis of temporal transcription expression profiles reveal links between protein function and developmental stages of Drosophila melanogaster

Wan, C; Lees, JG; Minneci, F; Orengo, CA; Jones, DT; (2017) Analysis of temporal transcription expression profiles reveal links between protein function and developmental stages of Drosophila melanogaster. PLoS Computational Biology , 13 (10) , Article e1005791. 10.1371/journal.pcbi.1005791. Green open access

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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.

Type: Article
Title: Analysis of temporal transcription expression profiles reveal links between protein function and developmental stages of Drosophila melanogaster
Open access status: An open access version is available from UCL Discovery
DOI: 10.1371/journal.pcbi.1005791
Publisher version: http://doi.org/10.1371/journal.pcbi.1005791
Language: English
Additional information: © 2017 Wan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Keywords: Science & Technology, Life Sciences & Biomedicine, Biochemical Research Methods, Mathematical & Computational Biology, Biochemistry & Molecular Biology, CENTRAL-NERVOUS-SYSTEM, CELL-MIGRATION, GENE ONTOLOGY, PREDICTION, DATABASE, PATTERN
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences > Structural and Molecular Biology
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10037871
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