Monash University
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Protein sequential, structural and functional analysis using deep learning

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Version 2 2019-03-01, 02:17
Version 1 2019-02-28, 09:32
posted on 2019-03-01, 02:17 authored by YING XU
This thesis introduces the application of deep learning in protein analysis. Three research questions are proposed in terms of protein sequence representation, deep learning framework design and biological background knowledge incorporation. To address these research questions, the distributed representation of protein sequences is proposed and evaluated in sequence-level, residue-level and biological interaction-level prediction tasks; a deep learning framework is proposed for any protein sequence-based residue-level prediction tasks; two multitask deep learning frameworks are applied to take advantage of the correlation between protein structural properties; and a deep transfer learning framework is proposed to incorporate the hierarchical classification systems in biology.


Campus location


Principal supervisor

Campbell Wilson

Additional supervisor 1

James Whisstock

Additional supervisor 2

Jiangning Song

Additional supervisor 3

Jue (Grace) Xie

Year of Award


Department, School or Centre

Information Technology (Monash University Caulfield)


Doctor of Philosophy

Degree Type



Faculty of Information Technology