PhD Thesis_JIANGNING SONG (25756702)_With Appendix.pdf (68.1 MB)

Predicting functional sites in proteins using intelligent machine learning and data mining techniques

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thesis
posted on 15.05.2018, 01:09 by JIANGNING SONG
Proteins are fundamental building blocks and play a central role in defining behavior within all biological systems. Identification of functional residues is a crucial step towards understanding the functional mechanisms of proteins. Experimental elucidation of protein function can be prohibitively expensive. To address this, this thesis focuses on developing computational approaches to predict protein functional sites from sequence and/or structural information, by combining feature engineering and modern machine-learning algorithms. Specific techniques are developed for predicting functional sites of different types. These demonstrate the importance of leveraging heterogeneous features. Online servers have been created that make the developed computational techniques publicly available.

History

Campus location

Australia

Principal supervisor

Geoff Ian Webb

Additional supervisor 1

Gholamreza Haffari

Year of Award

2018

Department, School or Centre

Clayton School of IT

Course

Doctor of Philosophy

Degree Type

DOCTORATE

Faculty

Faculty of Information Technology

Exports