Quokka

A comprehensive tool for rapid and accurate prediction of kinase family-specific phosphorylation sites in the human proteome

Fuyi Li, Chen Li, Tatiana T. Marquez-Lago, Andre Leier, Tatsuya Akutsu, Anthony W. Purcell, A. Ian Smith, Trevor Lithgow, Roger J. Daly, Jiangning Song, Kuo-Chen Chou

Research output: Contribution to journalArticleResearchpeer-review

33 Citations (Scopus)

Abstract

Motivation: Kinase-regulated phosphorylation is a ubiquitous type of post-translational modification (PTM) in both eukaryotic and prokaryotic cells. Phosphorylation plays fundamental roles in many signalling pathways and biological processes, such as protein degradation and protein-protein interactions. Experimental studies have revealed that signalling defects caused by aberrant phosphorylation are highly associated with a variety of human diseases, especially cancers. In light of this, a number of computational methods aiming to accurately predict protein kinase family-specific or kinase-specific phosphorylation sites have been established, thereby facilitating phosphoproteomic data analysis. Results: In this work, we present Quokka, a novel bioinformatics tool that allows users to rapidly and accurately identify human kinase family-regulated phosphorylation sites. Quokka was developed by using a variety of sequence scoring functions combined with an optimized logistic regression algorithm. We evaluated Quokka based on well-prepared up-to-date benchmark and independent test datasets, curated from the Phospho.ELM and UniProt databases, respectively. The independent test demonstrates that Quokka improves the prediction performance compared with state-of-the-art computational tools for phosphorylation prediction. In summary, our tool provides users with high-quality predicted human phosphorylation sites for hypothesis generation and biological validation. Availability and implementation: The Quokka webserver and datasets are freely available at http://quokka.erc.monash.edu/. Supplementary information: Supplementary data are available at Bioinformatics online.

Original languageEnglish
Article numberbty522
Pages (from-to)4223-4231
Number of pages9
JournalBioinformatics
Volume34
Issue number24
DOIs
Publication statusPublished - 15 Dec 2018

Cite this

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title = "Quokka: A comprehensive tool for rapid and accurate prediction of kinase family-specific phosphorylation sites in the human proteome",
abstract = "Motivation: Kinase-regulated phosphorylation is a ubiquitous type of post-translational modification (PTM) in both eukaryotic and prokaryotic cells. Phosphorylation plays fundamental roles in many signalling pathways and biological processes, such as protein degradation and protein-protein interactions. Experimental studies have revealed that signalling defects caused by aberrant phosphorylation are highly associated with a variety of human diseases, especially cancers. In light of this, a number of computational methods aiming to accurately predict protein kinase family-specific or kinase-specific phosphorylation sites have been established, thereby facilitating phosphoproteomic data analysis. Results: In this work, we present Quokka, a novel bioinformatics tool that allows users to rapidly and accurately identify human kinase family-regulated phosphorylation sites. Quokka was developed by using a variety of sequence scoring functions combined with an optimized logistic regression algorithm. We evaluated Quokka based on well-prepared up-to-date benchmark and independent test datasets, curated from the Phospho.ELM and UniProt databases, respectively. The independent test demonstrates that Quokka improves the prediction performance compared with state-of-the-art computational tools for phosphorylation prediction. In summary, our tool provides users with high-quality predicted human phosphorylation sites for hypothesis generation and biological validation. Availability and implementation: The Quokka webserver and datasets are freely available at http://quokka.erc.monash.edu/. Supplementary information: Supplementary data are available at Bioinformatics online.",
author = "Fuyi Li and Chen Li and Marquez-Lago, {Tatiana T.} and Andre Leier and Tatsuya Akutsu and Purcell, {Anthony W.} and Smith, {A. Ian} and Trevor Lithgow and Daly, {Roger J.} and Jiangning Song and Kuo-Chen Chou",
note = "Li, Fuyi Li, Chen Marquez-Lago, Tatiana T Leier, Andre Akutsu, Tatsuya Purcell, Anthony W Smith, A Ian Lithgow, Trevor Daly, Roger J Song, Jiangning Chou, Kuo-Chen eng England Bioinformatics. 2018 Jun 27. pii: 5045914. doi: 10.1093/bioinformatics/bty522.",
year = "2018",
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language = "English",
volume = "34",
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journal = "Bioinformatics",
issn = "1367-4803",
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Quokka : A comprehensive tool for rapid and accurate prediction of kinase family-specific phosphorylation sites in the human proteome. / Li, Fuyi; Li, Chen; Marquez-Lago, Tatiana T.; Leier, Andre; Akutsu, Tatsuya; Purcell, Anthony W.; Smith, A. Ian; Lithgow, Trevor; Daly, Roger J.; Song, Jiangning; Chou, Kuo-Chen.

In: Bioinformatics, Vol. 34, No. 24, bty522, 15.12.2018, p. 4223-4231.

Research output: Contribution to journalArticleResearchpeer-review

TY - JOUR

T1 - Quokka

T2 - A comprehensive tool for rapid and accurate prediction of kinase family-specific phosphorylation sites in the human proteome

AU - Li, Fuyi

AU - Li, Chen

AU - Marquez-Lago, Tatiana T.

AU - Leier, Andre

AU - Akutsu, Tatsuya

AU - Purcell, Anthony W.

AU - Smith, A. Ian

AU - Lithgow, Trevor

AU - Daly, Roger J.

AU - Song, Jiangning

AU - Chou, Kuo-Chen

N1 - Li, Fuyi Li, Chen Marquez-Lago, Tatiana T Leier, Andre Akutsu, Tatsuya Purcell, Anthony W Smith, A Ian Lithgow, Trevor Daly, Roger J Song, Jiangning Chou, Kuo-Chen eng England Bioinformatics. 2018 Jun 27. pii: 5045914. doi: 10.1093/bioinformatics/bty522.

PY - 2018/12/15

Y1 - 2018/12/15

N2 - Motivation: Kinase-regulated phosphorylation is a ubiquitous type of post-translational modification (PTM) in both eukaryotic and prokaryotic cells. Phosphorylation plays fundamental roles in many signalling pathways and biological processes, such as protein degradation and protein-protein interactions. Experimental studies have revealed that signalling defects caused by aberrant phosphorylation are highly associated with a variety of human diseases, especially cancers. In light of this, a number of computational methods aiming to accurately predict protein kinase family-specific or kinase-specific phosphorylation sites have been established, thereby facilitating phosphoproteomic data analysis. Results: In this work, we present Quokka, a novel bioinformatics tool that allows users to rapidly and accurately identify human kinase family-regulated phosphorylation sites. Quokka was developed by using a variety of sequence scoring functions combined with an optimized logistic regression algorithm. We evaluated Quokka based on well-prepared up-to-date benchmark and independent test datasets, curated from the Phospho.ELM and UniProt databases, respectively. The independent test demonstrates that Quokka improves the prediction performance compared with state-of-the-art computational tools for phosphorylation prediction. In summary, our tool provides users with high-quality predicted human phosphorylation sites for hypothesis generation and biological validation. Availability and implementation: The Quokka webserver and datasets are freely available at http://quokka.erc.monash.edu/. Supplementary information: Supplementary data are available at Bioinformatics online.

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DO - 10.1093/bioinformatics/bty522

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