Quokka swMATH ID: 27666 Software Authors: Li, F.; Li, C.; Marquez-Lago, T. T.; Leier, A.; Akutsu, T.; Purcell, A. W.; Ian Smith, A.; Lithgow, T.; Daly, R. J.; Song, J. Description: Quokka: a comprehensive tool for rapid and accurate prediction of kinase family-specific phosphorylation sites in the human proteome. 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/. Homepage: https://www.ncbi.nlm.nih.gov/pubmed/29947803 Related Software: pLoc-mHum; iKcr-PseEns; pLoc-mGneg; pLoc-mAnimal; iRSpot-Pse6NC; iRO-3wPseKNC; iEnhancer-EL; 2L-piRNA; iDNA6mA-PseKNC; iRNA-3typeA; iProt-Sub; iPromoter-2L; iRSpot-EL; iRNAm5C-PseDNC; iRNA-PseColl; pLoc-mEuk; iPTM-mLys; iRSpot-PseDNC; PseKNC; iSuc-PseOpt Cited in: 5 Publications all top 5 Cited by 18 Authors 2 Chou, Kuochen 2 Xiao, Xuan 1 Cheng, Xiang 1 Chong, Kil To 1 Guo, Fei 1 Jia, Jianhua 1 Li, Xiaoyan 1 Lu, Qianzi 1 Pan, Yi 1 Qiu, Wangren 1 Shen, Yinan 1 Su, Dongqing 1 Tang, Jijun 1 Tayara, Hilal 1 Wang, Shiyuan 1 Yang, Lei 1 Zhang, Qi 1 Zuo, Yongchun Cited in 1 Serial 5 Journal of Theoretical Biology Cited in 3 Fields 5 Biology and other natural sciences (92-XX) 4 Computer science (68-XX) 2 Statistics (62-XX) Citations by Year