Posted Fri, Oct, 04,2013
Published today in Evolutionary Bioinformatics is a new original research article by Chiou-Yi Hor, Chang-Biau Yang, Zih-Jie Yang and Chiou-Ting Tseng. Read more about this paper below:
Title
Prediction of Protein Essentiality by the Support Vector Machine with Statistical Tests
Abstract
Essential proteins include the minimum required set of proteins to support cell life. Identifying essential proteins is important for understanding the cellular processes of an organism. However, identifying essential proteins experimentally is extremely time-consuming and labor-intensive. Alternative methods must be developed to examine essential proteins. There were two goals in this study: identifying the important features and building learning machines for discriminating essential proteins. Data for Saccharomyces cerevisiae and Escherichia coli were used. We first collected information from a variety of sources. We next proposed a modified backward feature selection method and build support vector machines (SVM) predictors based on the selected features. To evaluate the performance, we conducted cross-validations for the originally imbalanced data set and the down-sampling balanced data set. The statistical tests were applied on the performance associated with obtained feature subsets to confirm their significance. In the first data set, our best values of F-measure and Matthews correlation coefficient (MCC) were 0.549 and 0.495 in the imbalanced experiments. For the balanced experiment, the best values of F-measure and MCC were 0.770 and 0.545, respectively. In the second data set, our best values of F-measure and MCC were 0.421 and 0.407 in the imbalanced experiments. For the balanced experiment, the best values of F-measure and MCC were 0.718 and 0.448, respectively. The experimental results show that our selected features are compact and the performance improved. Prediction can also be conducted by users at the following internet address: http://bio2.cse.nsysu.edu.tw/esspredict.aspx.
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Thu 08 Oct, 2015
Published This Week (5th - 9th October)Thu 08 Oct, 2015
Biomarker Insights Paper Endorsed by Editor in ChiefWed 07 Oct, 2015
Interview with Professor Jamie DaviesI thank Libertas for the guidance, speed and encouragement they provided from my first submission until publication. I appreciate the patience and support of everyone I communicated with. Your services are user-friendly. I intend to submit more articles to your journals.
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