Motivation:It is expected that the difference in the thermal stability of mesophilic and thermophilic proteins arises, in part at least, from the differences in their molecular structures and amino acid compositions. Existing machine learning approaches for supervised classification of proteins rely on the features derived from the structural networks and the amino acid sequences. However, the network features used leave out several important network centrality values, the statistic used is a simple average and the sequence features used are hand-picked leading to an accuracy of 90%. Results: We show that discriminating sub-sequences of the amino acid sequences can significantly improve classification accuracy compared to the existing approaches of counting amino acids, di-peptide or even tri-peptide bonds. We identify notions of network centrality, specifically that depends on the distances between Cα atoms, that appears to correlate better with thermal stability compared to the existing network features. We also show how to generate better statistics from the node-and edge-wise centrality values that more accurately captures the variations in their values for different types of proteins. These improved feature selection techniques make it possible to classify between thermophilic and mesophilic proteins with 96% accuracy and 99% area under ROC.
This study highlights the role of satisfaction for building e-marketing leadership and empirically explores the differences in the customer satisfaction of online buyers. The study tries to discern how segmenting the customer based on marital status may help the online marketers for effective leadership and competitive advantage in the modern globalized market. An online survey instrument was administered to a sample of 200 online buyers from a northern city of India. The respondents were contacted both personally as well as through the emails, social media like Facebook, Whatsapp etc. The instrument comprised items related to online satisfaction along with few variables of demographic variables. The study employed purposive sampling which is appropriate for exploratory type of studies. The findings indicate that online shoppers are moderately satisfied from e-retailers. It is suggested that e-retailers must address issues of customers vibrantly so that customers become highly satisfied which ultimately leads to e-marketing leadership.
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