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BACKGROUND Existing methods of predicting DNA-binding proteins used valuable features of physicochemical properties to design support vector machine (SVM) based classifiers. Generally, selection of physicochemical properties and determination of their corresponding feature vectors rely mainly on known properties of binding mechanism and experience of(More)
High genetic heterogeneity in the hepatitis C virus (HCV) is the major challenge of the development of an effective vaccine. Existing studies for developing HCV vaccines have mainly focused on T-cell immune response. However, identification of linear B-cell epitopes that can stimulate B-cell response is one of the major tasks of peptide-based vaccine(More)
Protein-protein interactions (PPIs) are involved in various biological processes, and underlying mechanism of the interactions plays a crucial role in therapeutics and protein engineering. Most machine learning approaches have been developed for predicting the binding affinity of protein-protein complexes based on structure and functional information. This(More)
This paper introduces a novel distributed algorithm for performing layout geometry operations usually found in design rule checking, layout verification and/or mask synthesis. Typically, during the mask synthesis flow, a large number of machines are available to the user. Also, as multiple machines/cores become more ubiquitous, even designers using layout(More)
This paper introduces a novel distributed algorithm for performing the layout geometry operations usually found in design rule checking, layout verification, and mask synthesis. A large number of machines are typically available to the user during the mask synthesis flow. As multiple machines or cores become more ubiquitous, even designers using layout(More)
Motivation Numerous ubiquitination sites remain undiscovered because of the limitations of mass spectrometry-based methods. Existing prediction methods use randomly selected non-validated sites as non-ubiquitination sites to train ubiquitination site prediction models. Results We propose an evolutionary screening algorithm (ESA) to select effective(More)
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