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Near infrared spectroscopy with support vector machine (NIR-SVM) to predict the crude protein (CP) in Alfalfa samples. The R2 of the predicted CP versus the experimental CP of the training data set is 0.983. The R2 of the independent test Data Set is 0.9823. The result suggested that it is feasible to rapidly determine the CP of Alfalfa by NIR data based on SVR.
Protein-protein interactions are important for the prediction of protein functions since two interacting proteins usually have similar functions in a cell. In this work, our aim is to predict protein-protein interactions with a known portion of the interaction network when there are large numbers of protein interactions in the data set. Phylogenetic profiles of proteins form the feature vectors for...
Given the essential role of protein in life processes, computational assignment of protein functions has become one of the most important tasks in the area of bioinformatics. While Gene Ontology (GO) has been widely used in functional annotation, new approaches to address the problem of annotation incompleteness, which can leverage the support of the GO framework, are imminently required. In this...
Protein glycosylation is one of the most common posttranslational modifications (PTMs) with several types. O-GlcNAcylation is an O-linked glycosylation with attachment of beta-N-acetylglucosamine (GlcNAc) to Ser/Thr residues catalyzed by O-GlcNAc transferase (OGA), whose removal is catalyzed by O-GlcNAcase. Unlike mucin-type O-glycosylation, O-GlcNAcylation occurs primarily in nucleocytoplasmic proteins...
We study the single class SVM (SCSVM) classifier performance on the positive data points while considering the impact of SCSVM on negative protein pair data points. We compare the result with the AA classifier (amino acids maximum entropy classifier) [9] to see if a better performance can be achieved for the same data configuration. The conclusion is that although positive classifier is slightly better...
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