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In this paper, a novel center-based nearest neighbor (CNN) classifier is proposed to deal with the pattern classification problems. Unlike nearest feature line (NFL) method, CNN considers the line passing through a sample point with known label and the center of the sample class. This line is called the center-based line (CL). These lines seem to have more(More)
G-protein coupled receptors (GPCRs) are transmembrane proteins which via G-proteins initiate some of the important signaling pathways in a cell and are involved in various physiological processes. Thus, computational prediction and classification of GPCRs can supply significant information for the development of novel drugs in pharmaceutical industry. In(More)
Integral membrane proteins are central to many cellular processes and constitute approximately 50% of potential targets for novel drugs. However, the number of outer membrane proteins (OMPs) present in the public structure database is very limited due to the difficulties in determining structure with experimental methods. Therefore, discriminating OMPs from(More)
To understand the structure and function of a protein, an important task is to know where it occurs in the cell. Thus, a computational method for properly predicting the subcellular location of proteins would be significant in interpreting the original data produced by the large-scale genome sequencing projects. The present work tries to explore an(More)
BACKGROUND To investigate the relationship between obesity and health-related quality of life (HRQL) in a randomly selected Chinese sample. METHODS A total of 3600 residents aged 18-80 years were sampled in five cities of China using a randomized stratified multiple-stage sampling method to receive the interview, with a self-completed questionnaire to(More)
This paper presents a method for recognizing trajectory-based human activities. We use a discriminative latent variable model in our proposed method, which considers that human trajectories are made up of some specific motion regimes, and different activities have different switching patterns among the motion regimes. We model the trajectories using Hidden(More)
Nuclear receptors are involved in multiple cellular signaling pathways that affect and regulate processes such as organ development and maintenance, ion transport, homeostasis, and apoptosis. In this article, an optimal pseudo amino acid composition based on physicochemical characters of amino acids is suggested to represent proteins for predicting the(More)
Trajectory-based human activity recognition aims at understanding human behaviors in video sequences, which is important for intelligent surveillance. Some existing approaches to this problem, e.g., the hierarchical Dirichlet process hidden Markov models (HDP-HMM), have a severe limitation, namely the motions cannot be shared among activities. To overcome(More)
The subcellular location of a protein is closely correlated with it biological function. In this paper, two new pattern classification methods termed as Nearest Feature Line (NFL) and Tunable Nearest Neighbor (TNN) have been introduced to predict the subcellular location of proteins based on their amino acid composition alone. The simulation experiments(More)
BACKGROUND Studies have shown that steroids can improve kidney survival and decrease the risk of proteinuria in patients with Immunoglobulin A nephropathy, but the overall benefit of steroids in the treatment of Immunoglobulin A nephropathy remains controversial. The aim of this study was to evaluate the benefits and risks of steroids for renal survival in(More)