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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)
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)
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)
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)
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)
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)
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)
G-protein coupled receptors (GPCRs) are involved in various physiological processes. Therefore, classification of amine type GPCRs is important for proper understanding of their functions. Though some effective methods have been developed, it still remains unknown how many and which features are essential for this task. Empirical studies show that feature(More)
Nuclear receptors are involved in multiple cellular signaling pathways that affect and regulate processes. Because of their physiology and pathophysiology significance, classification of nuclear receptors is essential for the proper understanding of their functions. Bhasin and Raghava have shown that the subfamilies of nuclear receptors are closely(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)