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The distributed nature of biological knowledge poses a major challenge to the interpretation of genome-scale datasets, including those derived from microarray and proteomic studies. This report describes DAVID, a web-accessible program that integrates functional genomic annotations with intuitive graphical summaries. Lists of gene or protein identifiers are(More)
Node mobility and end-to-end disconnections in Delay Tolerant Networks (DTNs) greatly impair the effectiveness of data dissemination. Although social-based approaches can be used to address the problem, most existing solutions only focus on forwarding data to a single destination. In this paper, we are the first to study multicast in DTNs from the social(More)
It has been reported that increasingly microRNAs are associated with diseases. However, the patterns among the microRNA-disease associations remain largely unclear. In this study, in order to dissect the patterns of microRNA-disease associations, we performed a comprehensive analysis to the human microRNA-disease association data, which is manually(More)
Several lines of evidence have implicated the existence of the brain's default network during passive or undirected mental states. Nevertheless, results on the emergence of the default network in very young pediatric subjects are lacking. Using resting functional magnetic resonance imaging in healthy pediatric subjects between 2 weeks and 2 years of age, we(More)
Tanshinones are abietane-type norditerpenoid quinone natural products that are the bioactive components of the Chinese medicinal herb Salvia miltiorrhiza Bunge. The initial results from a functional genomics-based investigation of tanshinone biosynthesis, specifically the functional identification of the relevant diterpene synthases from S. miltiorrhiza,(More)
AUC is an important performance measure and many algorithms have been devoted to AUC optimization, mostly by minimizing a surrogate convex loss on a training data set. In this work, we focus on one-pass AUC optimization that requires going through the training data only once without storing the entire training dataset, where conventional online learning(More)
In multi-instance multi-label learning (MIML), one object is represented by multiple instances and simultaneously associated with multiple labels. Existing MIML approaches have been found useful in many applications; however, most of them can only handle moderatesized data. To efficiently handle large data sets, we propose the MIMLfast approach, which first(More)
Recent reports demonstrate the anti-correlated behaviors between the default (DF) and the dorsal attention (DA) networks. We aimed to investigate the roles of the frontal parietal control (FPC) network in regulating the two anti-correlated networks through three experimental conditions, including resting, continuous self-paced/attended sequential finger(More)
Chemokines provide signals for activation and recruitment of effector cells into sites of inflammation, acting via specific G protein-coupled receptors. However, in vitro data demonstrating the presence of multiple ligands for a given chemokine receptor, and often multiple receptors for a given chemokine, have led to concerns of biologic redundancy. Here we(More)