With the development of the next-generation sequencing technology, the influence of rare variants on complex disease has gathered increasing attention. In this paper, we propose a clustering-based approach, the clustering sum test, to test the effects of rare variants association by using the simulated data provided by the Genetic Analysis Workshop 19 with an unbalanced case-control ratio. The ...

sensor networks generally consist of a very great number of sensor nodes which will be spread into a vast environment and aggregate data out of it. the sensor nodes are afflicted with some limitations as follows memory, reception, communication as well as calculation capability, and battery power. the transmission of a great amount of extra data increases data transmission and proportionally in...

one of the most important issues in urban planning is developing sustainable public transportation. the basic condition for this purpose is analyzing current condition especially based on data. data mining is a set of new techniques that are beyond statistical data analyzing. clustering techniques is a subset of it that one of it’s techniques used for analyzing passengers’ trip. the result of t...

Energy consumption is considered as a critical issue in wireless sensor networks (WSNs). Batteries of sensor nodes have limited power supply which in turn limits services and applications that can be supported by them. An efcient solution to improve energy consumption and even trafc in WSNs is Data Aggregation (DA) that can reduce the number of transmissions. Two main challenges for DA are: (i)...

Graphs have so many applications in real world problems. When we deal with huge volume of data, analyzing data is difficult or sometimes impossible. In big data problems, clustering data is a useful tool for data analysis. Singular value decomposition(SVD) is one of the best algorithms for clustering graph but we do not have any choice to select the number of clusters and the number of members ...

Kernel density smoothing techniques have been used in classification or supervised learning of gene expression profile (GEP) data, but their applications to clustering or unsupervised learning of those data have not been explored and assessed. Here we report a kernel density clustering method for analysing GEP data and compare its performance with the three most widely-used clustering methods: ...

OBJECTIVES To evaluate brain activation using functional magnetic resonance imaging (fMRI) and specifically, activation changes across time associated with practice-related cognitive control during eye movement tasks. EXPERIMENTAL DESIGN Participants were engaged in antisaccade performance (generating a glance away from a cue) while fMR images were acquired during two separate test sessions: ...