When we performed quantitative PCR (qPCR) experiments for 90 randomly selected chromosomal locations, which consist of locations both with and without CNV segments, overall 93.3% (84/90) were consistent in the results of CNV presence or absence between microarray and qPCR (Supplementary Material, Table S1).
Since raw SMLM data consist of locations of individual fluorophores, object-based co-localization methods (Bolte and Cordelieres 2006) can be used without any prior data processing.
The raw location data set consists of location point tuples (l = [mathit{ID}, mathit{latitude}, mathit{longitude}, mathit{source}, mathit{accuracy}, mathit{time}]), where for each tuple l the study participant ID, the latitude, the longitude, the information source (i.e. GPS, Network), the accuracy of the location point in meters, and the timestamp are recorded, respectively.
The dataset consists of locations and service usages.
The proposed scheme consists of location-centric hybrid system architecture for the coordinated processing among proximate devices.
Our benchmarks consisted of locations for which there are field data collected for monitoring and evaluation purposes for several time periods.
A solution to the model consists of locations and technologies for transfer stations, material recovery facilities, incinerators and sanitary landfills, as well as the waste flow between these locations.
ENFA compares the eco-geographical predictor distribution for a presence data set consisting of locations where the species has been detected with the predictor distribution of the whole area (Hirzel et al. 2001).
Our spatial point pattern consisted of locations with at least one cholera case and houses without cases.
This second initialization set consisted of locations defined from meta-analysis of task-evoked data and thus may constitute a set of more rational starting points for capturing functional area relationships.
