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ShareScore release 0.9.0
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266 results for “data partitioning”
Data from: Environmental variation partitioned into separate heritable components
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CpG island mediated linear and spatial gene partitioning (other data sets)
GEO Series GSE80795. Homo sapiens; Mus musculus. 0 samples. Type: Third-party reanalysis; Other; Methylation profiling by high throughput sequencing.
Open source data for microservice partitioning
<p>Open-source datasets for microservice partitioning.</p>
OPTIMAL PARTITIONS OF DATA IN HIGHER DIMENSIONS
OPTIMAL PARTITIONS OF DATA IN HIGHER DIMENSIONS BRADLEY W. JACKSON*, JEFFREY D. SCARGLE**, AND CHRIS CUSANZA, DAVID BARNES, DENNIS KANYGIN, RUSSELL SARMIENTO, SOWMYA SUBRAMANIAM, TZU-WANG CHUANG*** Abstract. Consider piece-wise constant approximations to a function of several parameters, and the problem of finding the best such approximation from measurements at a set of points in the parameter space. We find good approximate solutions to this problem in two steps: (1) partition the parameter space into cells, one for each of the N data points, and (2) collect these cells into blocks, such that within each block the function is constant to within measurement uncertainty. We describe a branch-and-bound algorithm for finding the optimal partition into connected blocks, as well as an O(N2) dynamic programming algorithm that finds the exact global optimum over this exponentially large search space, in a data space of any dimension. This second solution relaxes the connectivity constraint, and requires additivity and convexity conditions on the block fitness function, but in practice none of these items cause problems. From the wide variety of intelligent data understanding applications (including cluster analysis, classification, and anomaly detection) we demonstrate two: partitioning of the State of California (2D) and the Universe (3D).
Distributed Anomaly Detection using 1-class SVM for Vertically Partitioned Data
There has been a tremendous increase in the volume of sensor data collected over the last decade for different monitoring tasks. For example, petabytes of earth science data are collected from modern satellites, in-situ sensors and different climate models. Similarly, huge amount of flight operational data is downloaded for different commercial airlines. These different types of datasets need to be analyzed for finding outliers. Information extraction from such rich data sources using advanced data mining methodologies is a challenging task not only due to the massive volume of data, but also because these datasets are physically stored at different geographical locations with only a subset of features available at any location. Moving these petabytes of data to a single location may waste a lot of bandwidth. To solve this problem, in this paper, we present a novel algorithm which can identify outliers in the entire data without moving all the data to a single location. The method we propose only centralizes a very small sample from the different data subsets at different locations. We analytically prove and experimentally verify that the algorithm offers high accuracy compared to complete centralization with only a fraction of the communication cost. We show that our algorithm is highly relevant to both earth sciences and aeronautics by describing applications in these domains. The performance of the algorithm is demonstrated on two large publicly available datasets: (1) the NASA MODIS satellite images and (2) a simulated aviation dataset generated by the ‘Commercial Modular Aero-Propulsion System Simulation’ (CMAPSS).
Partitioning RNAs by length improves transcriptome reconstruction from short-read RNA-seq data
GEO Series GSE158985. Mus musculus. 19 samples. Type: Expression profiling by high throughput sequencing.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.