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6,452
datasets available to search
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Dataset results
6,452 results for “Application”
Design of a Tobacco Exon Array with application to investigate the differential cadmium accumulation property in two tobacco varieties
GEO Series GSE42319. Nicotiana tabacum. 21 samples. Type: Expression profiling by array.
Barley host response to the direct application of the trichothecene mycotoxin deoxynivalenol
GEO Series GSE33405. Hordeum vulgare. 24 samples. Type: Expression profiling by array.
Development of a microarray for Enchytraeus albidus (Oligochaeta): Preliminary tool with diverse applications
GEO Series GSE18569. Enchytraeus albidus. 16 samples. Type: Expression profiling by array.
Application of the High-throughput TAB-Array for the Discovery of Novel 5-Hydroxymethylcytosine Biomarkers in Pancreatic Ductal Adenocarcinoma
GEO Series GSE118694. Homo sapiens. 34 samples. Type: Methylation profiling by array.
Gene Co-Expression Network Analysis in Rhodobacter capsulatus and Application to Comparative Expression Analysis of Rhodobacter sphaeroides
GEO Series GSE53636. Rhodobacter capsulatus. 12 samples. Type: Expression profiling by array.
The design and validation of a Dehalococcoides genus microarray and its application to two newly isolated Dehalococcoides strains for comparative genomics
GEO Series GSE23707. Dehalococcoides; Anaeromyxobacter dehalogenans 2CP-C; Dehalococcoides mccartyi VS; Dehalococcoides mccartyi 195; Dehalococcoides sp. ANAS2; Dehalococcoides mccartyi BAV1; Dehalococcoides mccartyi CBDB1; Dehalococcoides sp. ANAS1. 24 samples. Type: Genome variation profiling by array.
Optimized methods for mapping DNA double-strand-break ends and resection tracts and application to meiotic recombination in mouse spermatocytes
GEO Series GSE265863. Mus musculus. 28 samples. Type: Other.
Deconstructing the Intercellular Interactome in Vascular Dementia with Focal Ischemia for Therapeutic Applications
GEO Series GSE298799. Mus musculus. 77 samples. Type: Expression profiling by high throughput sequencing.
Enhanced and controlled chromatin extraction from FFPE tissues and the application to ChIP-seq
GEO Series GSE128202. Mus musculus. 24 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Bioinformatics approaches for viral metagenomics in plants using short RNAs : model case of study and application to a Cicer arietinum population
GEO Series GSE63378. Cicer arietinum. 1 samples. Type: Non-coding RNA profiling by high throughput sequencing.
Assessing the significance of chromosomal aberrations in cancer: Methodology and application to glioma
GEO Series GSE9635. Homo sapiens. 374 samples. Type: Genome variation profiling by SNP array; SNP genotyping by SNP array.
Application of rapid CRISPR-Cas13a genetic identification to Chinook salmon in the Central Valley for the Juvenile Production Estimate (JPE)
Open the record for dataset details and reuse information.
Invasive Escherichia coli contributes to colon carcinogenesis by suppressing epithelial autophagy: application of phage therapy
GEO Series GSE144719. Mus musculus. 12 samples. Type: Expression profiling by array.
The development and application of LIMe-Hi-C to simultanteously study lamina association, DNA methylation and chromosome conformation at baseline and upon EZH2 and DNMT1 inhibition
GEO Series GSE180228. Homo sapiens. 13 samples. Type: Other.
Distributed Identification of Top-l Inner Product Elements and its Application in a Peer-to-Peer Network
Inner product computation is an important primitive used in many techniques for feature dependency detection, distance computation, clustering and correlation computation among others. Recently, peer-to-peer networks are getting increasing attention in various applications involving distributed file sharing, sensor networks, and mobile ad hoc networks. Efficient identification of top few inner product entries from the entire inner product matrix of features in a distributed peer-to-peer network is a challenging problem since centralizing the data from all the nodes in a synchronous, communication efficient manner may not be an option. This paper deals with the problem of identifying significant inner products among features in a peer-to-peer environment where different nodes observe a different set of data. It uses an ordinal framework to develop probabilistic algorithms to find top-LaTeX elements in the inner product matrix. These l inner product entries are important in making crucial decisions about dependency or relatedness between feature pairs, important for a number of data mining applications. In this paper we present experimental results demonstrating accurate and scalable performance of this algorithm for large peer-to-peer networks and also describe a real-world application for this algorithm.
Space Life and Physical Sciences Research and Applications Program
Space Life and Physical Sciences Research and Applications Program
Next-Generation Real-Time Geodetic Station Sensor Web for Natural Hazards Research and Applications Project
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Algorithms for Spectral Decomposition with Applications
The analysis of spectral signals for features that represent physical phenomenon is ubiquitous in the science and engineering communities. There are two main approaches that can be taken to extract relevant features from these high-dimensional data streams. The first set of approaches relies on extracting features using a physics-based paradigm where the underlying physical mechanism that generates the spectra is used to infer the most important features in the data stream. We focus on a complementary methodology that uses a data-driven technique that is informed by the underlying physics but also has the ability to adapt to unmodeled system attributes and dynamics. We discuss the following four algorithms: Spectral Decomposition Algorithm (SDA), Non-Negative Matrix Factorization (NMF), Independent Component Analysis (ICA) and Principal Components Analysis (PCA) and compare their performance on a spectral emulator which we use to generate artificial data with known statistical properties. This spectral emulator mimics the real-world phenomena arising from the plume of the space shuttle main engine and can be used to validate the results that arise from various spectral decomposition algorithms and is very useful for situations where real-world systems have very low probabilities of fault or failure. Our results indicate that methods like SDA and NMF provide a straightforward way of incorporating prior physical knowledge while NMF with a tuning mechanism can give superior performance on some tests. We demonstrate these algorithms to detect potential system-health issues on data from a spectral emulator with tunable health parameters.
A Modeling Framework for Prognostic Decision Making and its Application to UAV Mission Planning
The goal of prognostic decision making (PDM) is to utilize information on anticipated system health changes in selecting future actions. One of the key challenges in PDM is finding a sufficiently expressive yet compact mathematical representation of the system for use with decision optimization algorithms. In this paper we describe a general modeling approach for a class of PDM problems with non-linear system degradation processes and uncertainties in state estimation, action effects, and future operating conditions. The approach is based on continuous Partially Observable Markov Decision Processes (POMDPs) used in conjunction with 'black box' system simulations. The proposed modeling framework can be cast into simpler representations, depending on which sources of uncertainty are being included. The approach is illustrated with a mission planning case study for an unmanned aerial vehicle (UAV). In the case study a PDM system is tasked with optimizing the vehicle route after an in-flight component fault is detected. A stochastic algorithm (based on particle filtering) is used for decision optimization, with a second, deterministic algorithm providing a performance evaluation baseline. Both algorithms utilize a UAV physics simulator for generating predictions of future vehicle states. Performance benchmarking is done on a set of mission scenarios of increasing complexity.
New Sensing Application to Diagnose Power Semiconductor Aging in Actuator Power Drive Systems
This paper presents a new sensing application to diagnose power semiconductor aging in power drive systems. It has been shown previously that device parasitic characteristics change during the aging process which results in detectable changes in their frequency response. This change is manifested in the current signal at very high frequencies. Therefore, using a wideband AC current sensor, high frequency components of the current can be acquired, providing a way to detect device aging.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.