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1,481
datasets available to search
ShareScore release 0.9.0
Dataset results
1,481 results for “data processing”
HiCUP: pipeline for mapping and processing Hi-C data
GEO Series GSE73204. Mus musculus. 3 samples. Type: Other.
Optimization of miRNA-seq Data Pre-Processing
GEO Series GSE67074. Homo sapiens. 12 samples. Type: Non-coding RNA profiling by high throughput sequencing.
Clustering gene expression time series data using an infinite Gaussian process mixture model
GEO Series GSE104714. Homo sapiens. 24 samples. Type: Expression profiling by high throughput sequencing.
Alternatively processed and compiled RNA-Sequencing and clinical data for thousands of samples from The Cancer Genome Atlas
GEO Series GSE62944. Homo sapiens. 2 samples. Type: Expression profiling by high throughput sequencing.
Quantifying the effect of experimental perturbations in single-cell3RNA-sequencing data using graph signal processing
GEO Series GSE161465. Homo sapiens. 6 samples. Type: Expression profiling by high throughput sequencing.
Deep sequencing data from crRNA processing by SuCasΩ
GEO Series GSE178531. Escherichia coli. 1 samples. Type: Other.
methylGrapher: Genome-Graph-Based Processing of DNA Methylation Data from Whole Genome Bisulfite Sequencing
GEO Series GSE261315. Homo sapiens. 10 samples. Type: Methylation profiling by high throughput sequencing.
Integrative regulatory mapping indicates that the RNA-binding protein HuR (ELAVL1) couples pre-mRNA processing and mRNA stability [sequence data]
GEO Series GSE29779. Homo sapiens. 1 samples. Type: Other.
ChIP-seq data processing and relative and quantitative signal normalization for Saccharomyces cerevisiae
GEO Series GSE288548. Saccharomyces cerevisiae. 24 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Identification of a p-coumarate degradation regulon in Rhodopseudomonas palustris using Xpression, an integrated tool for prokaryotic RNA-seq data processing
GEO Series GSE39025. Rhodopseudomonas palustris CGA009. 3 samples. Type: Expression profiling by high throughput sequencing.
A data mining paradigm for identifying key factors in biological processes using gene expression data
GEO Series GSE100100. Mus musculus. 12 samples. Type: Expression profiling by high throughput sequencing.
Improving fibroblast characterization using single-cell RNA sequencing: an optimized tissue disaggregation and data processing pipeline
GEO Series GSE126111. Homo sapiens. 6 samples. Type: Expression profiling by high throughput sequencing.
Effect of performing SLAM-seq chemistry in methanol fixed cells versus standard tube processing on quantification bias in nucleotide conversion RNA-seq data
GEO Series GSE253370. Mus musculus. 12 samples. Type: Expression profiling by high throughput sequencing.
Data set for "Determining the minimum energy requirement of an LNG process: New insights into the impact of the vapour liquid equilibrium"
<p>Accompanying information for Xuan et al, 2020, "Determining the minimum energy requirement of an LNG process: New insights into the impact of the vapour liquid equilibrium", Energy, Paper number 117785, <a href="https://doi.org/10.1016/j.energy.2020.117785">https://doi.org/10.1016/j.energy.2020.117785</a></p>
Data for "Towards standardized processing of eddy covariance flux measurements of carbonyl sulfide"
<p>The final data set used in manuscript "Towards standardized processing of eddy covariance flux measurements of carbonyl sulfide" by Kohonen et al. (2020). The data set contains carbonyl sulfide (COS), carbon dioxide (CO2), carbon monoxide (CO) and water vapor (H2O) fluxes, together with flux ancillary data, measured at Hyytiälä forest in Juupajoki, Southern Finland, from July 2015 to October 2015. Hyytiala_COS_ECflux_2015.csv includes the quality screened flux data without u* filtering or storage correction. Final_ECfluxes_2015.dat includes the final data set of quality screened, u* filtered, storage corrected and gap-filled flux data. Raw data and data processed with other processing options are available upon request from the author.</p>
Data from Schmitt et al. 2018: Preattentive and Predictive Processing of Visual Motion
<p><strong>Dataset associated with the following publication:</strong></p> <p>Schmitt C, Klingenhoefer S, Bremmer F. Preattentive and Predictive Processing of Visual Motion. <em>Sci Rep</em>. 2018;8(1):12399. Published 2018 Aug 17. doi:10.1038/s41598-018-30832-9</p> <p><strong>Description of dataset:</strong></p> <p>The dataset contains preprocessed EEG data recorded from the 15 electrodes (Cz, Fz, FCz, FC1, FC2, F3, F4, FC5, FC6, P3, P4, P7, P8, PO3, PO4) used for analysis in our paper. Data containing eye movements, blinks or a movement response of the participants were removed. As a reference the average signal of the mastoid electrodes TP9 and TP10 was used.</p> <p>In a first preporcessing step data were low pass filtered with a cut-off frequency of 70 Hz and additionally a Notch filter at 50 Hz was applied. In a second step data were aligned to the (re)appearance of the moving target next to the central occluder and cut into 850 ms long epochs ranging from 200 ms before this (re)appearance to 650 ms after this time point. The average signal from a 50 ms long time window starting 50 ms before the (re)appearance was used for a baseline correction of each epoch before epochs were averaged separately for subjects and conditions as a last preprocessing step. </p> <p>Each uploaded file contains data of all 8 participants and all 15 electrodes separately for the four different conditions: 1) target movement to the right in complete trajectory trails (data_movedirR_complete_trajectory.mat); 2) target movement to the left in complete trajectory trails (data_movedirL_complete_trajectory.mat); 3) target movement to the right in half trajectory trails (data_movedirR_half_trajectory.mat); 4) target movement to the left in half trajectory trails (data_movedirL_half_trajectory.mat).</p> <p>Each file contains 30 matrices for the half trajectory conditions and 60 matrices for the complete trajectory conditions. Each matrix presents the data recorded at one electrode, for one type of trial (standard "AllS", deviant "AllD" or half trajectory "AllH") and one attention condition (attention to the fixation target, central "1" and attention to the moving target, peripheral "2"). Example: "P3_AllD_1"</p> <p>Each matrix consists of 8 lines representing the 8 participants. Data for the relevant condition was averaged for each participant and is presented in a separate line. The matrices consist of 850 columns representing the length of the presented recording time of 850 ms. Data from 200 ms before to 650 ms after the (re)appearance of the moving target is presented. The uploaded matrices contain values in µV.</p>
Processed data from "Human and rat skeletal muscle single-nuclei multi-omic integrative analyses nominate causal cell types, regulatory elements, and SNPs for complex traits"
<p>This is the processed data from our manscript "Human and rat skeletal muscle single-nuclei multi-omic integrative analyses nominate causal cell types, regulatory elements, and SNPs for complex traits"</p>
Usability Evaluation Process for Domain-Specific Languages - Documents and survey data
<p>Usability Evaluation Process for Domain-Specific Languages - Documents and survey data</p>
HR8799 NIRC2/Vortex Processed Data
<p>Processed data for HR8799 captured using Keck II's NIRC2 with the Vortex Coronagraph. The data was processed in preparation for a journal article and is <a href="https://mb2448.github.io/rnaas_data.html">further described on this page</a>.</p>
Data from: Ocean acidification induces biochemical and morphological changes in the calcification process of large benthic foraminifera
Large benthic foraminifera are significant contributors to sediment formation on coral reefs, yet they are vulnerable to ocean acidification. Here, we assessed the biochemical and morphological impacts of acidification on the calcification of Amphistegina lessonii and Marginopora vertebralis exposed to different pH conditions. We measured growth rates (surface area and buoyant weight) and Ca-ATPase and Mg-ATPase activities and calculated shell density using micro-computer tomography images. In A. lessonii, we detected a significant decrease in buoyant weight, a reduction in the density of inner skeletal chambers, and an increase of Ca-ATPase and Mg-ATPase activities at pH 7.6 when compared with ambient conditions of pH 8.1. By contrast, M. vertebralis showed an inhibition in Mg-ATPase activity under lowered pH, with growth rate and skeletal density remaining constant. While M. vertebralis is considered to be more sensitive than A. lessonii owing to its high-Mg-calcite skeleton, it appears to be less affected by changes in pH, based on the parameters assessed in this study. We suggest difference in biochemical pathways of calcification as the main factor influencing response to changes in pH levels, and that A. lessonii and M. vertebralis have the ability to regulate biochemical functions to cope with short-term increases in acidity.
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.