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173 results for “Statistical analysis”
Statistics and quantification dataset of Haspin and its related proteins analysis in mouse spermatocytes
<p><span>Chromosome segregation requires that centromeres properly attach to spindle microtubules. This essential step regulates the accuracy of cell division and therefore must be precisely regulated. One of the main centromeric regulatory signaling pathways is the Haspin-H3T3ph-</span><span>chromosomal passenger complex (</span><span>CPC) cascade, which is responsible for the recruitment of the</span><span> CPC to the centromeres</span><span>. In mitosis, Haspin kinase phosphorylates histone H3 at threonine 3 (H3T3ph), an essential epigenetic mark that recruits the CPC, whose catalytic component is Aurora B kinase. However, the centromeric Haspin-H3T3ph-CPC pathway remains largely uncharacterized in mammalian male meiosis. We have analyzed Haspin functions by either its chemical inhibition in cultured spermatocytes using LDN-192960, or the ablation of <em>Haspin</em> gene in <em>Haspin-/-</em>. Our studies suggest that Haspin kinase activity is required for proper chromosome congression during both meiotic divisions and for the recruitment of Aurora B and kinesin MCAK to meiotic centromeres. However, the absence of H3T3ph histone mark does not alter Borealin and SGO2 centromeric localization. These results add new and relevant information regarding the regulation of the Haspin-H3T3ph-CPC pathway and centromere function during meiosis. </span></p>
CLIC1 plasma concentration is associated with lymph node metastases in oral squamous cell carcinoma - Supplementary Material (Statistical Analysis)
<p>Supplementary file containing detailed statistical analysis of results of the article <em>CLIC1 plasma concentration is associated with lymph node metastases in oral squamous cell carcinoma.</em></p>
Data and statistical analysis scripts for manuscript on X-ray Microscopy of pennycress seeds
<p>Data and R statistical analysis code for manuscript on X-ray Microscopy of pennycress seeds</p> <blockquote> <p><strong>Evaluation of 3D seed structure and cellular traits in-situ using X-ray microscopy</strong></p> </blockquote> <p>The following files contains:</p> <ul> <li><code>Griffiths_et_al_2024_SeedXRM.R</code> - R statistics script for data processing of raw output from X-ray microscopy data and Marvin Seed analyzer data</li> <li><code>Raw_Data.zip</code> - Raw tabular data for use with R script from X-ray microscopy</li> <li><code>Data.zip</code> - Pre-processed tabluar data for use with R script</li> <li><code>Output.zip</code> - Output files that are generated from the R script</li> </ul>
A statistical analysis of tweeks in the mid-low latitudes based on long-term VLF measurements
<p>Figures, data, and code used in my paper describing "A statistical analysis of tweeks in the mid-low latitudes based on long-term VLF measurements"</p>
Statistical Analysis of Strategic Food Commodity Pricing Trends
<p>This material has presented on 2nd International Conference on Advance Research in Social and Economic Science in October 25, 2023.</p>
Root images for testing concatenation and statistical analysis with RhizoVision Explorer
<p>Thresholded images of cleaned and scanned roots as described for a paper entitled:</p> <p>"Divide and conquer: Using RhizoVision Explorer to aggregate data from multiple root scans using image concatenation and statistical methods"</p> <p>The zip file contains two main folders for Original and Concatenated images. Each contains a subfolder for the 3 different image sets for switchgrass, poplar, and petaland (which also includes some arctic samples). Original images include multiple scans of the same sample where the sample is denoted as a letter. Concatenated images were generated in python combining multiple scans of the same sample into one large image based on the common letter.</p>
Repeatability materials for paper "Database-Inspired Optimizations for Statistical Analysis"
<p>This repository contains files to replicate experiments in our paper "Database-Inspired Optimizations for Statistical Analysis", in particular data derived from the American Community Survey (ACS). Experiment scripts to use these files are here: https://scm.cwi.nl/DA/raaql-paper-experiments</p>
Supporting data and libraries used for statistical analysis for the article: "Targeted metabolomic profiling reveals differences in plasma metabolome of ovalbumin sensitised guinea pigs"
<p>Supporting data and libraries used for statistical analysis for the article: "Targeted metabolomic profiling reveals differences in plasma metabolome of ovalbumin sensitised guinea pigs"</p>
statistical analysis and data: How personality shapes gaze behavior without compromising subtle emotion recognition.
<pre>CODE:<br>script_gca_X.R: scripts used for the growth curve analysis fits<br>script_fits_brms_no_tb.r: script containing the fits (except those related to the crowth curve analysis).<br>inpact_script_contrasts.r: contrasts of every fits (call inpact_script_plot.r and inpact_script_save.r)<br>inpact_script_plot.r: plots<br>inpact_script_save: save contrasts to csv and xlsx files<br><br>DATA:<br>cluster_df.Rda: personality <br>neutral.Rda: neutral trials<br>sdtg.Rda: signal detection theory parameters<br>resp_emo.Rda : raw data to emotional trials<br>df_et4_propn.Rda: eye tracking data, first exposure phase of the emotional trials (0-1000ms)<br>df_et4_prop.Rda: eye tracking data, second exposure phase of the emotional trials (1000-2000ms)<br>df_n4_propn.Rda: eye tracking data, first exposure phase of the neutral trials (0-1000ms)<br>df_n4_prop.Rda: eye tracking data, second exposure phase of the neutral trials (1000-2000ms)<br><br>gca_e_contrast.Rda: contrasts of the growth curve analysis fit for the eye Area of Interest (AOI)<br>gca_n_contrast.Rda: contrasts of the growth curve analysis fit for the nose AOI<br>gca_m_contrast.Rda: contrasts of the growth curve analysis fit for the mouth AOI<br><br>X.rds: fits<br><br><br>STIMULI:<br>- videos of the neutral and emotional facial expressions<br>- backward masks</pre>
Graphics statistical analysis questionnaire
<p>Graphics from statistical analysis of the questionnaire and interviews on piltos</p>
Statistical analysis of the efficacy of the decontamination treatment
<p>This model was developed and applied by the EFSA Working Group on Working Group on the evaluation of substances used to remove microbial contamination from product of animal origin during the preparatory work on the Scientific Opinion ‘Evaluation of the safety and efficacy of the organic acids lactic and acetic acids to reduce microbiological surface contamination on pork carcasses and pork cuts' (see http://doi.org/10.2903/j.efsa.2018.5482).</p> <p>The code (SAS and R) has been used to evaluate the efficacy of two organic acids, lactic and acetic acid, intended to be used individually by food business operators during processing to reduce microbiological surface contamination on carcasses and cuts from pork. The reduction is expressed as log<sub>10</sub> reduction, i.e. the difference between the means of the log<sub>10</sub> concentrations of control group and treated group and corresponding 95% confidence interval (95% CI) when this information was available.</p> <p> </p> <p>The code may be run using these files:</p> <p>- data extraction from the file'<em>data_20181010.xlsx</em> '</p> <p>- References list using the file '<em>references_20180719.xlsx </em>'</p> <p>- Appraisal scores using the file '<em>Appraisal_20181004.xlsx </em>'</p> <p> </p>
Images and statistical analysis of alfalfa root crowns from inside and outside disease rings caused by cotton root rot
<p>This repository contains raw image data of root crowns imaged using the backlit RhizoVision Crown platform of alfalfa plants from either inside or outside disease rings caused by cotton root rot for a manuscript to be submitted. Data files and the R scripts are included for complete statistical analysis associated with the imaged root crown set.</p> <p>Please cite both this repository and below journal article if reusing this data for a publication.</p> <p><strong>Manuscript Title:</strong> Digital imaging to evaluate root system architectural changes associated with soil biotic factors</p> <p><strong>Authors: </strong>Chakradhar Mattupalli, Anand Seethepalli, Larry M. York, Carolyn A. Young</p> <p><strong>Journal Article: </strong><a href="https://doi.org/10.1094/PBIOMES-12-18-0062-R">https://doi.org/10.1094/PBIOMES-12-18-0062-R</a> (open access)</p> <p><strong>Image Files</strong></p> <p>afalfa_roots_raw_images.zip - 264 images in PNG format directly from a monochrome camera with gamma at 3.9 to make near-segmented raw images in greyscale</p> <p>alfalfa_feature_images.zip - 264 images in PNG format with a subset of computed features overlaid</p> <p>alfalfa_segmented_images.zip - 264 black and white, binary images in PNG format that result from simple thresholding of the raw images</p> <p>I_scale_1.png - an image of a 6 inch ruler for extracting pixel to physical unit conversion</p> <p>metadata.csv - metadata output from RhizoVision Analyzer with diameter ranges and other options used for image analysis</p> <p><strong>Statistical Analysis</strong></p> <p>alfalfaCRR_features_10012018.csv - extracted features from RhizoVision Analyzer v1.0.3 - called by name in R script</p> <p>RootArchitectureFieldStudyimagetoIDmap.csv - mapping of image file names to plot identity - called by name in R script</p> <p>manuscript complete root rot RVC analysis.R - R script with all analysis that used the data from the imaged root crowns</p> <p> </p> <p> </p>
Quick, Stat!: a statistical analysis of the Quick, Draw! Dataset
<p>Dataset used for the experiments of https://arxiv.org/abs/1907.06417 . This dataset is extracted from The Quick, Draw!<br> - A.I. Experiment. https://quickdraw.withgoogle.com/</p> <p> </p>
Minimizer collision statistics (BLEND: A Fast, Memory-Efficient, and Accurate Mechanism to Find Fuzzy Seed Matches in Genome Analysis)
<p>This dataset includes the statistics for the minimizers that generate the same hash value (i.e., collisions). The hash values are generated using a low-collision hash function and the SimHash technique in BLEND.</p> <p> </p> <p>*collision_stats.txt files include the overall collision statistics for a tool and configuration of the tool (i.e., the number of colliding minimizer pairs with a certain edit distance and their ratio to all number of collisions). For example blend_n3_collision_stats.txt shows the statistics for BLEND where the number of neighbors is set to 3 when running BLEND.</p> <p>_sim.csv files include all minimizer pairs with the same hash value and the edit distance between them.</p> <p> </p>
K-mer collision statistics (BLEND: A Fast, Memory-Efficient, and Accurate Mechanism to Find Fuzzy Seed Matches in Genome Analysis)
<p>This dataset contains 1,077 FASTA files and CSV files. Each FASTA file includes 25-character long sequences similar to each other.</p> <p>We have a CSV file for each tool (i.e., minimap2 and BLEND) and configuration (i.e., different number of neighbors in BLEND). CSV files include the non-identical k-mer pairs (16-mers) that generate the same hash value (i.e., collisions). These k-mers are extracted from sequences that are similar to each other. In each line, we show the hash value of the k-mers, the actual sequene pairs that the k-mers are extracted from, k-mer pairs that generate the same hash value, and the edit distance between these k-mers.</p> <p> </p>
Table 7. Results of calculation of epithelialization time statistics one-way analysis of variance (ANOVA) with SPSS 23.00
<p>Table 7. Results of calculation of epithelialization time statistics one-way analysis of variance (ANOVA) with SPSS 23.00</p>
Joint analysis of GWAS and multi-omics QTL summary statistics reveals a large fraction of GWAS signals shared with molecular phenotypes
<p>Data relevant to Wu et al. "Joint analysis of GWAS and multi-omics QTL summary statistics reveals a large fraction of GWAS signals shared with molecular phenotypes". </p>
Data and statistical analysis for: Response to Elexacaftor/Tezacaftor/Ivacaftor in intestinal organoids derived from patients with cystic fibrosis
<p>Data and code to reproduce all statistical analyses and figure in the manuscript "Response to Elexacaftor/Tezacaftor/Ivacaftor in intestinal organoids derived from patients with cystic fibrosis".</p> <p>The dataset is stored in the file `area_data.csv`, the columns are:</p> <ul> <li>`well` The ID of the well within the plate the measurement was taken</li> <li>`time` time from start of measurement</li> <li>`area` area of the organoids</li> <li>`patient` Anonymized ID of the patient</li> <li>`date` Date when the experiment was performed (date and patient ID identify the plate)</li> <li>`filename` The filename in raw data (not published) this plate was stored in. (uniquely identifies a plate)</li> <li>`mix` Identifies one od two variants of plate layouts used</li> <li>`replicate` ID of technical replicate (two technical replicates were done for each condition on the same plate)</li> <li>`type` The main condition - one of "TEZ/IVA", "ELX/TEZ/IVA", "FskOnly" (Control, only forskolin)</li> <li>`fsk_concentration` concentration of forskolin (μM)</li> </ul> <p>The file "organoids.Rmd" reproduces the analyses, other files are supporting to let the main analysis run.</p> <p>The analysis is written in R markdown.</p> <p> </p>
Statistically Analysis of Carpal Tunnel Syndrome Diagnosis
ClinicalTrials.gov study NCT05584839. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Observational Prospective Study.at the End of the Study the Patients Will be Classified According to PH,Serum Bicarbonate and Serum Sodium Into 6 Groups and Statistical Analysis Will be Performed Usin
ClinicalTrials.gov study NCT05082064. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
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.