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814 results for “Time Analysis”
Table with the results of the time series gene expression analysis for fins.
<p>Differences between transcriptomes of two Cottus fish lineages were assessed in the natural environment. Sampling was performed in a time series covering whole year. Two tissues were investigated: fins and livers. Present table shows results of a time series differential gene expression analysis performed on fin tissues.</p>
A time-course analysis using Differential Static Light Scattering (DSLS) of purified HTT1-3144 Q23 - 2019/01/28
<p><strong>Project: </strong>Biophysical investigation of purified HTT protein samples</p> <p><strong>Experiment: </strong>A time-course analysis using Differential Static Light Scattering (DSLS) of purified HTT<sup>1-3144</sup>Q23 </p> <p><strong>Date completed:­ </strong>2019/01/28</p> <p><strong>Rationale: </strong>Time and resources in the HD field have been primarily focussed on understanding HTT aggregation looking as caspase cleavage products spanning aa. 1-586 or exon 1 spanning aa. 1-90. However, we know that HTT protein purified in its apo form is able to self-associate into larger oligomeric species and that monomer, dimer and larger species are found following FLAG-affinity chromatography as determined by size-exclusion chromatography (SEC) and SEC-multi-angle light scattering (SEC-MALS). This experiment aimed to begin to investigate how HTT self-associates and aggregates over time in a range of different conditions. </p>
Time-slide correlation analysis of post-merger Extended Emission to GW170817
<p>Nico van Kampen Colloquium, ITP, Utrecht (October 23 2019, https://zenodo.org/record/3528005) - Movie clip. Shown is the result of $\chi$-image analysis of merged (H1,L1)-spectrograms produced in time-slide correlation analysis of H1-L1 data of GW170817. Time-sliding over -32s $\le \Delta t \le 32$s, including one-sample steps around the zero-crossing $\Delta t = 0$, reveals clustering of $\chi$-peak values representing a correlated (H1,L1)-detector response to a gravitational-wave signal.</p>
Experiment and analysis data of Study on the Effect of Pore-Clogging Caused by Fenton's Reagent on the Hydraulic Conductivity Using Time-lapsed Hydraulic Tomography
<p>The Microsoft Office Excel data file ('HT data.xlsx') contains two sheets: the first sheet includes the raw data from the first and second HT experiments, labeled as '1st' and '2nd' respectively; the second sheet contains their processed data.</p> <p>The compressed file ('Models.rar') includes all the models, such as the forward and inverse models. Each model contains its own input files and an executable file.</p>
"Toy Data Set" referenced in the article "A deep-learning based analysis framework for ultra-high throughput screening time-series data" (https://doi.org/10.1101/2024.08.22.609110)
<p>This data set, referenced as "toy data set" in the article "A deep-learning based analysis framework for ultra-high throughput screening time-series data" (<a href="Lint-to-article">https://doi.org/10.1101/2024.08.22.609110</a>), mimics a high-throughput screening data set. To demonstrate the application of our analysis framework described in the main article this toy data set was generated. It contains in total 1536000 individual transient signals, splitted in 5 batches of each 200 plates in 1536-well plate format. Five distinct signal classes were used to resemble typical shapes encountered in biological experiments. Fequency of occurrences for each class is reported in the main article.</p>
Supplementary Table S1. Combined analysis of variance containing the degrees of freedom (DF), mean squares (MS), P value (P val.), mean, coefficient of experimental variation (CEV%) and selective accuracy (SA) for the traits of luminosity (L*), chromaticity a* (a*), chromaticity b* (b*), grain length (length, mm), grain width (width, mm), grain thickness (thickness, mm), mass of 100 grains (Mass, g), normal grains (Ng, %), water absorption (absorption, %), cooking time (Ct, min:s), and concentrations of potassium (K, g kg-1 dry matter - DM), phosphorus (P, g kg-1 DM), calcium (Ca, g kg-1 DM), magnesium (Mg, g kg-1 DM), iron (Fe, mg kg-1 DM), zinc (Zn, mg kg-1 DM), and copper (Cu, mg kg-1 DM) obtained in 25 common bean cultivars evaluated in four experiments carried out from 2019 to 2021
<p><strong><span>Table S1.</span></strong><span> Combined analysis of variance.</span></p> <p><strong><span>Indirect selection for multiple technological and nutritional traits in common bean cultivars under different degrees of multicollinearity</span></strong></p> <p><strong><span>Bragantia, 2024.</span></strong></p>
Data files for manuscript "Exome first approach to reduce diagnostic costs and time – retrospective analysis of 111 individuals with rare neurodevelopmental disorders"
<p>#2021-07-23<br> #Summary<br> This ZIP-file contains the Excel files used for the clinical and variant analyses for the manuscript "Exome first approach to reduce diagnostic costs and time – retrospective analysis of 111 individuals with rare neurodevelopmental disorders".</p> <p>#Folder structure<br> ./ (parent directory containing this README file and all subfolders)<br> ./Clinical/ (contains an Excel sheets with complete clinical data, costs and criteria)<br> ./Variants/ (contains an Excel sheet with all variant annotation)</p> <p>#Files and checksums<br> 6DB0EF10BE7A7AF5A18E523F33FB662A ./Clinical/FileS2_Clinical.xlsx<br> 0B0C1AFA0751B63A35DC99DB25546A38 ./Variants/FileS3_Variants.xlsx</p>
LA-ICP-MS line scan data and time-series analysis outputs for Baltic Sea sediment core F80
<p>The datafile contains two sheets: HTM and MCA, corresponding to geochemical data from the Holocene Thermal Maximum and Medieval Climate Anomaly intervals, respectively, of a sediment core from the Baltic Sea (site F80, 58°00.00N, 19°53.81E, water depth 191m, Fårö Deep, collected during the HYPER/COMBINE cruise of R/V Aranda, May/June 2009). In each sheet, columns A-J contain Laser Ablation (LA)-ICP-MS line scan data of element ratios in resin-embedded sediment (Mo/Al, Fe/Al and Br/P) presented in the time domain (Age in years BP). Dating of the sediment core is described in the accompanying manuscript and references therein. These profiles are presented in three forms: Raw= raw data resampled to 1 year resolution; Det= detrended and normalized to unit variance; Gau; Gaussian bandpass filter at a period of 20-100 years. Columns L-S contain time-series analysis results of the detrended, normalized elemental ratios in period domain, including power spectra of each ratio (Blackman-Tukey window, columns M-O) and cross-spectral analysis (Blackman-Tukey window, bandwidth 5 years) of Mo/Al vs Br/P (columns P-Q) and Mo/Al vs Fe/Al (columns R-S), respectively. All analyses were performed in Analyseries 1.1.1 (Paillard et al., 1996). Figures containing the data have been submitted as part of a manuscript to Geophysical Research Letters (Jilbert et al., forthcoming),</p> <p> </p> <p>Paillard, D., Labeyrie, L., & Yiou, P. (1996). Macintosh program performs time‐series analysis. <em>Eos, Transactions American Geophysical Union</em>,<em> 77</em>(39), 379-379. <a href="https://doi.org/10.1029/96EO00259">https://doi.org/10.1029/96EO00259</a></p> <p>Jilbert, T., Gustafsson, B.G., Veldhuijzen, S., Reed, D.C., van Helmond, N.A.G.M., Hermans, M., & Slomp, C.P (forthcoming). Iron-phosphorus feedbacks drive multidecadal oscillations in Baltic Sea hypoxia. Submitted to <em>Geophysical Research Letters</em></p>
Normalized NMR integration values from the metabolomic analysis of Drosophila larvae extracts from 2 genotypes at 3 time points.
<p>We measured the metabolites related to energy production using 1H nuclear magnetic resonance spectroscopy (NMR). No alterations in the levels of carbohydrate stores or free amino acids were found between control and Sema1ai animals, corroborating the notion that the main metabolic changes are in the lipid metabolism. The exception is the glycolytic amino acid alanine (elevated in Sema1ai animals), confirming alterations in glycolysis. The levels of the ß-alanine amino acid are markedly reduced in 256 h AEL or 10.5-day-old Sema1ai animals, probably indicating muscle degeneration in the severely obese larvae that is consistent with the deteriorated state and reduced movement of the 10-day-old (256 hours) mutant larvae. Gluconeogenesis is stimulated by high lactate, and the concentration of lactate is higher in Sema1ai larvae than controls, though the difference is not statistically significant. Glycolysis is stimulated by glucose and inhibited by citrate, an early intermediate of the citric acid cycle. The increased citrate levels in the 10.5-day-old Sema1ai larvae suggest that glycolysis is lower at this age, consistent with the increased level of glucose in the severely obese larvae. The fact that both gluconeogenesis and glycolysis pathways are simultaneously enhanced in Sema1ai larvae support the hypothesis that the animals defecting in adiposity signaling are in a state of perceived energy insufficiency despite having sufficient energy stored.</p>
dhaw/fluCodeImperial: Using real-time data to guide decision-making during an influenza pandemic: a modelling analysis
<p><strong>All codes and data used for "Using real-time data to guide decision-making during an influenza pandemic: a modelling analysis" are included in this folder. The file "runExamples.m" contains a step-by-step method for reproducing figures and running model fits. Ensure that all data and code files are in the same directory, then a single execution of “runExamples” on the command line will generate all main and supplementary figures in the manuscript. There is one line of code per figure, clearly marked, that can be commented out as desired. In order to run the MCMC adaptive algorithm, a single line of code, also clearly marked, must be commented back in. Instructions to change the single-state example are given at the top of the file “runExamples.m”. The saved state selection of California (“state=1”) is consistent with all results presented in the manuscript. </strong></p> <p><strong> </strong></p> <p><strong>Plots make use of files from the following sources, with some modifications:</strong></p> <p><strong>Holger Hoffmann (2022). Violin Plot (https://www.mathworks.com/matlabcentral/fileexchange/45134-violin-plot);</strong></p> <p><strong>Evan (2022). Plot Groups of Stacked Bars (https://www.mathworks.com/matlabcentral/fileexchange/32884-plot-groups-of-stacked-bars);</strong></p> <p><strong>John Onofrey (2022). Shaded Plots and Statistical Distribution Visualizations (https://www.mathworks.com/matlabcentral/fileexchange/69203-shaded-plots-and-statistical-distribution-visualizations)</strong></p>
Time-to-Event analysis of factors influencing delay in discharge from a subacute Complex Discharge Unit during the first year of the pandemic (2020) in an Irish tertiary centre hospital
<p><strong>Figure S1:</strong> Forest plots 1 and 2 depicting Age and Gender strata associated Hazard ratio (Markers) estimates (95% Confidence Interval demonstrated by horizontal line) exhibited statistically significant results for individuals <65 years of age who had a delay in discharge due to complications from comorbidities; those in 65-75 years of age category, had prolonged LOS due to admission with frailty, falls and/or integrated rehabilitation needs; and 75-85 years of age category showed an association of at least 4 out of the 5 common delaying factors. Strata Gender exhibited a significant delay in discharge due to complications from comorbidities and patient-centred needs; in comparison to the female gender who also experienced a delay in discharge as a result of both factors alongside frailty, falls and/or integrated rehabilitation needs.<strong>[A. </strong>Complications/comorbidities prolonging discharge, <strong>B.</strong> Healthcare-associated infection, <strong>C</strong>. Frailty, falls and/or integrated rehabilitation needs, <strong>D</strong>. Patient-centred needs, <strong>E</strong>. Community services]. </p> <p><strong>Figure S2:</strong> Forest plot 3 depicting Multimorbidity (MM) strata-associated Hazard ratio (Markers) estimates (95% Confidence Interval demonstrated by horizontal line) exhibited a significant delay in discharge due to complications from comorbidities, frailty, falls, and/or integrated rehabilitation and patient-centred needs in patients with ≤4 MM. In contrast patients with >4 MM experienced significant delays in discharge due to complications from comorbidities and patient-centred needs. <strong>[A. </strong>Complications/comorbidities prolonging discharge, <strong>B.</strong> Healthcare-associated infection, <strong>C</strong>. Frailty, falls and/or integrated rehabilitation needs, <strong>D</strong>. Patient-centred needs, <strong>E</strong>. Community Services].</p>
Time Series Analysis of a Daytime Urban Heat Island in Dar es Salaam Metropolitan Areas.
<p>The study aimed to determine the existing linear influence levels of various causative factors of Urban Heat Island (UHI) by using Geographically Weighted Regression Model (GWR) that determines non-stationarity by generating a new equation for each sample size. Urban heat island occurs when higher temperatures reside in urban areas compared to surrounding areas due to the replacement of natural vegetation with construction materials during development purposes. Time Series with Linear Regression was used to determine the linearity between dependent and independent variables. Moderate Resolution Imaging Spectroradiometer (MODIS) products such as MOD11A1, MCD43A1, MOD09A1 and MOD13A1 were used to acquire Land Surface Temperature (LST), Albedo, Indexed-Based Built-Up Index (IBI) and Enhanced Vegetation Index (EVI) respectively. In-situ datasets of the wind speed were acquired from Tanzania Meteorological Agency (TMA). UHI was observed to have a non-linear trend with IBI and wind speed and a linear trend with Albedo and EVI. The strongest values of UHI were observed at the city center, IBI was observed as a leading causative factor by having a non-lineality influence of 0.023 followed by Albedo, wind speed and EVI with an influence of 0.019, 0.016 and -0.015 respectively. Since IBI and Albedo contribute more to the development of heat island, urban residents should be encouraged to use construction materials with a lower absorption rate of solar energy.</p>
Time series analysis of tegument ultrastructure of in vitro transformed miracidium to mother sporocyst of the human parasite Schistosoma mansoni
<p>Here is a compilation of all the Scanning Electron Microscopy pictures at our disposal regarding the in vitro transformation of miracidia to mother sporocysts of <em>Schistosoma mansoni</em>. These datas were partially published in:</p> <p><a href="https://doi.org/10.1016/j.actatropica.2023.106840">https://doi.org/10.1016/j.actatropica.2023.106840</a></p> <p> </p>
Exploratory Analysis of Top 50 Companies in Indian Stock Market: A Time Series Analysis of Historical Stock Prices
<p>The dataset consists of 'open, close, high, low, close, adj close and volume' columns for the top 50 Indian Companies and the dataset been fetched from YahooFinance for over 20 years. </p>
Characterisation of night-time outdoor lighting in small urban centres using cluster analysis of remotely sensed light emissions (Dataset)
<p>Data used for the paper "Characterisation of night-time outdoor lighting in small urban centres using cluster analysis of remotely sensed light emissions". </p>
TAT: Timing Analysis Toolkit for high-energy pulsar astrophysics
<p>The TAT-pulsar (Timing Analysis Toolkit for Pulsars) package is a specialized toolkit designed for handling the scientific intricacies of pulsar timing. It provides a suite of Python-based utilities and scripts that facilitate the analysis, processing, and visualization of pulsar data. By leveraging observational data from pulsars, along with the associated physical processes and statistical characteristics, TAT-pulsar integrates a series of useful tools and data analysis scripts specifically developed for both isolated pulsars and binary systems. This enables swift analysis and the detailed presentation of timing properties in the high-energy pulsar field. Developed and implemented completely independently from other pulsar timing software such as Stingray (<a href="https://ascl.net/1608.001">ascl:1608.001</a>) and PINT (<a href="https://ascl.net/1902.007">ascl:1902.007</a>), TAT-pulsar serves as a valuable cross-checking and supplementary tool for data analysis.</p>
Data for: Developmental plasticity in anurans: meta-analysis reveals effects of larval environments on size at metamorphosis and timing of metamorphosis
<p>Many anuran amphibians (frogs and toads) rely on aquatic habitats during their larval stage. The quality of this environment can significantly impact the overall lifetime fitness and dynamics of the population. Over 450 studies have been published on the impact of the environment on anuran developmental plasticity, yet we lack a synthesis of these effects across different environments. We conducted a meta-analysis and used a comparative approach to understand whether developmental plasticity in response to different larval environments produces predictable changes in metamorphic phenotypes. We analyzed data from 124 studies spanning 80 anuran species and six larval environments and showed that interspecific variation in mass at metamorphosis and the duration of the larval period is partly explained by the type of environment experienced during the larval period. Phylogenetic relationships among species were not associated with variation in mass at metamorphosis plasticity or duration of the larval period plasticity. Larval environments tended to reduce mass at metamorphosis relative to control conditions, with the degree of change depending on the identity and severity of environmental change. Higher temperatures and lower water levels shortened the duration of the larval period, whereas less food and higher densities increased the duration of the larval period. Our results provide a foundation for future studies on developmental plasticity, especially in response to global changes. This study provides motivation for additional work that links developmental plasticity with fitness consequences within and across life stages, as well as how the outcomes described here are altered in compounding environments.</p>
Data and analysis code of "Forestation at the right time with the right species can generate persistent carbon benefits in China"
<p>This collection contains the datasets used in our study ‘<strong><em>Forestation at the right time with the right species can generate persistent carbon benefits in China</em></strong>’.</p> <p> </p> <p><strong><em>Part A: Data</em></strong></p> <p>Most of the data presented here are after pre-processing, such as transforming the projection, extracting variables, clipping to the study region (70<sup>o</sup>E-140<sup>o</sup>E,15<sup>o</sup>N-55<sup>o</sup>N), and resampling to 1-km.</p> <p>The original source of these data sets (usually global, at different resolutions) is given in 'data_original.txt' as well as in the 'Data availability' of the main text.</p> <p>1. Climate_china_1km.7z: This compressed file contains the annual precipitation and temperature from Peng et al. 2019 at 1km.</p> <p>2. Soil_china_1km.7z: This compressed file contains the soil properties derived from Soilgrid250m for China at 1-km resolution.</p> <p>3. Topography_china_1km.7z: This compressed file contains the topographic properties derived from Global Multi-resolution Terrain Elevation Data 2010 for China at 1-km resolution.</p> <p>4. MaxEnt_process.7z: This compressed file contains all the input data and model results of the MaxEnt model: 1) environment layers in ’.asc’, 2) rarefied occurrence points for the 15 forest types, 3) MaxEnt results in ’.tif’ (average of the 10-folds results)</p> <p>5. Potential_china_forest_1km.7z: contains the potential forest distributions for China at 1-km resolution from multiple source (Random Forest, WRI and ORCHIDEE). Note: the forest distribution is in the form of logical variables in the .mat file, where a value of 1 or true means that the grid point is potentially forestable, and a value of 0 or false means this grid is not suitable for forest.</p> <p>6. Existing_china_forest_1km.7z: contains the existing forest distributions for China at 1-km resolution from multiple source (FI2013-2017, Hansen, MODIS, ESA-CCI, CNLUCC, GLC-FCS30 and GlobeLand30). Note: the existing forest distribution is in the form of logical variables in the .mat file, where a value of 1 or true means there is forest distribution, and a value of 0 or false means there is currently no forest distribution.</p> <p>7. Crop_urban_china_1km.7z: similar to the Existing_china_forest_1km.zip, but stores the distribution of cropland and urban.</p> <p>8. Masks_area_china_1km.7z: area mask and the shp files of the national and provincial boundaries of China.</p> <p>9. CMIP6_outputs.7z: contains historical (1970-2014) and future (2015-2100) climate and CO2 fertilization factor simulated by Earth System Models participating in CMIP6.</p> <p>10. Ori_carbon_all_grid_1km.mat: Living biomass carbon densities in 2010 for China at 1-km (unit: Mg C ha<sup>-1</sup>). Both aboveground and belowground biomass carbon values are included. The original biomass map is from Spawn et al. 2020.</p> <p>11. Forest_inventory_data_5th_9th.xlsx: 1) The forest area reported in 5th to 9th national forest inventory 2) The forest area of different age classes derived from the 9th national forest inventory.</p> <p>12. Forest_age_CN2019.7z: the forest stand age map for China updated to 2019.</p> <p>13. data_original.txt: the original source of these data sets</p> <p><strong>Part B: MATLAB Code</strong></p> <p>This file (Matlab_code.7z) contains the code, functions and parameters for our analysis of the data, mainly MATLAB files (.m or mat)</p> <p><strong>Part C: Demo/Example data and code</strong></p> <p>This file (Demo.7z) contains the demo of our code running, which includes the demo code along with code comments, input data for the demo, and the expected output results.</p> <p><strong>Part D: Docs</strong></p> <p>Reference and guidelines (Docs.7z).</p> <p>If you have any questions or suggestions, please contact xuhaotony@pku.edu.cn</p>
The second data release from the European Pulsar Timing Array I. The dataset and timing analysis
<p>Pulsar timing arrays offer a probe of the low-frequency gravitational wave spectrum (1−100 nanohertz), which is intimately connected to a number of markers that can uniquely trace the formation and evolution of the Universe. We present the dataset and the results of the timing analysis from the second data release of the European Pulsar Timing Array (EPTA). The dataset contains high-precision pulsar timing data from25 millisecond pulsars collected with the five largest radio telescopes in Europe, as well as the Large European Array for Pulsars. The dataset forms the foundation for the search for gravitational waves by the EPTA, presented in associated papers. We describe the dataset and present the results of the frequentist and Bayesian pulsar timing analysis for individual millisecond pulsars that have been observed over the last∼25 years.We discuss the improvements to the individual pulsar parameter estimates, as well as new measurements of the physical properties of these pulsars and their companions. This data release extends the dataset from EPTA Data Release 1 up to the beginning of 2021, with individual pulsar datasets with timespans ranging from 14 to 25 years. These lead to improved constraints on annual parallaxes, secular variation of the orbital period, and Shapiro delay for a number of sources. Based on these results, we derived astrophysical parameters that include distances, transverse velocities,binary pulsar masses, and annual orbital parallaxes.</p>
Attack time analysis in dynamic attack trees via integer linear programming
<p>Matlab code for the experiments of the paper "Attack time analysis in dynamic attack trees via integer linear programming" by Milan Lopuhaä-Zwakenberg & Mariëlle Stoelinga.</p> <p>The code can be accessed either via the virtual machine in Artifact_MILPforDATs_revised.zip, or through the code directly in Matlab_code.zip. The results are in Paper_results.zip.</p> <p>To run the code, installations of Matlab and Gurobi are required.</p>
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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.