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990 results for “quantification”
Data from: Quantification of collective behaviour via causality analysis
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SPIKEPIPE: A metagenomic pipeline for the accurate quantification of eukaryotic species occurrences and intraspecific abundance change using DNA barcodes or mitogenomes
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Tassie BRUV: A benchmark data set for computer vision and movement quantification algorithms
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Quantification of Food Waste Disposal in the United States: A Meta-Analysis
This data set is the result of a systematic review of studies on food waste disposed in the United States, an issue which major consequences for social, nutritional, economic, and environmental issues. It was created to determine how much food is discarded in the U.S., and to determine if specific factors drive increased disposal. By applying meta-analytic tools on it this dataset, it was found that the aggregate proportion of food waste in U.S. municipal solid waste from 1995 to 2013 was 0.147 (95% CI 0.137–0.157) of total disposed waste, which is lower than that estimated by U.S. Environmental Protection Agency for the same period (0.176). Further, that the proportion of food waste increased significantly with time, and there were no significant differences in food waste between rural and urban samples, or between commercial/institutional and residential samples. These results are published in the study titled Quantification of Food Waste Disposal in the United States: A Meta-Analysis (Thyberg et al., 2015).
Data for Precursor intensity-based label-free quantification software tools for Galaxy Platform.
<p><strong>Precursor intensity-based label-free quantification software tools for proteomic and multi-omic analysis within the Galaxy Platform.</strong></p> <p> </p> <p><strong>ABRF:</strong> Data was generated through the collaborative work of the ABRF Proteomics Research Group (<a href="https://abrf.org/research-group/proteomics-research-group-prg">https://abrf.org/research-group/proteomics-research-group-prg</a>). See Reference for details: Van Riper, S. et al. ‘<a href="http://cbs.umn.edu/sites/cbs.umn.edu/files/public/downloads/2016_ABRF_PRG_Poster_for_ASMS_20160501.pdf">An ABRF-PRG study: Identification of low abundance proteins in a highly complex protein sample</a>’ at the 64th Annual Conference of American Society of Mass Spectrometry and Allied Topics" at San Antonio, TX."</p> <p><strong>UPS:</strong> <strong>MaxLFQ Cox J, Hein MY, Luber CA, Paron I, Nagaraj N, Mann M.<a href="https://www.ncbi.nlm.nih.gov/pubmed/24942700/"> Accurate proteome-wide label-free quantification by delayed normalization and maximal peptide ratio extraction, termed MaxLFQ.</a> Mol Cell Proteomics. 2014 Sep;13(9):2513-26. doi: 10.1074/mcp.M113.031591. Epub 2014 Jun 17. PubMed PMID: 24942700; PubMed Central PMCID: PMC4159666;</strong></p> <p><strong>PRIDE #5412; ProteomeXchange repository PXD000279: </strong>ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2014/09/PXD000279</p>
Dataset for NMR quadrature echo and T1 saturation recovery pulse sequences underlying the publication 'On the quantification of solid phases in hydrated cement paste by 1H nuclear magnetic resonance relaxometry'
<p>This record comprises the datasets of combined 1H NMR quadrature echo and T1 saturation recovery pulse sequences underlying the publication “On the quantification of solid phases in hydrated cement paste by 1H nuclear magnetic resonance relaxometry” by Robert Schulte Holthausen & Peter J. McDonald, Cement and Concrete Research, https://doi.org/10.1016/j.cemconres.2020.106095.</p> <p><br> In this work different solid phases, important to cement paste hydration, are investigated with low-field bench top 1H nuclear magnetic resonance with a view to developing an alternate characterisation methodology that requires minimal invasive or destructive sample preparation.</p> <p><br> A combination of the well-established quadrature echo pulse sequence with variable pulse gap together with a T1 saturation recovery quadrature echo pulse sequence is used.</p>
Noninvasive quantification of axon radii using diffusion MRI
<p>Axon size plays a crucial role in determining conductance velocity and, consequently, in the the timing and synchronization of neural activation. Noninvasive measurement of axon radii could have significant impact on the understanding of healthy and diseased neural processes. However, until now, accurate axon radius mapping has eluded in vivo neuroimaging, mainly due to a lack of sensitivity of the MRI signal to micron-sized axons. Here, we show how -- when confounding factors such as extra-axonal water and axonal orientation dispersion are eliminated -- heavily diffusion-weighted MRI signals becomes sensitive to axon radii. However, diffusion MRI is only capable of estimating a single metric representing the entire axon radius distribution within a voxel that emphasizes the largest axons. Our findings, both in rodents and humans, enable noninvasive mapping of critical information on axon radii, as well as resolve the long-standing debate on whether axon radii can be quantified.</p>
Quantification of stroke lesion volume using epidural EEG in a cerebral ischaemic rat model
<p>We have uploaded the dataset of rat EEG in response to the specific sound stimuli. The dataset includes rat EEG of normal subjects (n = 10), mild (n = 7), moderate (n = 7), and severe (n = 7) right auditory cortical infarction subjects. </p> <p>The dataset can be analyzed using MATLAB software. For power spectrum density (PSD) analysis of the data, we used the zero-phase forward and reverse Infinite Impulse Response Butterworth filter of 4th order. Further, we averaged the last 300 ms of the signal before stimulus onset as a baseline correction. Next, we down-sampled the data from 1,200 to 600 Hz. Subsequently, we conducted the PSD analysis using signals obtained from the target stimulus onset to 1 s using Welch’s method, which is one of the most widely used periodogram methods for determining the power density of EEG frequency components. The parameter was set to divide the EEG signals into eight sections of equal length, each with a 50% overlap based on the Hamming window. We defined the frequency range for each band as follows: Delta (1-4 Hz), theta (4-8 Hz), alpha (8-12 Hz), and beta (12-30 Hz). We calculated the relative power for each frequency band by summing all of the absolute PSD values across the four bands to compute the total power followed by dividing the absolute value for each frequency band with the total power. Finally, we calculated the DAR (delta/alpha ratio) and the DTABR ((delta + theta) / (alpha + beta) ratio), which were computed by the relative power of the relevant frequency bands. Further, we analysed AEPs in response to the target sound stimuli by averaging all of the epochs between 300 ms before the stimuli onset to 500 ms after it. The AEP amplitude was defined as the highest recorded voltage following the sound stimulus. The latency of the components of the AEPs was defined as the duration from stimulus onset to the peak amplitude.</p>
Sentiment Quantification Datasets
<p>These files are contain the tokenized reviews that are used for quantication experiments on text.</p> <p>IMDB is derived from the IMDB dataset from Maas et al., 2011 (https://ai.stanford.edu/~amaas/data/sentiment/).<br> The version of the IMDB content in this dataset has minimal processing with respect to the original dataset, yet, it is provided to unsure reproducibility of experiments.</p> <p>HP and Kindle dataset are Amazon reviews collected by the authors. The reviews are respectively about the books in the Harry Potter series, and about the Kindle e-book reader.</p>
I2K2020 Data for "Quantification of the 3D brain vasculature in zebrafish light sheet fluorescence microscopy data"
<p>Example data for the I2K2020 tutorial "Quantification of the 3D brain vasculature in zebrafish light sheet fluorescence microscopy data" (https://www.janelia.org/you-janelia/conferences/from-images-to-knowledge-with-imagej-friends/virtual-workshop-program)</p> <p>"Readme" file for data description included in folder.</p> <p><strong>Background:</strong> Zebrafish transgenic lines and light sheet fluorescence microscopy (LSFM) allow unrivalled insights into vascular development <em>in vivo</em> and 3D. The vascular architecture can be used to describe physiological status. However, assessment of the vasculature still relies on individual visual assessment rather than objective quantification. Thus, an image analysis pipeline is required to allow data assessment in 3D robustly and sensitively, while being able to handle LSFM data.</p> <p>Kugler et al have produced an image analysis workflow to quantify the zebrafish brain vasculature in 3D (https://www.biorxiv.org/content/10.1101/2020.08.06.239905v2).</p> <p><strong>Aim</strong>: In this tutorial we will use the analysis workflow produced by Kugler et al to examine and quantify the zebrafish brain vasculature in 3D with a hands-on practical (https://github.com/ElisabethKugler/ZFVascularQuantification).</p>
Amyloid burden quantification depends on PET and MR image processing methodology
<p>The enclosed datasets refer to the work developed at the University Medical Center Groningen and consist of the minimally required PET image data to replicate the results of the study entitled "Amyloid burden quantification depends on PET and MR image processing methodology" which abstract can be found below:</p> <blockquote> <p>Quantification of amyloid load with positron emission tomography can be useful to assess Alzheimer’s Disease <em>in-vivo. </em>However, quantification can be affected by the image processing methodology applied. This study’s goal was to address how amyloid quantification is influenced by different semi-automatic image processing pipelines. Images were analysed in their <em>Native Space </em>and <em>Standard Space</em>; non-rigid spatial transformation methods based on maximum a posteriori approaches and tissue probability maps (TPM) for regularisation were explored. Furthermore, grey matter tissue segmentations were defined before and after spatial normalisation, and also using a population-based template. Five quantification metrics were analysed: two intensity-based, two volumetric-based, and one multi-parametric feature.</p> <p>Intensity-related metrics were not meaningfully affected by spatial normalisation and did not significantly depend on the grey matter segmentation method, with an impact similar to that expected from test-retest studies (≤10%). Yet, volumetric and multi-parametric features were sensitive to the image processing methodology, with an overall variability up to 45%. Therefore, the analysis should be carried out in <em>Native Space</em> avoiding non-rigid spatial transformations. For analyses in <em>Standard Space</em>, spatial normalisation regularised by TPM is preferred. Volumetric-based measurements should be done in <em>Native Space,</em> while intensity-based metrics are more robust against differences in image processing pipelines.</p> </blockquote>
Quantification of uncertainties introduced by data-processing procedures of sap flow measurements using the cut-tree method on a large mature tree
<p>Motivation: Sap flow sensors are crucial instruments to understand whole-tree water use. The lack of direct calibration of the available methods on large trees and the application of several data-processing procedures may jeopardize our understanding of water uptake dynamics by increasing the uncertainties around sensor-based estimates. We directly compared the heat ratio method (HRM) sap flow measurements to water uptake measured gravimetrically using the cut-tree method on a large mature aspen tree to quantify those uncertainties for ten consecutive days.</p> <p>Dataset: In this dataset, we provide sap flux density (ten-minutes intervals; g.cm-2.hr-1; corrected for wounding and sapwood thermal diffusivity) obtained from four HRM sap flow sensors installed at 2.5 m high on the focus tree (20 m tall, 60 years old trembling aspen in the boreal mixedwood region of Alberta) between July 18th and August 22nd 2017. We present the code and data (weather data from neighboring weather station) used to calculate whole-tree sap flux (L.hr-1) from each of the individual sensors using different methods of radial integration of sap flux density across the sapwood area estimated via different calculations, as well as different zero-flow corrections used. The cut-tree procedure was applied to the focus tree, and gravimetric measurements of water uptake (ten-minutes intervals) were made using a recording scale. We directly compared the different estimates of hourly, daily and cumulative sap flows obtained with gravimetric measurement of water uptake. We present the code providing the statistical analysis and results reported in the associated publication (Merlin, M., Solarik, K.A., Landhäusser, S.M. Quantification of uncertainties introduced by data-processing procedures of sap flow measurements using the cut-tree method on a large mature tree. 2020. Agricultural and Forest Meteorology, http://dx.doi.org/10.1016/j.agrformet.2020.107926)</p>
Data from: Bayesian quantification of ecological determinants of outcrossing in natural plant populations: computer simulations and the case study of biparental inbreeding in English yew
The mating system is a central parameter of plant biology because it shapes their ecological and evolutionary properties. Therefore, determining ecological variables that influence the mating system is important for a deeper understanding of the functioning of plant populations. Here, using old concepts and recent statistical developments, we propose a new statistical tool to make inferences about ecological determinants of outcrossing in natural plant populations. The method requires co-dominant genotypes of seeds collected from maternal plants within different locations. Using extensive computer simulations, we demonstrated that the method is robust to the issues expected for real-world data, including the Wahlund effect, inbreeding and genotyping errors such as allele dropout and allele misclassification. Furthermore, we showed that the estimates of ecological effects and outcrossing rates can be severely biased if genotyping errors and genetic differentiation are not treated explicitly. Application of the new method to the case study of a dioecious tree (Taxus baccata) allowed revealing that female trees that grow in lower local densities have a greater tendency towards mating with relatives. Moreover, we also demonstrated that biparental inbreeding is higher in populations that are characterised by a longer mean distance between trees and a smaller mean trunk perimeter. We found these results to agree with both the theoretical predictions and the history of English yew.
Data from: nlstimedist: an R package for the biologically meaningful quantification of unimodal phenology distributions
Phenological investigation can provide valuable insights into the ecological effects of climate change. Appropriate modelling of the time distribution of phenological events is key to determining the nature of any changes, as well as the driving mechanisms behind those changes. Here we present the nlstimedist R package, a distribution function and modelling framework that describes the temporal dynamics of unimodal phenological events. The distribution function is derived from first principles and generates three biologically interpretable parameters. Using seed germination at different temperatures as an example, we show how the influence of environmental factors on a phenological process can be determined from the quantitative model parameters. The value of this model is its ability to represent various unimodal temporal processes statistically. The three intuitively meaningful parameters of the model can make useful comparisons between different time periods, geographical locations or species' populations, in turn allowing exploration of possible causes.
Code and Data for Examining the Quantification Capability of Automated Mineralogy System
<p>This package contains the code and data supporting a study that examined the quantification performance of automated mineralogy systems.</p>
Data for "Observation and quantification of the pseudogap in unitary Fermi gases"
<p>This dataset is for research article "Observation and quantification of the pseudogap in unitary Fermi gases".</p>
NextClone and CloneDetective: An Integrated Nextflow Pipeline and R Package for Clonal Barcode Extraction and Quantification
<p>Raw FASTQ files for the DNA-seq data required to replicate the analyses presented at: https://phipsonlab.github.io/NextClone-analysis/.</p>
Intrusive and Non-Intrusive Uncertainty Quantification Methodologies for Pyrolysis Modeling
<p>This repository contains python scripts and results for uncertainty analysis of Arrhenius equation with kinetic parameters as uncertain. The data set contains folders for each PMMA variant (1,2 and 3) used for uncertainty quantification (UQ) and 'Misc' folder containing miscellaneous files and scripts used in the study. </p> <p>Each PMMA variant folder has further sub-folders for the UQ methods implemented:</p> <ol> <li>Intrusive polynomial chaos (IPC)</li> <li>Monte Carlo (MC)</li> <li>Non-intrusive polynomial chaos (NIPC)</li> </ol> <p>Additionally convergence and comparison for the UQ methods is available in sub-folders of the same name respectively.</p> <p>The python file 'UoWu_noLatex.mplstyle' for plotting style used by us is attached to ease the rerunning of the scripts.</p>
Bi-fidelity Variational Auto-encoder for Uncertainty Quantification: Experimental Data
<p>Quantifying the uncertainty of quantities of interest (QoIs) from physical systems is a primary objective in model validation. However, achieving this goal entails balancing the need for computational efficiency with the requirement for numerical accuracy. To address this trade-off, we propose a novel bi-fidelity formulation of variational auto-encoders (BF-VAE) designed to estimate the uncertainty associated with a QoI from low-fidelity (LF) and high-fidelity (HF) samples of the QoI. This model allows for the approximation of the statistics of the HF QoI by leveraging information derived from its LF counterpart. Specifically, we design a bi-fidelity auto-regressive model in the latent space that is integrated within the VAE's probabilistic encoder-decoder structure. An effective algorithm is proposed to maximize the variational lower bound of the HF log-likelihood in the presence of limited HF data, resulting in the synthesis of HF realizations with a reduced computational cost. Additionally, we introduce the concept of the bi-fidelity information bottleneck (BF-IB) to provide an information-theoretic interpretation of the proposed BF-VAE model. Our numerical results demonstrate that BF-VAE leads to considerably improved accuracy, as compared to a VAE trained using only HF data, when limited HF data is available.</p>
Quantification of phosphorylated metabolites, organic acids, and intermediates of the TCA cycle using capillary ion chromatography tandem mass spectrometry (capIC-MS/MS) following treatment of Escherichia coli with ciprofloxacin
<p>Capillary ion chromatography tandem mass spectrometry (capIC-MS/MS) was used to quantify phosphorylated metabolites, organic acids, and intermediates of the TCA cycle of Escherichia coli treated with ciprofloxacin, BTP-001 (a novel antimicrobial peptide), and a combination of the two . Metabolite extracts were analyzed with a Xevo TQ-XS triple quadrupole mass spectrometer (Waters, USA).</p><p>Samples were gathered from E. coli cultures grown in batch cultivations using 1 liter bioreactors. Briefly, intracellular metabolites were extracted by cycling samples between −20 °C EtOH and N2 (<i>l</i>) in three consecutive freeze–thaw cycles, with vortexing every 10 min during the thawing phase. Filters were removed and the cell debris was pelleted (4500 rcf, 10 min, -9 °C). The supernatants were transferred to a new tube, snap frozen in N2 (<i>l</i>), and lyophilized. Lyophilized extracts were reconstituted in 500 µL cold Milli-Q H2O and cleared by spin-filtration with a 10 kDa molecular cutoff (20817 rcf, 10 min, 0 °C). A mix of 80 µL centrifuged sample and 20 µL 13C-labeled ISTD extract from yeast was sent to analysis. </p><p>Data processing and absolute quantification was performed as earlier described using the TargetLynx application manager of MassLynx v 4.1 (Waters) to interpolate calibration curves made with appropriate dilutions of analytical grade standards (Sigma-Aldrich). The response factor of the corresponding U13C-isotopologues were used to correct the standard and sample extract response factors. Extract concentrations were normalized to the CDW, which was calculated from interpolation of the OD600 vs. CDW (g/L) curve. </p><p>Further statistical analysis in MetaboAnalyst v 5.0 replaced missing values with 1/5 of the minimum value of the respective metabolite. An unpaired T-test with unequal variance determined differential enriched metabolites with a false discovery rate (FDR) < 0.05 which are presented as log2 fold-change compared to control. </p>
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.