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3,264 results for “FAST”
Data from: SuperFine: fast and accurate supertree estimation
Many research groups are estimating trees containing anywhere from a few thousand to hundreds of thousands of species, towards the eventual goal of the estimation of a Tree of Life, containing perhaps as many as several million leaves. These phylogenetic estimations present enormous computational challenges, and current computational methods are likely to fail to run even on datasets in the low end of this range. One approach to estimate a large species tree is to use phylogenetic estimation methods (such as maximum likelihood) on a supermatrix produced by concatenating multiple sequence alignments for a collection of markers; however, the most accurate of these phylogenetic estimation methods are extremely computationally intensive for datasets with more than a few thousand sequences. Supertree methods, which assemble phylogenetic trees from a collection of trees on subsets of the taxa, are important tools for phylogeny estimation where phylogenetic analyses based upon maximum likelihood are infeasible. In this paper, we introduce SuperFine, a meta-method that utilizes a novel two-step procedure in order to improve the accuracy and scalability of supertree methods. Our study, using both simulated and empirical data, shows that SuperFine-boosted supertree methods produce more accurate trees than standard supertree methods, and run quickly on very datasets with thousands of sequences. Furthermore, SuperFine-boosted MRP (Matrix Representation with Parsimony, the most well known supertree method) approaches the accuracy of maximum likelihood methods on supermatrix datasets under realistic conditions.
Data from: Aging, mortality, and the fast growth trade-off of Schizosaccharomyces pombe
Replicative aging has been demonstrated in asymmetrically dividing unicellular organisms, seemingly caused by unequal damage partitioning. Although asymmetric segregation and inheritance of potential aging factors also occurs in symmetrically dividing species, it nevertheless remains controversial whether this results in aging. Based on large-scale single-cell lineage data obtained by time-lapse microscopy with a microfluidic device, in this report, we demonstrate the absence of replicative aging in old-pole cell lineages of Schizosaccharomyces pombe cultured under constant favorable conditions. By monitoring more than 1,500 cell lineages in seven different culture conditions, we showed that both cell division and death rates are remarkably constant for at least 50–80 generations. Our measurements revealed that the death rate per cellular generation increases with division rate, pointing to a physiological trade-off with fast growth under balanced growth conditions. We also observed the formation and inheritance of Hsp104-associated protein aggregates, which are a potential aging factor in old-pole cell lineages, and found that these aggregates exhibited a tendency to preferentially remain at the old-poles for several generations. However, the aggregates were eventually segregated from old-pole cells upon cell division and probabilistically allocated to new-pole cells. We found that cell deaths were typically preceded by sudden acceleration of protein aggregation, thus relatively large amount of protein aggregates existed at the very ends of the dead cell lineages. Our lineage tracking analyses, however, revealed that the quantity and inheritance of protein aggregates increased neither cellular generation time nor cell death initiation rates. Furthermore, our results demonstrated that unusually large amounts of protein aggregates induced by oxidative stress exposure did not result in aging; old-pole cells resumed normal growth upon stress removal, despite the fact that most of them inherited significant quantities of aggregates. These results collectively indicate that protein aggregates are not a major determinant of triggering cell death in S. pombe, and thus cannot be an appropriate molecular marker or index for replicative aging under both favorable and stressful environmental conditions.
Data analysis and benchmark results for: "hictk: blazing fast toolkit to work with .hic and .cool files"
<p><strong>README</strong></p> <p>Data found in this dataset was generated as part of the following publication: "hictk: blazing fast toolkit to work with .hic and .cool files" (preprint available soon).<br><br>The data analysis pipeline used to generate the data is hosted on GitHub at <a href="https://github.com/paulsengroup/2023-hictk-paper">github.com/paulsengroup/2023-hictk-paper</a> and archived on Zenodo <a href="https://doi.org/10.5281/zenodo.10868277">doi.org/10.5281/zenodo.10868277</a>.</p> <p>Refer to the README found in the .zip file for more information on how the data is organized.</p> <p><strong>Contact information</strong></p> <p>Inquiries regarding this dataset should be addressed to the corresponding author for "hictk: blazing fast toolkit to work with .hic and .cool files" (Jonas Paulsen).</p>
Review of Breast Cancer Prognosis MicroRNAslncRNAs, Obesity, The LPR6 Biomarker, and Night Fasting
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Evaluation of the CaloINN generative network - Fast detector simulation
<p>These are the sampled used in the paper "Normalizing Flows for High-Dimensional Detector Simulations" for the evaluation of the CaloINN and the CaloVAE+INN models.</p> <p>Each zip file contains the generated showers stored in the CaloChallenge format together with figures of high-level observables.</p> <p>We include the layer energy deposition, the center of energy, the width of the center of energy, the layer sparsity, the ratio E_tot/E_inc, and the full voxel energy distribution.</p> <p>For these features we provide:</p> <ul> <li>energy inclusive histograms for all the datasets;</li> <li>for dataset 1, three incident energies: 256 MeV, 8.192GeV, 262.144 GeV;</li> <li>for dataset 2 and 3, three incident energy windows, (1-10), (10-100), (100-1000) GeV;</li> <li>separation power between Geant4 and our samples calculatd from the histograms.</li> </ul>
Effect of a modified 5:2 intermittent fasting diet on population with overweight or obesity in China: A self-controlled clinical trial
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Data Repository: Fast Single-Particle Tracking of Membrane Proteins Combined with Super-Resolution Imaging of Actin Nanodomains
<p>This repository contains a collection of correlated 2D super-resolution images obtained through single molecule localization microscopy and 3D time series of single particle tracking data of membrane proteins. By utilizing high-speed fluorescent microscopy, we tracked a transmembrane protein – the high-affinity IgE receptor – and an outer-leaflet protein – GPI-anchored protein – at the frame rate of 490 Hz. Subsequently, actin structures of the same cells were captured using a super-resolution microscopy (dSTORM technique). Additionally, this dataset includes Technical Validation to support the transition from live-cell imaging to fixed-cell imaging when adding fixation buffers. </p> <p>The data was classified as “Class I” and “Class II” describing two categories of RBL-2H3 cells. In "Class I", the cells were untransfected. In “Class II”, the cells were transfected to express GFP-GPI-anchored fusion protein. The zip folder names that include “IgE Untreated” include image time series of fluorescently labeled IgE receptors in untreated RBL-2H3 cells and image series of corresponding super-resolution imaging of fluorescently labeled actin filaments of the same cell in “SRImage” folder.</p> <p>The data with folder names including with “IgE Treated” are image time series of fluorescently labeled IgE receptors in either phalloidin- or PMA-treated RBL-2H3 cells and corresponding image series of super-resolution imaging of fluorescently labeled actin filaments in the same cell.</p> <p>Similarly, the data with folder names starting with “GPI Untreated” are image time series of fluorescently labeled GPI-anchored proteins in untreated RBL-2H3 cells and corresponding image series of super-resolution imaging of fluorescently labeled actin filaments in the same cell.</p> <p>The data with folder names starting with “GPI Treated” are image time series of fluorescently labeled GPI-anchored proteins in phalloidin treated RBL-2H3 cells and corresponding image series of super-resolution imaging of fluorescently labeled actin filaments in the same cell.</p> <p>The number within each folder name represents an individual experiment and the corresponding data collected under the same conditions.</p> <p>For all experiments an IR movie was added to monitor the cell morphology during live-cell image and adding initial fixation buffer and it was saved in the tracking file. </p> <p>The HDF5 files of all data are available in the second version of this repository. For each sample, there are two files: "Tracking.h5" and "SuperResolution_actin.h5". The "Tracking" files include two groups: single-particle tracking data and IR images during tracking. The "SuperResolution_actin" files contain two groups: super-resolution images of actin filaments and IR reference images for image registeration and drift correction during data collection. </p> <p> </p> <p> </p> <p> </p>
Replication data for fast quantum key distribution
<p>The dataset contains experimental measurements (photon counts) of a polarization-based quantum channel equipped with different configurations.</p> <p> </p>
BLEND: A Fast, Memory-Efficient, and Accurate Mechanism to Find Fuzzy Seed Matches (e.coli-pb-sequelii)
<p><strong>e.coli-pb-sequelii</strong></p> <p>E. Coli PacBio HiFi reads (100X coverage)</p> <p>Please see the README inside the directory. The depth of coverage is downsampled to 100X. We provide the data that we use in our BLEND submission.</p> <p> </p> <p>Original read sets: https://www.ebi.ac.uk/ena/browser/view/PRJNA602597?show=reads</p> <p>Paper that produced the original read sets: https://academic.oup.com/g3journal/article/11/6/jkab083/6188627#304735528</p>
BLEND: A Fast, Memory-Efficient, and Accurate Mechanism to Find Fuzzy Seed Matches (Figures)
<p>We provide the source to generate the figures and PDFs we use in the BLEND submission</p>
BLEND: A Fast, Memory-Efficient, and Accurate Mechanism to Find Fuzzy Seed Matches (d.ananassae-pb-sequelii)
<p><strong>d.ananassae-pb-sequelii</strong></p> <p>D. ananassae PacBio HiFi reads (50X) and the reference genome used in our BLEND submission.</p> <p> </p> <p>Original read sets: https://www.ebi.ac.uk/ena/browser/view/PRJNA602597?show=reads</p> <p>Paper that produced the original read sets: https://academic.oup.com/g3journal/article/11/6/jkab083/6188627#304735528</p>
MOJITOO: a fast and universal method for integration of multimodal single cell data
<p>MOJITOO benchmarking seurat Robjects.</p>
Fast likelihood calculations for automatic identification of macroevolutionary rate heterogeneity in continuous and discrete traits
<p>Understanding phenotypic disparity across the tree of life requires identifying where and when evolutionary rates change on phylogeny. A primary methodological challenge in macroevolution is therefore to develop methods for accurate inference of among-lineage variation in rates of phenotypic evolution. Here, we describe a method for inferring among-lineage evolutionary rate heterogeneity in both continuous and discrete traits. The method assumes that the present-day distribution of a trait is shaped by a variable-rate process arising from a mixture of constant-rate processes and uses a single-pass tree traversal algorithm to estimate branch-specific evolutionary rates. By employing dynamic programming optimization techniques and approximate maximum likelihood estimators where appropriate, our method permits rapid exploration of the tempo and mode of phenotypic evolution. Simulations indicate that the method reconstructs rates of trait evolution with high accuracy. Application of the method to datasets on squamate reptile reproduction and turtle body size recovers patterns of rate heterogeneity identified by previous studies but with computational costs reduced by many orders of magnitude. Our results expand the set of tools available for detecting macroevolutionary rate heterogeneity and point to the utility of fast, approximate methods for studying large scale biodiversity dynamics.</p>
Genome-wide DNA methylation analysis in monozygotic twins identifies potential biomarkers of fasting plasma glucose
<p><strong><span>Purpose:</span></strong><span> An epigenome-wide association study (EWAS) was conducted to detect specific epigenetic variants potentially related to fasting plasma glucose (FPG) in middle-aged and elderly Chinese monozygotic twins.</span></p> <p><span><strong>Methods:</strong> </span><span>Association between DNA methylation (DNAm) of single CpG and FPG was tested by applying generalized estimation equation in 52 twin pairs. Differentially methylated regions (DMRs) were identified by</span><em> <span>comb-P</span></em> <span>approach</span><span>. Inference about Causation through Examination of Familial Confounding (ICE FALCON) was utilized to perform the causal inference. Candidate CpGs were quantified using Sequenom MassARRAY platform in a community population. Weighted gene co-expression network analysis (WGCNA) was conducted using gene expression data. </span></p> <p><span><strong>Results</strong>: </span><span>The relationship between DNAm of 30 top CpGs and FPG reached <em>P</em>-value</span><span><</span><span>1×10<sup>-6</sup></span><span> level. Thirty-two DMRs within 24 genes, such as TLCD1, MRPS31P5, </span><span>CASZ1 </span><span>and CXADRP3, were identified. Causal relationship of 20 top CpGs within <em>TLCD1, MZF1, PTPRN2, SLC6A18, ASTN2, IQCA1, GRIN1</em>, and <em>PDE2A </em>with FPG were further identified. Pathways related to FPG such as mitogen-activated protein kinase p38 binding were found. Three CpGs mapped to <em>SLC6A18 </em>were</span><span> validated in a community population, with </span><span>a hypermethylated direction in type 2 diabetes cases. The gene expression levels of 18 genes where the top CpGs and DMRs located, such as <em>SLC6A18 </em>and <em>TLCD1</em>, were positively correlated with FPG. Besides, common biological pathways, such as dopamine binding, regulation of biosynthetic process, and neuron fate specification, were found in methylation and gene expression analyses.</span></p> <p><span><strong>Conclusion</strong>: </span><span>Our findings showed that</span> <span>multiple methylated CpGs and regions, crucial genes, and biological pathways were underlyingly associated with FPG and diabetes.</span></p>
Robust and fast post-processing of single-shot spin qubit detection events with a neural network
<p>Dataset to the paper 'Robust and fast post-processing of single-shot spin qubit detection events with a neural network'</p>
Fast domain-wall and skyrmion logic in a chirally coupled ferrimagnet
Open the record for dataset details and reuse information.
Dataset and code for Fast sequence alignment for centromere with RaMA
<p>Dataset and code for Fast sequence alignment for centromere with RaMA</p>
Planning Fast-Charging Infrastructure for Long-Haul Electric Trucks
<p>Dataset</p>
Imada Fasting Cancer - single cell RNA-Seq Processed Data R object
Open the record for dataset details and reuse information.
Figure 2 in The fast-calling short-tailed cricket Anurogryllus celerinictus Walker, 1973 (Orthoptera: Gryllidae) occurs in Cuba, Greater Antilles
Figure 2. Live Anurogryllus celerinictus from Cuba, photographed in nocturnal activity at nature: a) adult male, calling on a street curb; b) "long-winged" male, feeding on a grass root; c) "short-winged" male, retreating into its self-dug burrow after being disturbed; d) adult male, using a crack in the wall baseboard as burrow.
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.