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1,049 results for “robustness”
Accurate Flow Decomposition via Robust Integer Linear Programming
<p>Dataset created using Poisson distribution to generate imperfect flow .</p> <p>March 2024 - Update: It contains the original graph, the ground truth and the imperfect flow used for inexact and robust flow decompositions.</p>
A robust method for measuring aminoacylation through tRNA-Seq
<p>Raw data and code for processing and recreating plots shown in the associated article.</p> <p>The gzipped tar ball was split into 512 mb packs to enable easy upload/download.</p> <p>To download with <code>zenodo_get</code> run the command:</p> <p><code>pip3 install zenodo_get</code></p> <p><code>zenodo_get -r 10778311</code></p> <p>To merge and unzip run the command:</p> <p><code>cat tRNA-charge-seq.tar.gz.part-* | gunzip -c > tRNA-charge-seq.tar</code></p> <p><code>tar -xvf tRNA-charge-seq.tar</code></p>
Data from: Foraging-induced craniofacial plasticity is associated with an early, robust, and dynamic transcriptional response
<p>Phenotypic plasticity is the ability of a single genotype to vary its phenotype in response to the environment. Plasticity of the skeletal system in response to mechanical input is widely studied, but the timing of its transcriptional regulation is not well-understood. Here we used the cichlid feeding apparatus to examine the transcriptional dynamics of skeletal plasticity over time. Using three closely related species that vary in their ability to remodel bone and a panel of 11 genes, including well studied skeletal differentiation markers and newly characterized environmentally sensitive genes, we examined plasticity at 1, 2, 4 and 8 weeks following the onset of alternate foraging challenges. We found that the plastic species exhibited environment-specific bursts in gene expression at 1 week, followed by a sharp decline in levels, while the species with more limited plasticity exhibited consistently low levels of gene expression. This trend held across nearly all genes, suggesting that it is a hallmark of the larger plasticity regulatory network. We conclude that plasticity of the cichlid feeding apparatus is not the result of slowly accumulating gene expression difference over time, but rather is stimulated by early bursts of environment-specific gene expression followed by a return to homeostatic levels.</p>
OrgaMapper: A robust and easy-to-use workflow for analyzing organelle positioning
<p><span>Eukaryotic cells are highly compartmentalized by a variety of organelles that carry out specific cellular processes. The position of these organelles within the cell is elaborately regulated and vital for their function. For instance, the position of lysosomes relative to the nucleus controls their degradative capacity and is altered in pathophysiological conditions. The molecular components orchestrating the precise localization of organelles remain incompletely understood. A confounding factor in these studies is the fact that organelle positioning is surprisingly non-trivial to address. E.g., perturbations that affect the localization of organelles often lead to secondary phenotypes such as changes in cell or organelle size. These phenotypes could potentially mask effects or lead to the identification of false positive hits. To uncover and test potential molecular components at scale, accurate and easy-to-use analysis tools are required that allow robust measurements of organelle positioning. </span></p> <h2><span>Results</span></h2> <p><span>Here, we present an analysis workflow for the faithful, robust, and quantitative analysis of organelle positioning phenotypes. Our workflow consists of an easy-to-use Fiji plugin and an R Shiny App. These tools enable users without background in image or data analysis to (1) segment single cells and nuclei and to detect organelles, (2) to measure cell size and the distance between detected organelles and the nucleus, (3) to measure intensities in the organelle channel plus one additional channel, (4) to measure radial intensity profiles of organellar markers, and (5) to plot the results in informative graphs. Using simulated data and immunofluorescent images of cells in which the function of known factors for lysosome positioning has been perturbed, we show that the workflow is robust against common problems for the accurate assessment of organelle positioning such as changes of cell shape and size, organelle size and background.</span></p> <h2><span>Conclusion</span></h2> <p><span>OrgaMapper is a versatile, robust and easy-to-use automated image analysis workflow that can be utilized in microscopy-based hypothesis testing and screens. It effectively allows for the mapping of the intracellular space and thereby enables the discovery of novel regulators of organelle positioning. </span></p>
Supplementary data: Bayesian multi-exposure image fusion for robust high dynamic range ptychography
<p>Accompanying supplementary data for the paper. To download this data automatically and use the software, please refer to the details in the README of the linked github repository. </p> <p><strong>Github URL: </strong><a href="https://github.com/microscopic-image-analysis/bayes-mef"><strong>https://github.com/microscopic-image-analysis/bayes-mef</strong></a></p>
Accurate and Robust Stellar Rotation Periods catalog for 82771 Kepler stars using deep learning
<p>This repository is for the paper "Rotation Period for 83022 Kepler Stars: A Deep Learning Approach" by I. Kamai and H. B. Perets. It is associated with manuscript number AAS56501. It consists a frozen repository and the published catalog</p>
FEater dataset: A molecular fragment dataset to benchmark the robustness of 3D flexible object recognition
<p>This dataset is associated with the work: Benchmarking the robustness of the correct identification of flexible 3D objects using common machine learning models</p> <pre><code># Original FEater-Single and FEater_Dual dataset. FEater_Single ├── TestSet_coord.h5 ├── TrainingSet_coord.h5 └── ValidationSet_coord.h5 FEater_Dual ├── TestSet_coord.h5 ├── TrainingSet_coord.h5 └── ValidationSet_coord.h5 # Non-redundant baseline dataset FEater_Baseline ├── TestSet_Dual.h5 ├── TestSet_Single.h5 ├── TrainingSet_Dual.h5 └── TrainingSet_Single.h5 # FEater-Single and FEater_Dual in different sample size FEater_Mini200 ├── Mini200_Dual.h5 └── Mini200_Single.h5 FEater_Mini400 ├── Mini400_Dual.h5 └── Mini400_Single.h5 FEater_Mini800 ├── Mini800_Dual.h5 └── Mini800_Single.h5</code></pre> <p>For further details of the usage, please visit the original GitHub repository: <a title="FEater_repo" href="https://github.com/miemiemmmm/FEater" target="_blank" rel="noopener">https://github.com/miemiemmmm/FEater</a></p>
Spatial-DC: a robust deep learning-based method for deconvolution of spatial proteomics
<p>The processed reference and spatial proteomics datasets, along with the processed mIHC imaging data of mouse PDAC tissue are available in the repository.</p> <p>Also, the source code for pre-processing, data analysis, and generating figure and tables has been deposited in both GitHub [<a href="https://github.com/TencentAILabHealthcare/Spatial-DC">https://github.com/TencentAILabHealthcare/Spatial-DC</a>] and Zenodo [<a href="https://doi.org/10.5281/zenodo.14386585">https://doi.org/10.5281/zenodo.14386585</a>].</p> <p> </p>
Dataset for "Mechanically robust supramolecular polymer co-assemblies"
<p>Source data of the study reported in the publication entitled "Mechanically robust supramolecular polymer co-assemblies". The data should be considered together with the published manuscript and the supplementary information file.</p>
A multi-uncertainty-set-based robust transmission expansion planning model using an efficient linear AC network
<p>The file uploaded provides input data for the paper "A multi-uncertainty-set-based robust transmission expansion planning model using an efficient linear AC network".</p>
Code and data for Nguyen Le et al. "Robust optimal control of interacting multi-qubit systems for quantum sensing"
<p>This is the code and simulation data for the paper "Robust optimal control of interacting multi-qubit systems for quantum sensing" by Nguyen Le et al.</p>
NIOO-QingZ/Geertruidenberg_Mesocosms: Towards climate-robust water quality management: testing the efficacy of different eutrophication control measures during a heat
<p>Data and Codes used in the following open-access publication: </p> <p>https://www.sciencedirect.com/science/article/pii/S0048969722015145</p>
Robust biases in the estimation of passive yaw rotations
<p>We investigated the ability to estimate passive self-motion perception with and without external auditory sources of information. In the first experiment (1a), auditory cues were automatically delivered, while in the second experiment (1b) participants themselves generated the auditory cues. Here we share the raw dataset from the two experiments.</p>
Developmental timing of Drosophila pachea pupae is robust to temperature changes
<p>Rearing temperature is correlated with the timing and speed of development in a wide range of poikiloterm animals that do not regulate their body temperature. However, exceptions exist, especially in species that live in environments with high temperature extremes or oscillations. <em>Drosophila pachea</em> is endemic to the Sonoran desert in Mexico, in which temperatures and temperature variations are extreme. We wondered if the developmental timing in <em>D. pachea</em> may be sensitive to differing rearing temperatures or if it remains constant. We determined the overall timing of the <em>Drosophila pachea</em> life-cycle at different temperatures. The duration of pupal development was similar at 25 °C, 29 °C and 32 °C, although the relative progress differed at particular stages. Thus, <em>D. pachea</em> may have evolved mechanisms to buffer temperature effects on developmental speed, potentially to ensure proper development and individual's fitness in desert climate conditions.</p>
Robustness of organ morphology is associated with modules of co-expressed genes related to plant cell wall
<p>Reproducibility in organ size and shape is a fundamental trait of living organisms. The mechanisms underlying such robustness remain, however, to be elucidated. In the manuscript <a href="https://www.biorxiv.org/content/10.1101/2022.04.26.489498v1"><strong>"Robustness of organ morphology is associated with modules of co-expressed genes related to plant cell wall", </strong>doi: https://doi.org/10.1101/2022.04.26.489498</a>, we took the sepal of Arabidopsis as a model, and we investigated whether variability of gene expression plays a role in variation of organ morphology.</p> <p>To address this question, we produced a dataset composed of both transcriptomic and morphological information obtained from 27 individual sepals from wild-type plants.</p> <p>This repository contains the raw confocal image of 30 sepals used as starting point for the analysis, as well as their extracted contours as binary images. These images were used to recover the 3D shape of the sepals.</p> <p>The 30 abaxial sepals were collected at early stage 11, from three different Col-0 wild-type plants, labeled D, E and F, grown simultaneously in experimentally controlled standard conditions. Each sepal was imaged under a confocal microscope using autofluorescence. Immediately following imaging, the sepal was frozen in liquid nitrogen for RNA extraction, on which an RNA-seq analysis was performed.</p> <p><strong>Related informations :</strong></p> <ul> <li>The repository of the numerical tools used for 3D shape extraction as well as the results of geometrical measurements is <a href="http://forge.cbp.ens-lyon.fr/redmine/projects/florivar">here</a>.</li> <li>The repository of RNA-Seq analysis results of these same sepals is here.</li> <li>And the analysis tools used to relate geometrical measurements to RNA-seq data are here.</li> </ul>
Supplementary data for 'scROSHI - robust supervised hierarchical identification of single cells'
<p>This record contains some of the supplementary files for the manuscript "scROSHI - robust supervised hierarchical identification of single cells" by Prummer et al.</p> <p>The file "scROSHI_Fig03_counts.zip" contains SingleCellExperiment R objects as RDS files, "sce_A.RDS", "sce_B.RDS", "sce_C.RDS", corresponding to the three samples shown in Figure 3. The 'assay' slot of the SingleCellExperiment objects contains the gene x cell raw count matrix, the 'colData' slot contains the description for each cell: barcode, celltype_major, celltype_final, cnv_status.</p> <p>Please see https://github.com/ETH-NEXUS/scROSHI for code generating the cell type labels.</p>
Data from: Robust single-image tree diameter estimation with mobile phones
<p>Ground-based forest inventories are a key element of forest carbon monitoring, reporting, and verification schemes and a cornerstone of forest ecology research. Recent work using LiDAR-equipped mobile phones to automate parts of the forest inventory process assumes that tree trunks are well-spaced and visually unoccluded, or else requires manual intervention or offline processing to identify and measure tree trunks.</p> <p>In this paper, we design an algorithm that exploits a low-cost smartphone LiDAR sensor to estimate trunk diameter automatically from a single image in complex and realistic field conditions. We implement our design and build it into an app on a Huawei P30 Pro smartphone, demonstrating that the algorithm has low enough computational cost to run on this commodity platform in near real-time.</p> <p>We evaluate our app in three different forests across three seasons and find that in a corpus of 97 sample tree images, our app estimates trunk diameter with RMSE of 3.7 cm (R<sup>2</sup> = .97; 8.0% mean error) compared to manual DBH measurement. It achieves a 100% tree detection rate while reducing surveyor time by up to a factor of 4.6.</p> <p>Our work contributes to the search for a low-cost, low-expertise alternative to Terrestrial Laser Scanning that is nonetheless robust and efficient enough to compete with manual methods. We highlight the challenges that low-end mobile depth scanners face in occluded conditions and offer a lightweight, fully automatic approach for segmenting depth images and estimating trunk diameter despite these challenges. Our approach lowers the barriers to in situ forest measurement outside of an urban or plantation context, maintaining a tree detection and accuracy rate comparable to previous mobile phone methods even in complex forest conditions.</p>
Soil ecotoxicology needs robust biomarkers – a meta-analysis approach to test the robustness of gene expression-based biomarkers for measuring chemical exposure effects in soil invertebrates
<p>Gene expression-based biomarkers are regularly proposed as rapid, sensitive and mechanistically informative tools to identify whether soil invertebrates are experiencing adverse effects due to chemical exposure. However, before biomarkers could be deployed within diagnostic studies, systematic evidence of the robustness of such biomarkers to detect effects is needed. Here, we present an approach for conducting a systematic meta-analysis of the robustness of gene expression-based biomarkers in soil invertebrates.</p> <p>The approach was developed and trialled for two measurements of gene expression commonly proposed as biomarkers in soil ecotoxicology: metallothionein (MT) gene expression in earthworms for metals and heat shock protein 70 (HSP70) gene expression in earthworms for organic chemicals. From a systematic analysis of the published literature, we collected 294 unique gene expression data points and used linear mixed-effect models to assess concentration, exposure duration and species effects on the quantified response.</p> <p>This database provided contains gene-expression data from publications that have used gene expression-based biomakers to study effects of chemical pollutants on soil invertebrates. R scripts are provided that were used to study the patterns of gene expression as reported in accompanying publication. </p> <p>We encourage colleagues in the field to apply this approach to other biomarkers, as such quantitative assessment is a prerequisite to ensuring that the suitability and limitations of proposed biomarkers are known and stated.</p>
Formation of robust bound states of interacting photons
<p>Data and analysis scripts for the manuscript https://arxiv.org/abs/2206.05254</p>
Robust analysis of phylogenetic tree space
<p>Phylogenetic analyses often produce large numbers of trees. Mapping trees' distribution in "tree space" can illuminate the behavior and performance of search strategies, reveal distinct clusters of optimal trees, and expose differences between different data sources or phylogenetic methods—but the high-dimensional spaces defined by metric distances are necessarily distorted when represented in fewer dimensions. Here, I explore the consequences of this transformation in phylogenetic search results from 128 morphological data sets, using stratigraphic congruence—a complementary aspect of tree similarity—to evaluate the utility of low-dimensional mappings. I find that phylogenetic similarities between cladograms are most accurately depicted in tree spaces derived from information-theoretic tree distances or the quartet distance. Robinson–Foulds tree spaces exhibit prominent distortions and often fail to group trees according to phylogenetic similarity, whereas the strong influence of tree shape on the Kendall–Colijn distance makes its tree space unsuitable for many purposes. Distances mapped into two or even three dimensions often display little correspondence with true distances, which can lead to profound misrepresentation of clustering structure. Without explicit testing, one cannot be confident that a tree space mapping faithfully represents the true distribution of trees, nor that visually evident structure is valid. My recommendations for tree space validation and visualization are implemented in a new graphical user interface in the "TreeDist" R package.</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.