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573 results for “Structure analysis”
Snapshots, frequency contact maps analysis, Poisson Boltzmann calculations, and data scripts for characterization of structural and energetic differences between conformations of the SARS-CoV-2 spike protein
<p><strong>Molecular dynamics simulation</strong> trajectories, which have been performed using the Amber ff14SB force field running with the Amber18 package at the NSF-funded (OAC-1826915, OAC-1828163) ELSA high performance computing cluster at The College of New Jersey. Simulation methodology and further details are described in [1] and [2]. For further details on the trajectories, please contact Joseph Baker (bakerj@tcnj.edu).</p> <p>The <strong>Poisson Boltzmann </strong>energy calculations have been achieved by using the input_files.tar.xz found here and solving the Poisson Boltzmann equation with pygbe. A more detailed example and tutorial can be found at [4]. For further details contact Horacio V Guzman.</p> <p><strong>The dataset contains </strong></p> <ul> <li><strong>A total of 30 snapshots of the three trajectories (10 snapshots each system = two per replica x 5 replicas/system):</strong></li> </ul> <ol> <li>SARS-CoV-2002 spike protein with three RBD in the down positions: "COV2-DDD/PDB/" .</li> <li>SARS-CoV-2002 spike protein with one RBD in the up and two RBD in the down positions: "COV2-UDD/PDB/".</li> <li>SARS-CoV-2002 spike protein with two RBD in the up and one RBD in the down positions: "COV2-DUU/PDB/".</li> </ol> <ul> <li><strong>Input files for Poisson-Boltzmann analysis</strong>:</li> </ul> <ol> <li>PoissonBoltzmann/input_files.tar.xz</li> </ol> <ul> <li><strong>Data for the frequency contact map and processing scripts</strong>:</li> </ul> <ol> <li>cov2-ddd.pdb, cov2-udd.pdb, cov2-duu.pdb reference PDB files.</li> <li>Contact maps [3] at "COV2-DDD/CONTACT_MAP/", "COV2-UDD/CONTACT_MAP/", "COV2-DUU/CONTACT_MAP/".</li> <li>frequency.lua: get frequency of contacts from a set of contacts map files.</li> <li>diff_frequency.lua: get differential frequency of contacts from a set of frequency files.</li> <li>Frequency of contacts listed in frequency.data files at "COV2-DDD/", "COV2-UDD/" and "COV2-DUU/" directories.</li> </ol> <p>Read the "INFO" files for further informations.</p> <p>This dataset and the code is part of a collaboration between:</p> <ul> <li>The Institute of Fundamental Technological Research, Polish Academy of Sciences, Warsaw, Poland (supported by the National Science Centre, Poland, under grant No. 2017/26/D/NZ1/0046)</li> <li>Department of Chemistry, The College of New Jersey, New Jersey, United States (supported by National Science Foundation under grant numbers OAC-1826915 and OAC-1828163).</li> <li>Jozef Stefan Institute, Ljubljana, Slovenia (supported by the Slovenian Research Agency (Funding No. P1-0055)).</li> <li>School of engineering in bioinformatics, University of Talca, Talca, Chile.</li> </ul> <p>[1] Rodrigo A. Moreira, Mateusz Chwastyk, Joseph L. Baker, Horacio V Guzman, & Adolfo B. Poma. (2020). All-atom simulations snapshots and contact maps analysis scripts for SARS-CoV-2002 and SARS-CoV-2 spike proteins with and without ACE2 enzyme (Version 0.1) [Data set]. Zenodo. http://doi.org/10.5281/zenodo.3817447</p> <p>[2] Chad W. Hopkins, Scott Le Grand, Ross C. Walker, and Adrian E. Roitberg. Long-Time-Step Molecular Dynamics through Hydrogen Mass Repartitioning. Journal of Chemical Theory and Computation 2015 11 (4), 1864-1874. http://doi.org/10.1021/ct5010406</p> <p>[3] Rodrigo A. Moreira, Mateusz Chwastyk, Joseph L. Baker, Horacio V Guzman, & Adolfo B. Poma. Quantitative determination of mechanical stability in the novel coronavirus spike protein. Nanoscale, 2020,12, 16409-16413. <a href="https://doi.org/10.1039/D0NR03969A">https://doi.org/10.1039/D0NR03969A</a></p> <p>[4] https://github.com/pyF4all</p>
Data from: Bringing multivariate support to multiscale codependence analysis: assessing the drivers of community structure across spatial scales
1. Multiscale codependence analysis (MCA) quantifies the joint spatial distribution of a pair of variables in order to provide a spatially-explicit assessment of their relationships to one another. For the sake of simplicity, the original definition of MCA only considered a single response variable (e.g. a single species). However, that definition would limit the application of MCA when many response variables are studied jointly, for example when one wants to study the effect of the environment on the spatial organisation of a multi-species community in an explicit manner. 2. In the present paper, we generalize MCA to multiple response variables. We conducted a simulation study to assess the statistical properties (i.e. type I error rate and statistical power) of multivariate MCA (mMCA) and found that it had honest type I error rate and sufficient statistical power for practical purposes, even with modest sample sizes. We also exemplified mMCA by applying it to two ecological data sets. 3. The simulation study confirmed the adequacy of mMCA from a statistical standpoint: it has honest type I error rates and sufficient power to be useful in practice. Using mMCA, we were able to detect variation in fish community structure along the Doubs River (in France), which was associated with large spatial structures in the variation of physical and chemical variables related to water quality. Also, mMCA usefully described the spatial variation of an Oribatid mite community structure associated with a gradient of water content superimposed on various smaller-scale spatial features associated with vegetation cover in the peat blanket surrounding Lac Geai (in Québec, Canada). 4. In addition to demonstrating the soundness of mMCA in theory and practice, we further discuss the strengths and assumptions of mMCA and describe other potential scenarios where it would be helpful to biologists interested in assessing influence of environmental conditions on community structure in a spatially-explicit way.
Data from: Pan-genome analysis highlights the role of structural variation in the evolution and environmental adaptation of Asian honeybees
<p>The <em>Asian honeybee</em>, <em>Apis cerana</em>, is an ecologically and economically important pollinator. Mapping its genetic variation is key to understanding population-level health, histories, and potential capacities to respond to environmental changes. However, most efforts to date were focused on single nucleotide polymorphisms (SNPs) based on a single reference genome, thereby ignoring larger-scale genomic variation. We employed long-read sequencing technologies to generate a chromosome-scale reference genome for the ancestral group of<em> A. cerana</em>. Integrating this with 525 resequencing datasets, we constructed the first pan-genome of <em>A. cerana</em>, encompassing almost the entire gene content. We found that 31.32% of genes in the pan-genome were variably present across populations, providing a broad gene pool for environmental adaptation. We identified and characterized structural variations (SVs) and found that they were not closely linked with SNP distributions, however, the formation of SVs was closely associated with transposable elements. Furthermore, phylogenetic analysis using SVs revealed a novel <em>A. cerana</em> ecological group not recoverable from the SNP data. Performing environmental association analysis identified a total of 44 SVs likely to be associated with environmental adaptation. Verification and analysis of one of these, a 330 bp deletion in the Atpalpha gene, indicated that this SV may promote the cold adaptation of <em>A. cerana</em> by altering gene expression. Taken together, our study demonstrates the feasibility and utility of applying pan-genome approaches to map and explore genetic feature variations of honeybee populations, and in particular to examine the role of SVs in the evolution and environmental adaptation of <em>A. cerana</em>.</p>
Molecular dynamics trajectories, GROMACS input files, and analysis code from "Rational optimization of a transcription factor activation domain inhibitor" by Basu et. al, Nature Structural & Molecular Biology, 2023
<p>Molecular dynamics trajectories, GROMACS input files, and analysis code from "Rational optimization of a transcription factor activation domain inhibitor" by Basu et. al, Nature Structural & Molecular Biology, 2023</p> <p> </p> <p> </p>
Thermal conductivity analysis of polymer-derived nano-composite via image-base structure reconstruction, computational homogenization and machine learning
<p>This dataset includes supplementary data and utilities for validating simulation results and training machine learning models as outlined in the publication titled "Thermal Conductivity Analysis of Polymer-Derived Nanocomposite via Image-Based Structure Reconstruction, Computational Homogenization, and Machine Learning" (<a href="https://doi.org/10.1002/adem.202302021">Fathidoost, 2024</a>).</p> <p>This dataset containes the microstructure images (identified by particle diameters size \(D_1\) and \(D_2\) volume fraction \(V_\mathrm{f}\) and aspect ratio \(A_\mathrm{r}\)) (see Table 1) and their corresponding homogenized thermal conductivity. these images resemble the microstructure of the monolithic \(\mathrm{(Hf,Ta)C/SiC}\) ceramic following FAST sintering, the material system of this work (<a href="https://doi.org/10.1002/adem.202302021">Fathidoost, 2024</a>). White and black colors within the images represent distinct regions of the material system, respectively referring to former powder particles (FPPs) and sinter necks (SNs), which is explained in this work.</p> <p>Table 1. Parameterized descriptors extracted from the mesoscale SEM image analysis</p> <table> <tbody> <tr> <td>Param.</td> <td>Mean [unit]</td> <td>Std.</td> </tr> <tr> <td>\(D_{1}\)</td> <td>40, 50, 60 [μm]</td> <td>20%</td> </tr> <tr> <td>\(D_{2}\)</td> <td>20, 25, 26, 30, 33, 40 [μm]</td> <td>30%</td> </tr> <tr> <td>\(V_\mathrm{f}\)</td> <td>1.5, 2.0</td> <td>-</td> </tr> <tr> <td>\(A_\mathrm{r}\)</td> <td>35, 40, 45, 55, 60 [%]</td> <td>-</td> </tr> </tbody> </table> <p>This dataset contains:</p> <ul> <li><em>dataset.csv: </em>containing a summary of data including the names of microstructure images, their corresponding geometric details, as well as the first and third principal components of two-point statistics for all images, along with the effective thermal conductivity of the corresponding microstructures. Further details can be found in the associated publication.</li> <li><em>microstructures_images.zip</em>: containing binary cross-section images of the RVEs from synthetic microstructures。</li> <li><em>results.zip:</em> contains all the simulation results based on digitized diffuse-interface microstructures, which can be opened by the post-processing software, such as ParaView.</li> </ul>
Data from: Range-wide genetic analysis of an endangered bumble bee (Bombus affinis) reveals population structure, isolation by distance, and low colony abundance
<p>Declines in bumblebee species ranges and abundances are documented across multiple continents and have prompted the need for research to aid species recovery and conservation. The rusty patched bumblebee (<em>Bombus affinis</em>) is the first federally-listed bumblebee species in North America. We conducted a range-wide population genetics study of <em>B. affinis</em> from across all extant conservation units to inform conservation efforts. To understand the species' vulnerability and help establish recovery targets, we examined population structure, patterns of genetic diversity, and population differentiation. Additionally, we conducted site-level analysis of colony abundance to inform prioritizing areas for conservation, translocation, and other recovery actions. We find substantial evidence of population structuring along an east-to-west gradient. Putative populations show evidence of isolation by distance, high inbreeding coefficients, and a range wide male diploidy rate of ~15%. Our results suggest the Appalachians represents a genetically distinct cluster with high levels of private alleles and substantial differentiation from the rest of the extant range. Site-level analyses suggest low colony abundance estimates for <em>B. affinis</em> compared to similar datasets of stable, co-occurring species. These results lend genetic support to trends from observational studies suggesting B. affinis has undergone a recent decline and exhibits substantial spatial structure. The low colony abundances observed here suggest caution in overinterpreting the stability of populations even where <em>B. affinis</em> is reliably detected interannually. These results help delineate informed management units, provide context for the potential risks of translocation programs, and can help set clear recovery targets for this and other threatened bumblebee species.</p>
Arthropod food webs in the foreland of a retreating glacier: Gut content analysis and structural equation modeling (SEM)
<p>Below- and above-ground arthropod communities were explored at a glacier foreland area in low Arctic Southwest Greenland aiming for a better understanding of the mechanisms behind the arthropod succession driven by increasing temperatures in the context of an Arctic climate change scenario. Arthropods were sampled in 2015 and 2016 along a downslope transect where the microclimate became warmer downhill a chronosequence towards a climax vegetation. The arthropod data sets were analyzed in relation to an environmental data set. Bottom-up controlled population developments were important in the early phase of the vegetation development while top-down prevailed in the later phase of the vegetation development. The shift from bottom-up to top-down cascades between arthropod predators and their potential prey populations was mainly driven by increasing temperatures away from the glacier. Structural equation modeling (SEM) shows bottom-up and top-down controlled food chains as bottom-up control was important for spider and harvestman populations while top-down control was important for ground beetle populations. These mechanisms are closely related to the hunting strategies of the predators as bottom-up mechanisms are connected to a sit-and-wait behavior while top-down mechanisms are related to active-search behavior. The SEM analyzes were supported by DNA metabarcoding as well as by the literature. A consequence of the strong top-down cascades in the later phase of the succession is high rates of intra-guild predation (IGP) among all arthropod predators. Particularly in the guts of the linyphiid spider, <em>Collinsia holmgreni </em>Thorell 1871, trophic linkages to other linyphiid and lycosid spiders were detected. The IGP ratio of <em>C. holmgreni</em> was negatively correlated with the activity density of available ground-living prey. Probably as a consequence of the high IGP among the linyphiid spiders, cold-adapted linyphiid species like <em>C. holmgreni</em> decreased in numbers downhill and became extinct in the warmer climax vegetation, where lycosid spiders dominated. SEM shows that the declining activity densities of the soil fauna, such as collembolans and mites, due to predation, are responsible for the increase in organic matter content in the topsoil.</p>
NASTRA: Accurate analysis of short tandem repeat markers by nanopore sequencing with repeat-structure-aware algorithm
<p><span>Forensic short-tandem repeats (STR) genetic markers are multi-allelic and widely utilized for individual identification, kinship testing, and cell-line authentication. Nanopore sequencing, known for its portability, is emerging as a promising approach for STR typing, facilitating real-time and in-field testing. However, its efficacy is often hampered by sequencing noise. Previous methods rely on alignment-based genotyping, necessitating known alleles, which limits their applicability to unknown alleles. Here, we introduced NASTRA, an innovative allele reference-free tool for precise germline analysis of STR genetic markers. NASTRA incorporates a recursive algorithm to infer repeat structures of allele sequences using only known repeat motifs. Our tests, conducted on 80 individual samples and 8 DNA standards, have demonstrated NASTRA's exceptional 100% accuracy in genotyping nearly all diploid STRs across various multiplex kits and flow cells. It surpasses alignment-based methods in accuracy and speed. In a paternity testing case study, NASTRA accurately identified three relationships among six individuals within an 18-minute sequencing duration. These results underscore NASTRA's ability to perform STR analysis on both NGS and nanopore sequencing platforms, significantly enhancing the utility of nanopore sequencing in relevant applications.</span></p>
Data from: Genetic analysis of red deer (Cervus elaphus) administrative management units in a human-dominated landscape - patterns of genetic diversity, population structure and gene flow
<p><span><span>Red deer (</span><span><em>Cervus elaphus</em></span><span>) throughout central Europe are</span> impacted by different anthropogenic activities including habitat fragmentation, selective hunting, and translocations<span>. This has substantial influences on genetic diversity and the long-term conservation of local populations of this species. Here we use genetic samples from 480 red deer individuals to assess the genetic diversity and differentiation of the 12 administrative management units located in Schleswig Holstein, the northernmost federal state in Germany. </span></span><span><span>We applied multiple analytical approaches and show that the history of local populations (i.e., translocations, culling of individuals outside of designated red deer zones, and anthropogenic infrastructures) has led to comparably low levels of genetic diversity. The mean expected heterozygosity was below 0.6 and we observed on average 4.2 alleles across 12 microsatellite loci. Effective population sizes below the recommended level of 50 were estimated for multiple local populations. </span></span><span><span>Our estimates of genetic structure and gene flow show that red deer in northern Germany are best described as a complex network of asymmetrically connected subpopulations, with high genetic exchange among some local populations and reduced connectivity of others. Genetic diversity was also correlated with population densities of neighboring management units. </span></span></p> <p><span><span>Based on these findings, we suggest that connectivity among existing management units needs to be considered in the practical management of the species, which means that some administrative management units should be managed together, while the effective isolation of other units needs to be mitigated.</span></span></p>
Classification and structural analysis of value chain contracts for biodiversity conservation in the European Union
<p><span>The data provided by this dataset are the raw data published in the paper "<strong>Classification and structural analysis of value chain contracts for biodiversity conservation in the European Union</strong>" (<a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.sftr.2024.100372" target="_blank" rel="noopener"><span><span>https://doi.org/10.1016/j.sftr.2024.100372</span></span></a>). </span></p>
Integrated Analysis of Seismic Sources and Structures: Understanding Earthquake Clustering during Hydraulic Fracturing
<p>The uploaded files include the 3D velocity model, 2D seismic reflection profiles, and horizontal slice utilized in this study.</p>
Cross-spectra used in "Detailed S-wave velocity structure of sediment and crust off Sanriku, Japan by a new analysis method for distributed acoustic sensing data using a seafloor cable and seismic interferometry"
<p>Cross-spectra used in "Detailed S-wave velocity structure of sediment and crust off Sanriku, Japan, derived from distributed acoustic sensing data collected using a seafloor cable with seismic interferometry", by Shun Fukushima, Masanao Shinohara, Kiwamu Nishida, Akiko Takeo, Tomoaki Yamada, and Kiyoshi Yomogida </p> <p>For more information, please contact Shun Fukushima (s-fuku@eri.u-tokyo.ac.jp)</p>
Aboveground herbivory causes belowground changes in twelve oak Quercus species: a phylogenetic analysis of root biomass and non‐structural carbohydrate storage
Plant ecosystem structure is understood to be a result of complex multitrophic interactions. Most multitrophic studies focus on plant aboveground adaptations to aboveground herbivore pressures, neglecting belowground adaptations in response to aboveground damage. Differential investment in root structures may allow plants to compensate for tissue loss or damage due to herbivores. Furthermore, phylogeny may constrain a plant's ability to adapt belowground. We examined the belowground responses of 12 species of oak (Quercus) to varying locations and intensities of simulated herbivore damage. We first established that oak belowground traits responded to aboveground herbivory by measuring patterns of investment in coarse vs fine root structures and re-allocation of non-structural carbohydrates (NSC) to root storage. We then tested whether phylogeny could explain variations in investment patterns using phylogenetic independent contrasts. Plant adaptations to aboveground herbivory included allocating biomass and carbon reserves to root structures, depending on the location and intensity of herbivore damage. NSC re-allocation to root storage was observed when oak species experienced any type of damage, but damage to lateral tissues caused a greater re-allocation than apical damage or control treatments. We found that most belowground responses to aboveground herbivory are species-specific and may be adapted for environmental conditions or type of herbivory. Some responses to herbivore damage, such as changes in fine-root mass and root sugar concentrations, were phylogenetically constrained. Phylogenetic constraints generally occur when there is severe damage at the apical meristem. Plants may adapt to aboveground tissue loss due to varying herbivore pressures (i.e. varying location and intensity of damage) by differentially investing in root types and NSC re-allocation to root storage. Understanding linkages between and phylogenetic constraints of plant belowground responses to aboveground herbivory will improve our understanding of the ecological processes involved in multitrophic interactions.
Fig. 1, 1–10 in Song Repertoire And Comparative Analysis Of Song Structure Of Chaffinch, Fringilla Coelebs (Fringillidae), From The Northeast Of Balkan Region
Fig. 1, 1–10. Sonograms of most frequent song types of Balkan chaffinches.
Fig. 1, 10–18 in Song Repertoire And Comparative Analysis Of Song Structure Of Chaffinch, Fringilla Coelebs (Fringillidae), From The Northeast Of Balkan Region
Fig. 1, 10–18. Sonograms of most frequent song types of Balkan chaffinches.
Data and scripts from: Long term analysis of social structure: evidence of age-based consistent associations in male Alpine ibex
<p>The folder contains the data and scripts used to produce the manuscript: "Long term analysis of social structure: evidence of age-based consistent associations in Alpine ibex" by Alice Brambilla, Achaz von Hardenberg, Claudia Canedoli, Francesca Brivio, Cédric Sueur and Christina R Stanley.</p>
Research data: "Effects of Network Structures on the Production Planning in Closed-loop Supply Chains – A Case Study based Analysis for Lithium-ion Batteries in Europe"
<p>This data set belongs to the paper Effects of Network Structures on the Production Planning in Closed-loop Supply Chains – A Case Study based Analysis for Lithium-ion Batteries in Europe in the International Journal of Production Economics (DOI). The BatPac model, as well as, the model for the economic assessment of the recycling route are not included. The needed data can be found in the file (name). Further, the BatPaC model can be gather from the website of Argonne National Laboratory and the assessment tool for the recycling routes via this DOI: 10.5281/zenodo.6500946.</p> <p> </p> <p>This work is part of the research project Recycling 4.0 (EFRE | ZW 6-85018080), which is funded by the European Regional Development Fund and managed by the development bank for the German federal state of Lower Saxony (NBank).</p>
NUMERICAL ANALYSIS OF FLOW STRUCTURE AND HEAT TRANSFER IN BUBBLING FLUIDIZED BEDS
<p>The videos show the movements of selected particles in different geometries of fluidized bed heat exchangers. Two geometries without auxiliary measures and one with air cushion technology are shown.</p>
Research Data Supporting "Coupling Lipid Nanoparticle Structure and Automated Single Particle Composition Analysis to Design Phospholipase Responsive Nanocarriers"
<p>Raw research data supporting Barriga, Pence, et al. 2022, Advanced Materials. <a href="https://doi.org/10.1002/adma.202200839">https://doi.org/10.1002/adma.202200839</a></p>
Finite element analysis related to MiGriBot, a microrobotic structure
<p>The dataset presents the input and the results of three particular simulations made with ANSYS Workbench, a FEM software. Files contain information about the setting up of the analysis and results data.<br> There is information about the displacement of the parallel mechanism under actuation, a pick-and-place simulation, a modal analysis at the home configuration, and an evaluation of the stiffness of the gripper.</p>
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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OpenNeuro
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